Method and system for converting hormone detection data

Abstract

A method for converting hormone data detected by different detection methods is provided, the method including: acquiring first detection values ​​of a hormone from a first platform; acquiring second detection values ​​of the hormone from a second platform; fitting the first detection values ​​and the second detection values ​​using Passing-Bablok regression; determining whether there is a systematic difference between the first detection values ​​and the second detection values ​​based on the fitting result of the Passing-Bablok regression; if there is no systematic difference between the first detection values ​​and the second detection values, converting the first detection value or the second detection value based on the fitting formula of the Passing-Bablok regression; and if there is a systematic difference between the first detection values ​​and the second detection values, fitting the first detection value and the second detection values ​​based on the fitting formula of the spline regression and converting the first detection value or the second detection value based on the fitting formula of the spline regression.

Description

Detailed Description of the Invention

[0001] [Technical field] The present application relates to a method and system for converting hormone detection data obtained by different detection methods, and in particular to a method and system for converting sex hormone detection data. [Background technology]

[0002] Hormones are substances secreted directly into the bloodstream by endocrine organs or tissues in humans and animals and exert specific effects on the body. Tissues such as the gastrointestinal tract and placenta also secrete hormones, such as pancreatic secretagogue, gastric secretagogue, and chorionic gonadotropin. The coordinated action of various hormones is necessary to maintain the body's metabolism and functions. From a chemical perspective, some hormones are phenolic derivatives, such as epinephrine and thyroxine; some are polypeptides or proteins, such as pituitary hormone-releasing factor, pituitary hormones, insulin, glucagon, calcitonin, and parathyroid hormone; and some are steroid compounds, such as androgens, estrogens, and adrenocortical hormones. Many hormone preparations and synthetic products have important uses in medicine and animal husbandry.

[0003] An important category of hormones is the sex hormone. Sex hormones (which are essentially lipids) are synthesized in animal tissues, such as the gonads, placenta, and adrenal zona reticularis. They promote genital maturation, the development of secondary sexual characteristics, and the maintenance of sexual function. The ovaries of female animals primarily secrete two sex hormones, estrogen and progesterone, while the testes of male animals primarily secrete androgens, primarily testosterone. Hormones secreted by the hypothalamic-pituitary-gonadal axis or hypothalamic-pituitary-adrenal axis are roughly classified into three categories based on their chemical structure. The first category is steroids, such as adrenal cortical hormones and steroid sex hormones. The second category is amino acids, including thyroxine, adrenal medullary hormones, and pineal hormones. The third category of hormones is composed of peptides and proteins, such as hypothalamic hormones, pituitary hormones, gastrointestinal hormones, and calcitonin. The third category of hormones is basically a protein polymer substance, and from an immunological point of view, the third category of hormones has multiple antigenic epitopes and can usually be detected using the double antibody sandwich method.

[0004] Anti-Müllerian hormone (AMH), which contributes to the regression of Müllerian ducts during the sexual differentiation of male embryos, was first discovered by Jost in 1947. In 1999, Dulinger et al. used AMH gene knockout mice to discover that AMH inhibits primordial follicle mobilization, placing AMH in the third category of hormones. Since then, researchers have begun to study and clinically apply AMH in reproductive science and developed kits to detect it. During ovarian stimulation, AMH is an important indicator of ovarian reserve. AMH is also considered an ideal marker for determining the dosage of recombinant human follicle-stimulating hormone (rFSH) adrenocorticotropic hormone in individualized ovarian stimulation plans during IVF treatment. AMH is gradually being recognized as an important parameter in reproductive science. Therefore, accurate, efficient, and reliable AMH detection methods are becoming increasingly important.

[0005] Currently, there are various AMH detection methods in the related field, among which new automated anti-Müllerian hormone detection methods are gradually replacing the original ELISA detection method. Currently available automated anti-Müllerian hormone detection methods include the Elecsys AMH method provided by Roche (hereinafter sometimes abbreviated as the "Roche method", "Roche method", or "Elecsys method"), the Access AMH method provided by Beckman Coulter (hereinafter sometimes abbreviated as the "Beckman method", "Beckman method", or "Access method"), the chemiluminescent AMH detection method provided by Kangrun (hereinafter sometimes abbreviated as the "Kangrun chemiluminescent method" or "Kangrun chemiluminescent method"), and the enzyme-linked immunosorbent AMH detection method provided by Kangrun (hereinafter sometimes abbreviated as the Kangrun Anshlab method or the Kangrun enzyme immunoassay Anshlab method).

[0006] In 2014, Roche offered the Elecsys method, a detection method based on the monoclonal antibodies F2B 12 / H and F2B 7 / A. Subsequently, Beckman also offered the Access method, which also uses the same monoclonal antibodies. Because Roche and Beckman use similar antibodies, the main difference between the two is the development of the detection method. Furthermore, Kangrun, a Chinese company, has developed an automated AMH detection method using another monoclonal antibody coded 1B63D7.

[0007] Estrogens are the major female hormone. They promote the maturation of female accessory sex organs and the development of secondary sexual characteristics, and maintain normal sexual desire and reproductive function. They are primarily estradiol (E2). They are inactivated in the liver and converted to estriol and estrone, which are then conjugated with glucuronic acid and excreted in urine. During pregnancy, the placenta can secrete large amounts of estriol. Estradiol (E2), first discovered by Edward Doisy 77 years ago, has been proven to play an important role in various physiological processes. Therefore, E2 quantification is widely used in the clinical evaluation of female and male conditions or diseases, including fertility testing, ovarian stimulation monitoring during assisted reproductive technologies, pregnancy, polycystic ovary syndrome (PCOS), hypogonadism, amenorrhea, and E2-related tumors. Methods used for E2 quantification include immunoassays, gas chromatography-mass spectrometry (GC-MS), and liquid chromatography-tandem mass spectrometry (LC-MS / MS). Although mass spectrometry has superior specificity and sensitivity to immunoassays, its cost and technical complexity limit its application as a routine clinical method. Automated immunoassay platforms, which do not require complex sample extraction procedures, have become the first choice in most clinical laboratories due to their high throughput, reproducibility, and short turnaround time.

[0008] Most direct automated immunoassay platforms are optimized to measure E2 concentrations between 20 and 2000 pg / mL. This concentration range can meet almost all clinical objectives in obstetrics and gynecology and is suitable for assisted reproductive technology (ART) in hospitals. However, standardizing E2 measurement within such a wide concentration range is challenging. It has been reported that assay sensitivity for E2 testing at low levels is affected. In hospital clinical laboratories, clinicians have observed significant heterogeneity among immunoassay platforms for various automated devices, especially at low E2 levels, such as below 200 pg / mL. This may be due to a lack of international calibrators for E2, differences in calibration point assignments, and systematic differences in detection. Variations in E2 levels, especially in the low-level range, inevitably cause considerable confusion among clinicians regarding the interpretation of results. [DISCLOSURE OF THE INVENTION]

[0009] Although several major sex hormones mentioned in the background art above, such as AMH and E2, all play important roles in clinical detection and diagnosis, there are various methods and platforms for detecting these sex hormones, resulting in the inability to effectively and integratedly evaluate and analyze test results from various sources.

[0010] Taking AMH as an example, there are currently various AMH detection methods on the market, and the AMH values ​​obtained by these methods are not consistent. Therefore, AMH results obtained by a patient using a specific AMH detection method at one hospital cannot be adopted at other hospitals that use other AMH detection methods. This significantly increases the medical burden on patients and the complexity of clinical practice, hindering the clinical application of online assessment tools for AMH. Using AMH as one of the most important predictive indicators, the inventors of this application have established several online prediction tools, including an ovarian reserve assessment tool (http: / / 121.43.113.123:9999 / ), a PCOS screening assessment tool (http: / / 121.43.113.123:8888 / ), an oocyte retrieval prediction tool (http: / / 121.43.113.123:8002 / ), and an online tool for guiding the starting and adjusting doses of exogenous FSH administration (http: / / 121.43.113.123:8004). Since AMH has become an increasingly important evaluation parameter in reproductive medicine, in order to conveniently apply, integrate and calculate the AMH data of patients detected by different hospitals and detection institutions, this field urgently needs a calculation method and system that can convert or integrate the AMH values ​​obtained by different detection methods.

[0011] Take estradiol, for example. Estradiol is a C18 steroid hormone and the most biologically active of the estrogens. It is produced in the testes in men, the ovaries in women, and the placenta during pregnancy, and its concentration varies according to the menstrual cycle. Its primary physiological function is to promote the formation and development of ovarian follicles, promote the development of the ovaries and female reproductive organs, and promote the emergence of female secondary sexual characteristics. It can also promote the synthesis of various transport proteins in the liver. Circulating estradiol levels are one of the indicators of the function of the hypothalamus-pituitary-reproductive target gland axis and have certain diagnostic significance in diagnosing endocrine and gynecological disorders, such as precocious puberty, growth retardation, and infertility. In hospital clinical laboratories, clinicians have observed significant heterogeneity among immunoassay platforms of various automated devices, especially at low E2 levels, such as below 200 pg / mL. This may be due to the lack of international calibrators for E2 and differences in calibration point assignments. Variations in E2 levels, especially in the low range, are bound to cause considerable confusion among clinicians regarding the interpretation of results.

[0012] Specifically, the technical proposal of this application is as follows:

[0013] 1. A method for converting hormone data detected by different detection methods, comprising: obtaining a first detection value of the hormone from a first platform; obtaining a second detection value of the hormone from a second platform; fitting the first detected value and the second detected value using Passing-Bablok regression; determining whether there is a systematic difference between the first detected value and the second detected value based on a fitting result of the Passing-Bablok regression; If there is no systematic difference between the first detected value and the second detected value, converting the first detected value or the second detected value based on a fitting formula of the Passing-Bablok regression; and if there is a systematic difference between the first detected value and the second detected value, fitting the first detected value and the second detected value based on a spline regression, and converting the first detected value or the second detected value based on the fitting formula of the spline regression. 2. The method described in item 1, wherein determining whether there is a systematic difference between the first detection value and the second detection value based on the fitting result of the Passing-Bablok regression is determining whether there is a systematic difference between the first detection value and the second detection value by calculating a 95% confidence interval of the intercept of the linear regression result. 3. If the 95% confidence interval of the intercept includes 0, it is determined that there is no systematic difference between the first detection value and the second detection value; If the 95% confidence interval of the intercept does not include 0, it is determined that there is a systematic difference between the first detection value and the second detection value. The method described in item 2. 4. When fitting the first detection value and the second detection value based on the spline regression, identifying the nodes of the spline regression using characteristic nodes and statistical indicators; The method according to any one of Items 1 to 3. 5. The method according to item 4, wherein the statistical index is AIC (Akaike Information Criterion) index or BIC (Bayes Information Criterion) index. 6. The method according to any one of items 1 to 5, wherein the hormone is a sex hormone, preferably selected from hypothalamic-pituitary-gonadal axis hormones including hypothalamic hormones, pituitary prolactin (PRL), follicle-stimulating hormone (FSH), luteinizing hormone (LH), anti-Müllerian hormone (AMH), inhibin B, estradiol (E2), testosterone (T), dehydroepiandrosterone sulfate (DHEA-S), estriol (E3), and progesterone (P), and preferably anti-Müllerian hormone (AMH) or estradiol (E2). 7. When the sex hormone is anti-Mullerian hormone (AMH), the first platform is a Roche AMH detection platform, and the second platform is a Kangrun chemiluminescent AMH detection platform, converting the detection results of the Roche AMH detection platform and the Kangrun chemiluminescent AMH detection platform using Passing-Bablok regression; Preferably, the formula for converting Kangrun chemiluminescent AMH(X) to Roche AMH(Y) is: Roche AMH=a1+b1*Kangrun chemiluminescent AMH; In the formula, a1 is an arbitrary value selected from −0.0035 to 0.0303, and b1 is an arbitrary value selected from 0.85 to 0.8844. Preferably, the formula for converting Roche AMH(X) to Kangrun chemiluminescent AMH(Y) is: Kangrun chemiluminescence AMH = a2 + b2 * Roche AMH; In the formula, a2 is an arbitrary value selected from -0.0356 to 0.00393, and b2 is an arbitrary value selected from 1.1307 to 1.1765. The method according to item 6. 8. When the sex hormone is anti-Mullerian hormone (AMH), the first platform is a Beckman AMH detection platform, and the second platform is a Roche AMH detection platform, converting the detection results of the Beckman AMH detection platform and the Roche AMH detection platform using spline regression; Preferably, the formula for converting Roche AMH(X) to Beckman AMH(Y) is: Beckman AMH=a3+b3*Roche AMH+c3*g1(Roche AMH-1)+d3*g2(Roche AMH-9), where Roche AMH<=1 ng / ml, then g1=0 and g2=0, in which case the formula becomes: Beckman AMH=a3+b3*Roche AMH If Roche AMH > 1 ng / ml and <= 9 ng / ml, then g1 = 1 and g2 = 0, in which case the formula becomes: Beckman AMH=a3+b3*Roche AMH+c3*(Roche AMH-1) If Roche AMH>9ng / ml, then g1=1 and g2=1, in which case the formula becomes: Beckman AMH=a3+b3*Roche AMH+c3*(Roche AMH-1)+d3*(Roche AMH-9) In the formula, a3 is an arbitrary value selected from -0.28809 to 0.30461, b3 is an arbitrary value selected from 0.665236 to 1.430824, c3 is an arbitrary value selected from 0.073606 to 0.900514, and d3 is an arbitrary value selected from -0.70344 to -0.42116, Preferably, the formula for converting Beckman AMH(X) to Roche AMH(Y) is: Roche AMH=a4+b4*Beckman AMH+c4*g1(Beckman AMH-0.5)+d4*g2(Beckman AMH-1) where if the Beckman AMH value is <=0.5 ng / ml, then g1=0 and g2=0, in which case the formula becomes: Roche AMH=a4+b4*Beckman AMH If the Beckman AMH value is >0.5 ng / ml and <=1 ng / ml, then g1=1 and g2=0, in which case the formula becomes: Roche AMH=a4+b4*Beckman AMH+c4*(Beckman AMH-0.5) If the Beckman AMH value is >1 ng / ml, then g1 = 1 and g2 = 1, in which case the formula becomes: Roche AMH=a4+b4*Beckman AMH+c4*(Beckman AMH-0.5)+d4*(Beckman AMH-1), In the formula, a4 is an arbitrary value selected from -0.42466 to 0.41822, b4 is an arbitrary value selected from -0.11202 to 2.17363, c4 is an arbitrary value selected from -1.96122 to 1.21734, and d4 is an arbitrary value selected from -0.49419 to 0.66553. The method according to item 6. 9. When the sex hormone is anti-Müllerian hormone (AMH), the first platform is a Beckman AMH detection platform, and the second platform is a Kangrun chemiluminescent AMH detection platform, converting the detection results of the Beckman AMH detection platform and the Kangrun chemiluminescent AMH detection platform using spline regression; Preferably, the formula for converting Beckman AMH(X) to Kangrun chemiluminescent AMH(Y) is: Kangrun chemiluminescence AMH=a5+b5*Beckman AMH+c5*g1(Beckman AMH-1)+d5*g2(Beckman AMH-4)+e5*g3(Beckman AMH-13) where, if the Beckman AMH value is <=1 ng / ml, then g1=0, g2=0, and g3=0, and in this case, the formula becomes: Kangrun chemiluminescence AMH = a5 + b5 * Beckman AMH If the Beckman AMH value is >1 ng / ml and <=4 ng / ml, then g1=1, g2=0, and g3=0, and in this case the formula becomes: Kangrun chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) If the Beckman AMH value is >4 ng / ml and <=13 ng / ml, then g1=1, g2=1, and g3=0, and in this case the formula becomes: Kangrun chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) + d5 * (Beckman AMH-4) If the Beckman AMH value is >13 ng / ml, then g1 = 1, g2 = 1, and g3 = 1, and in this case, the formula becomes: Kangrun chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) + d5 * (Beckman AMH-4) + e5 * (Beckman AMH-13) In the formula, a5 is any value selected from -0.24101 to 0.26258, b5 is any value selected from 0.72643 to 1.42037, c5 is any value selected from -0.78107 to 0.04326, d5 is any value selected from 0.29488 to 0.57880, and e5 is any value selected from -0.71455 to -0.47130. Preferably, the formula for converting Kangrun chemiluminescent AMH(X) to Beckman AMH(Y) is: Beckman AMH = a6 + b6 * Kangrun Chemiluminescent AMH + c6 * g1 (Kangrun Chemiluminescent AMH-0.5) + d6 * g2 (Kangrun Chemiluminescent AMH-13) In the formula, when the Kangrun chemiluminescence AMH value is less than 0.5 ng / ml, g1=0 and g2=0. In this case, the formula becomes: Beckman AMH = a6 + b6 * Kangrun chemiluminescent AMH When the Kangrun chemiluminescence AMH value is >0.5 and <=13 ng / ml, g1=1 and g2=0, and in this case, the formula becomes: Beckman AMH = a6 + b6 * Kangrun chemiluminescent AMH + c6 * (Kangrun chemiluminescent AMH-0.5) If the Kangrun chemiluminescence AMH value is >13 ng / ml, then g1=1 and g2=1, and in this case, the formula becomes: Beckman AMH = a6 + b6 * Kangrun Chemiluminescent AMH + c6 * (Kangrun Chemiluminescent AMH-0.5) + d6 * (Kangrun Chemiluminescent AMH-13) In the formula, a6 is an arbitrary value selected from -0.45082 to 0.54656, b6 is an arbitrary value selected from -0.35329 to 1.82169, c6 is an arbitrary value selected from -0.63742 to 1.56010, and d6 is an arbitrary value selected from -0.52283 to -0.22757. The method according to item 6. 10. When the sex hormone is anti-Müllerian hormone (AMH), the sex hormone is anti-Müllerian hormone (AMH), the first platform is a Kangrun chemiluminescence AMH detection platform, and the second platform is a Kangrun enzyme immunoassay (Anshlab) AMH detection platform, using spline regression to transform the detection results of the Kangrun chemiluminescence AMH detection platform and the Kangrun enzyme immunoassay (Anshlab) AMH detection platform; Preferably, the formula for converting Kangrun chemiluminescent AMH (X) to Kangrun enzyme immunoassay (Anshlab) AMH (Y) is: Kangrun Enzyme Immunosorbent Assay (Anshlab) AMH = a7 + b7 * Kangrun Chemiluminescent AMH + c7 * g1 * (Kangrun Chemiluminescent AMH-2) + d7 * g2 * (Kangrun Chemiluminescent AMH-4) + e7 * g3 * (Kangrun Chemiluminescent AMH-7) In the formula, a7 is an arbitrary value selected from -0.31000 to 0.20149, b7 is an arbitrary value selected from 0.73863 to 1.10064, c7 is an arbitrary value selected from -0.08941 to 0.51000, d7 is an arbitrary value selected from 0.08121 to 0.54582, and e7 is an arbitrary value selected from -0.70493 to -0.42738. Furthermore, if Kangrun chemiluminescent AMH <= 2 ng / ml, then g1 = 0, in which case the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescence AMH; When Kangrun chemiluminescent AMH is >2 ng / ml and <=4 ng / ml, g1=1 and g2=0, in which case the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 (Kangrun chemiluminescent AMH-2), When Kangrun chemiluminescent AMH is >4 ng / ml and <=7 ng / ml, then g1=1 and g2=1, and in this case, the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 (Kangrun chemiluminescent AMH-2) + d7 * g2 (Kangrun chemiluminescent AMH-4), If Kangrun chemiluminescent AMH > 7ng / ml, then g1 = 1, g2 = 1, and g3 = 1, and in this case, the formula becomes: Kangrun Enzyme Immunosorbent Assay (Anshlab) AMH = a7 + b7 * Kangrun Chemiluminescent AMH + c7 * g1 (Kangrun Chemiluminescent AMH-2) + d7 * g2 (Kangrun Chemiluminescent AMH-4) + e7 * g3 (Kangrun Chemiluminescent AMH-7) The method according to item 6. 11. When the sex hormone is estradiol E2, the first platform is a Kangrun estradiol detection platform, and the second platform is a Siemens estradiol detection platform, converting the detection results of Kangrun estradiol and Siemens estradiol using spline regression; Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value + c8 * g1 (Kangrun E2 detection value - 660) + d8 * g2 (Kangrun E2 detection value - 2030) During the ceremony, When the Kangrun E2 detection value is ≦660 pmol / L, g1=0 and g2=0. In this case, the above formula becomes: Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value When the Kangrun E2 detection value is >660 pmol / L and <=2030 pmol / L, g1=0 and g2=0. In this case, the above formula becomes: Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value + c8 * (Kangrun E2 detection value - 660) If the Kangrun E2 detection value is >2030 pmol / L, then g1 = 0 and g2 = 1, and in this case, the above formula becomes: Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value + c8 * (Kangrun E2 detection value - 660) + d8 * (Kangrun E2 detection value - 2030) In the formula, a7 is an arbitrary value selected from -93.069 to -6.91207, b7 is an arbitrary value selected from 1.310892 to 1.569808, c7 is an arbitrary value selected from -0.8957 to -0.52322, and d7 is an arbitrary value selected from -0.08505 to 0.085318. The method according to item 7. 12. A system for converting hormone data detected by different detection methods, comprising: a sub-module that obtains a first detection value of the hormone from a first platform; a sub-module that obtains a second detection value of the hormone from a second platform; a sub-module for fitting the first detected value and the second detected value using Passing-Bablok regression; a sub-module for determining whether there is a systematic difference between the first detected value and the second detected value based on a fitting result of the Passing-Bablok regression; a submodule for determining whether there is a systematic difference between the first detection value and the second detection value based on a fitting result of the Passing-Bablok regression; If there is no systematic difference between the first detected value and the second detected value, converting the first detected value or the second detected value based on a fitting formula of the Passing-Bablok regression; If there is a systematic difference between the first detected value and the second detected value, the system performs a step of fitting the first detected value and the second detected value based on a spline regression and converting the first detected value or the second detected value based on a fitting formula of the spline regression. 13. The system of claim 12, wherein determining whether there is a systematic difference between the first detection value and the second detection value based on the fitting result of the Passing-Bablok regression is determining whether there is a systematic difference between the first detection value and the second detection value by calculating a 95% confidence interval of an intercept of a linear regression result. 14. If the 95% confidence interval of the intercept includes 0, it is determined that there is no systematic difference between the first detection value and the second detection value; If the 95% confidence interval of the intercept does not include 0, it is determined that there is a systematic difference between the first detection value and the second detection value. The system of claim 13. 15. When fitting the first detected value and the second detected value based on the spline regression, identifying the nodes of the spline regression using characteristic nodes and statistical indicators. Item 15. The system according to any one of Items 12 to 14. 16. The system according to item 15, wherein the statistical index is an AIC (Akaike Information Criterion) index or a BIC (Bayes Information Criterion) index. 17. The system according to any one of items 12 to 16, wherein the hormone is a sex hormone selected from hypothalamic-pituitary-gonadal axis hormones including hypothalamic hormones, pituitary prolactin (PRL), follicle-stimulating hormone (FSH), luteinizing hormone (LH), anti-Müllerian hormone (AMH), inhibin B, estradiol (E2), testosterone (T), dehydroepiandrosterone sulfate (DHEA-S), estriol (E3), and progesterone (P), and preferably anti-Müllerian hormone (AMH) or estradiol (E2). 18. When the sex hormone is anti-Mullerian hormone (AMH), the first platform is a Roche AMH detection platform, and the second platform is a Kangrun chemiluminescent AMH detection platform, converting the detection results of the Roche AMH detection platform and the Kangrun chemiluminescent AMH detection platform using Passing-Bablok regression; Preferably, the formula for converting Kangrun chemiluminescent AMH(X) to Roche AMH(Y) is: Roche AMH=a1+b1*Kangrun chemiluminescent AMH; In the formula, a1 is an arbitrary value selected from −0.0035 to 0.0303, and b1 is an arbitrary value selected from 0.85 to 0.8844. Preferably, the formula for converting Roche AMH(X) to Kangrun chemiluminescent AMH(Y) is: Kangrun chemiluminescence AMH = a2 + b2 * Roche AMH; In the formula, a2 is an arbitrary value selected from -0.0356 to 0.00393, and b2 is an arbitrary value selected from 1.1307 to 1.1765. Item 18. The system according to item 17. 19. When the sex hormone is anti-Mullerian hormone (AMH), the first platform is a Beckman AMH detection platform, and the second platform is a Roche AMH detection platform, converting the detection results of the Beckman AMH detection platform and the Roche AMH detection platform using spline regression; Preferably, the formula for converting Roche AMH(X) to Beckman AMH(Y) is: Beckman AMH=a3+b3*Roche AMH+c3*g1(Roche AMH-1)+d3*g2(Roche AMH-9), where Roche AMH<=1 ng / ml, then g1=0 and g2=0, in which case the formula becomes: Beckman AMH=a3+b3*Roche AMH If Roche AMH > 1 ng / ml and <= 9 ng / ml, then g1 = 1 and g2 = 0, in which case the formula becomes: Beckman AMH=a3+b3*Roche AMH+c3*(Roche AMH-1) If Roche AMH>9ng / ml, then g1=1 and g2=1, in which case the formula becomes: Beckman AMH=a3+b3*Roche AMH+c3*(Roche AMH-1)+d3*(Roche AMH-9) In the formula, a3 is an arbitrary value selected from -0.28809 to 0.30461, b3 is an arbitrary value selected from 0.665236 to 1.430824, c3 is an arbitrary value selected from 0.073606 to 0.900514, and d3 is an arbitrary value selected from -0.70344 to -0.42116, Preferably, the formula for converting Beckman AMH(X) to Roche AMH(Y) is: Roche AMH=a4+b4*Beckman AMH+c4*g1(Beckman AMH-0.5)+d4*g2(Beckman AMH-1) where if the Beckman AMH value is <=0.5 ng / ml, then g1=0 and g2=0, in which case the formula becomes: Roche AMH=a4+b4*Beckman AMH If the Beckman AMH value is >0.5 ng / ml and <=1 ng / ml, then g1=1 and g2=0, in which case the formula becomes: Roche AMH=a4+b4*Beckman AMH+c4*(Beckman AMH-0.5) If the Beckman AMH value is >1 ng / ml, then g1 = 1 and g2 = 1, in which case the formula becomes: Roche AMH=a4+b4*Beckman AMH+c4*(Beckman AMH-0.5)+d4*(Beckman AMH-1), In the formula, a4 is an arbitrary value selected from -0.42466 to 0.41822, b4 is an arbitrary value selected from -0.11202 to 2.17363, c4 is an arbitrary value selected from -1.96122 to 1.21734, and d4 is an arbitrary value selected from -0.49419 to 0.66553. Item 18. The system according to item 17. 20. When the sex hormone is anti-Müllerian hormone (AMH), the first platform is a Beckman AMH detection platform, and the second platform is a Kangrun chemiluminescent AMH detection platform, converting the detection results of the Beckman AMH detection platform and the Kangrun chemiluminescent AMH detection platform using spline regression; Preferably, the formula for converting Beckman AMH(X) to Kangrun chemiluminescent AMH(Y) is: Kangrun chemiluminescence AMH=a5+b5*Beckman AMH+c5*g1(Beckman AMH-1)+d5*g2(Beckman AMH-4)+e5*g3(Beckman AMH-13) where, if the Beckman AMH value is <=1 ng / ml, then g1=0, g2=0, and g3=0, and in this case, the formula becomes: Kangrun chemiluminescence AMH = a5 + b5 * Beckman AMH If the Beckman AMH value is >1 ng / ml and <=4 ng / ml, then g1=1, g2=0, and g3=0, and in this case the formula becomes: Kangrun chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) If the Beckman AMH value is >4 ng / ml and <=13 ng / ml, then g1=1, g2=1, and g3=0, and in this case the formula becomes: Kangrun chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) + d5 * (Beckman AMH-4) If the Beckman AMH value is >13 ng / ml, then g1 = 1, g2 = 1, and g3 = 1, and in this case, the formula becomes: Kangrun chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) + d5 * (Beckman AMH-4) + e5 * (Beckman AMH-13) In the formula, a5 is any value selected from -0.24101 to 0.26258, b5 is any value selected from 0.72643 to 1.42037, c5 is any value selected from -0.78107 to 0.04326, d5 is any value selected from 0.29488 to 0.57880, and e5 is any value selected from -0.71455 to -0.47130. Preferably, the formula for converting Kangrun chemiluminescent AMH(X) to Beckman AMH(Y) is: Beckman AMH = a6 + b6 * Kangrun Chemiluminescent AMH + c6 * g1 (Kangrun Chemiluminescent AMH-0.5) + d6 * g2 (Kangrun Chemiluminescent AMH-13) In the formula, when the Kangrun chemiluminescence AMH value is less than 0.5 ng / ml, g1=0 and g2=0. In this case, the formula becomes: Beckman AMH = a6 + b6 * Kangrun chemiluminescent AMH When the Kangrun chemiluminescence AMH value is >0.5 and <=13 ng / ml, g1=1 and g2=0, and in this case, the formula becomes: Beckman AMH = a6 + b6 * Kangrun chemiluminescent AMH + c6 * (Kangrun chemiluminescent AMH-0.5) If the Kangrun chemiluminescence AMH value is >13 ng / ml, then g1=1 and g2=1, and in this case, the formula becomes: Beckman AMH = a6 + b6 * Kangrun Chemiluminescent AMH + c6 * (Kangrun Chemiluminescent AMH-0.5) + d6 * (Kangrun Chemiluminescent AMH-13) In the formula, a6 is an arbitrary value selected from -0.45082 to 0.54656, b6 is an arbitrary value selected from -0.35329 to 1.82169, c6 is an arbitrary value selected from -0.63742 to 1.56010, and d6 is an arbitrary value selected from -0.52283 to -0.22757. Item 18. The system according to item 17. 21. When the sex hormone is anti-Müllerian hormone (AMH), the sex hormone is anti-Müllerian hormone (AMH), the first platform is a Kangrun chemiluminescence AMH detection platform, and the second platform is a Kangrun enzyme immunoassay (Anshlab) AMH detection platform, using spline regression to transform the detection results of the Kangrun chemiluminescence AMH detection platform and the Kangrun enzyme immunoassay (Anshlab) AMH detection platform; Preferably, the formula for converting Kangrun chemiluminescent AMH (X) to Kangrun enzyme immunoassay (Anshlab) AMH (Y) is: Kangrun Enzyme Immunosorbent Assay (Anshlab) AMH = a7 + b7 * Kangrun Chemiluminescent AMH + c7 * g1 * (Kangrun Chemiluminescent AMH-2) + d7 * g2 * (Kangrun Chemiluminescent AMH-4) + e7 * g3 * (Kangrun Chemiluminescent AMH-7) In the formula, a7 is an arbitrary value selected from -0.31000 to 0.20149, b7 is an arbitrary value selected from 0.73863 to 1.10064, c7 is an arbitrary value selected from -0.08941 to 0.51000, d7 is an arbitrary value selected from 0.08121 to 0.54582, and e7 is an arbitrary value selected from -0.70493 to -0.42738. Furthermore, if Kangrun chemiluminescent AMH <= 2 ng / ml, then g1 = 0, in which case the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescence AMH; When Kangrun chemiluminescent AMH is >2 ng / ml and <=4 ng / ml, g1=1 and g2=0, in which case the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 (Kangrun chemiluminescent AMH-2), When Kangrun chemiluminescent AMH is >4 ng / ml and <=7 ng / ml, then g1=1 and g2=1, and in this case, the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 (Kangrun chemiluminescent AMH-2) + d7 * g2 (Kangrun chemiluminescent AMH-4), If Kangrun chemiluminescent AMH > 7ng / ml, then g1 = 1, g2 = 1, and g3 = 1, and in this case, the formula becomes: Kangrun Enzyme Immunosorbent Assay (Anshlab) AMH = a7 + b7 * Kangrun Chemiluminescent AMH + c7 * g1 (Kangrun Chemiluminescent AMH-2) + d7 * g2 (Kangrun Chemiluminescent AMH-4) + e7 * g3 (Kangrun Chemiluminescent AMH-7) Item 18. The system according to item 17. 22. When the sex hormone is estradiol E2, the first platform is a Kangrun estradiol detection platform, and the second platform is a Siemens estradiol detection platform, converting the detection results of Kangrun estradiol and Siemens estradiol using spline regression; Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value + c8 * g1 (Kangrun E2 detection value - 660) + d8 * g2 (Kangrun E2 detection value - 2030) During the ceremony, When the Kangrun E2 detection value is ≦660 pmol / L, g1=0 and g2=0. In this case, the above formula becomes: Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value When the Kangrun E2 detection value is >660 pmol / L and <=2030 pmol / L, g1=0 and g2=0. In this case, the above formula becomes: Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value + c8 * (Kangrun E2 detection value - 660) If the Kangrun E2 detection value is >2030 pmol / L, then g1 = 0 and g2 = 1, and in this case, the above formula becomes: Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value + c8 * (Kangrun E2 detection value - 660) + d8 * (Kangrun E2 detection value - 2030) In the formula, a7 is an arbitrary value selected from -93.069 to -6.91207, b7 is an arbitrary value selected from 1.310892 to 1.569808, c7 is an arbitrary value selected from -0.8957 to -0.52322, and d7 is an arbitrary value selected from -0.08505 to 0.085318. Item 18. The system according to item 17. [Effects of the invention]

[0014] The method and system of the present application enable the conversion and calculation of serum hormone detection values ​​obtained using different hormone detection methods, allowing patients to conveniently standardize hormone detection data obtained from different hospitals or laboratories. That is, the results of the same hormone test item from different hospitals or different detection systems can be mutually recognized through specific formula conversion. This data conversion, on the one hand, reduces the cost of sex hormone detection when patients visit different hospitals or laboratories. On the other hand, it is useful for promoting artificial intelligence software based on data from specific detection platforms and for applying the same indicators to different detection platforms, thereby contributing to the subsequent development of digital medicine. For example, the inventor's team used reproductive medicine big data from Peking University Third Hospital to build various digital medical applications, including tools for assessing ovarian reserve, assessing oocyte count, screening for PCOS, and calculating the starting and adjusting doses of exogenous FSH administration. All of these tools require AMH levels to be entered, but the inventor's tool is a prediction based solely on the Kangrun chemiluminescence AMH hormone level on the Kangrun Anshlab platform. If it needs to be applied to different AMH detection brands, the present invention must be adapted for conversion, thereby reducing the cost of hormone detection for patients and ensuring the accuracy of digital medical tools. [Brief explanation of the drawings]

[0015] Various other advantages and merits of the present application will become apparent to those skilled in the art upon reading the following detailed description of the preferred embodiments. The drawings in the specification are intended only to illustrate the preferred embodiments and are not to be considered as limiting the present application. Obviously, the drawings described below are only some embodiments of the present application, and those skilled in the art can derive other drawings based on these drawings without any creative effort. In addition, the same parts are designated by the same reference numerals throughout the drawings. [Figure 1]1A, 1B, and 1C show the fitting results of Roche AMH and Kangrun AMH, the agreement between the measurement results of Roche AMH and Kangrun AMH, and a mountain-shaped graph of Kangrun AMH and Roche AMH, respectively. [Figure 2] These are the fitting results of Deming regression and Passing-Bablok regression for the E2 results. [Figure 3] 10 is a Bland-Altman plot showing the agreement between Kangrun and Siemens for E2 results. [Figure 4] FIG. 10 is a graph showing a mountain-shaped graph of Siemens E2 detection values ​​and Kangrun E2 detection values. [Figure 5] Figure 1 shows a comparison of predictions made using the E2 platform between Passing-Bablok regression and spline regression transformations. [Figure 6] Figure 1 shows the number of nodes in the linear spline regression of Kangrun chemiluminescence AMH detection results and Kangrun enzyme immunoassay (Anshlab) AMH detection. [Figure 7] FIG. 1 shows grouping of Kangrun chemiluminescence AMH detection results and Kangrun enzyme immunoassay (Anshlab) AMH detection data. [Figure 8] FIG. 1 shows Kangrun enzyme immunoassay (Anshlab) AMH data calculated using platform transformation formulas for all data. [Figure 9] FIG. 1 shows Kangrun enzyme immunoassay (Anshlab) AMH data calculated using platform conversion formulas for some data with low values ​​(<7 ng / ml). DETAILED DESCRIPTION OF THE INVENTION

[0016] [Details of the invention] Specific embodiments of the present invention will now be described in more detail. It should be understood, however, that the present invention may be embodied in many different forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0017] It should be noted that specific terms are used in the specification and claims to refer to specific components. Those skilled in the art should understand that different terms may be used to refer to the same component. In this specification and claims, differences in nouns are not used to distinguish between components, but rather differences in the functions of the components are used as the basis for distinction. For example, the terms "comprise" and "include" used throughout the specification and claims are open terms and should be interpreted as "including but not limited to." The following description is of a preferred embodiment for carrying out the present invention; however, these descriptions are intended to illustrate the general principles of the specification and do not limit the scope of the present invention. The scope of protection of the present invention is determined by the appended claims.

[0018] Passing-Bablok regression is mainly used to fit the consistency of a linear relationship between a dependent variable and an independent variable. In this regression, both the dependent variable and the independent variable are assumed to be random. The idea of ​​Passing-Bablok regression is to calculate the slope between any two points and finally take the median of all the slopes as the estimated value of the slope. Passing-Bablok regression mainly tests the difference between the intercept and 0 and the difference between the slope and 1 to determine whether the two methods are statistically consistent.

[0019] Spline regression is a piecewise regression and is different from linear regression. While linear regression fits a linear relationship to all data, spline regression divides the data into multiple segments and fits a linear relationship to each segment. Therefore, spline regression is a piecewise polynomial function smoothly connected by nodes. In spline regression, the number of nodes and node values, as well as the form of the fitting curve for each segment (linear, quadratic, cubic, etc.) must be determined in combination with the actual data.

[0020] Nodes in the spline regression process are usually determined primarily based on the unique nodes identified in the field, supplemented by statistical indicators. If there are relatively clear nodes in the field based on the characteristics of the data itself (i.e., unique nodes based on the characteristics of the data), the determination is first based on the unique nodes. However, if there are no clear unique nodes in the field, consideration is given to making a decision based on statistical indicators. Commonly used indicators include AIC (Akaike Information Criterion) and BIC (Bayesian Information Criterion), which are standards for measuring model performance. The lower the AIC or BIC, the better the model fitting effect.

[0021] The present application provides a method for converting hormone data detected by different detection methods, the method comprising: Step 1: obtaining a first detection value of the hormone from a first platform; Step 2: obtaining a second detection value of the hormone from a second platform; Step 3: fitting the first detected value and the second detected value using Passing-Bablok regression; Step 4: determining whether there is a systematic difference between the first detected value and the second detected value based on the fitting result of the Passing-Bablok regression; If there is no systematic difference between the first detected value and the second detected value, converting the first detected value or the second detected value based on a fitting formula of the Passing-Bablok regression; If there is a systematic difference between the first detection value and the second detection value, the first detection value and the second detection value are fitted based on spline regression, and the first detection value or the second detection value is converted based on the fitting formula of the spline regression.

[0022] Specifically, there is no particular order for Step 1 and Step 2.

[0023] The method of the present application can convert and calculate serum hormone detection values ​​obtained by different hormone detection methods, allowing patients to conveniently standardize hormone detection data obtained from different hospitals or laboratories, that is, the results of the same hormone test items from different hospitals or different detection systems can be mutually recognized through specific formula conversion. On the one hand, this data conversion can reduce the cost of sex hormone detection when patients visit different hospitals or laboratories, and on the other hand, it can help promote artificial intelligence software based on data from specific detection platforms and apply it to different detection platforms using the same indicators, thereby contributing to the subsequent development of digital medicine.

[0024] In the present application, determining whether there is a systematic difference between the first detection value and the second detection value based on the fitting result of the Passing-Bablok regression is determining whether there is a systematic difference between the first detection value and the second detection value by calculating a 95% confidence interval of the intercept of the linear regression result.

[0025] A confidence interval is an interval estimate of a population parameter constructed from sample statistics. In statistics, a confidence interval for a probability sample is an interval estimate of a population parameter from a sample. The confidence interval indicates the degree to which the true value of the parameter falls around the measurement result with a certain probability. The confidence interval indicates the degree of reliability of the measurement of the measured parameter, i.e., the "probability" required earlier. This probability is called the confidence level, and the confidence space at a confidence level of 0.95 can also be expressed as a 95% confidence interval.

[0026] Specifically, if the 95% confidence interval of the intercept includes 0, it is determined that there is no systematic difference between the first detection value and the second detection value, Specifically, if the 95% confidence interval of the intercept does not include 0, it is determined that there is a systematic difference between the first detected value and the second detected value.

[0027] In the present application, when fitting the first detected value and the second detected value based on spline regression, the specific nodes and statistical indicators are used to identify the nodes of the spline regression.

[0028] Specifically, the statistical index is the AIC (Akaike Information Criterion) index or the BIC (Bayes Information Criterion) index.

[0029] The Akaike Information Criterion (AIC) is one of the commonly used criteria for comparing the fit of multiple regression models with different numbers of explanatory variables. This criterion states that explanatory variables should be added to the original model only if they can reduce the AIC value. If the added explanatory variables have no explanatory power, they will not be very useful in reducing the residual sum of squares, but they may increase the number of estimated parameters and increase the AIC value.

[0030] Bayes Information Criterion, also known as Bayes Decision Criterion, is a fundamental method in statistical pattern recognition. The Bayes Decision Criterion takes into account both the occurrence probability of various reference groups and the magnitude of the loss caused by misjudgment, and has a strong judgment ability. The Bayes method is more suitable for the following situations: (1) When the number (capacity) of the sample (subsample) is not large enough, and statistical theory of large subsamples is not applicable. (2) The experiment is genetic, and statistics require prior information to exist before the experiment.

[0031] In the present application, the hormone is a sex hormone, and preferably, the sex hormone is selected from hypothalamic-pituitary-gonadal axis hormones, including hypothalamic hormones, pituitary prolactin (PRL), follicle-stimulating hormone (FSH), luteinizing hormone (LH), anti-Mullerian hormone (AMH), inhibin B, estradiol (E2), testosterone (T), dehydroepiandrosterone sulfate (DHEA-S), estriol (E3), and progesterone (P).

[0032] Specifically, the hormone is anti-Müllerian hormone (AMH) or estradiol (E2).

[0033] In the present application, the first platform can be Roche AMH detection platform, Kangrun chemiluminescent AMH detection platform, Beckman AMH detection platform, Kangrun enzyme immunoassay (Anshlab) AMH detection platform, Kangrun estradiol detection platform, and Siemens estradiol detection platform.

[0034] In the present application, the second platform can be Roche AMH detection platform, Kangrun chemiluminescent AMH detection platform, Beckman AMH detection platform, Kangrun enzyme immunoassay (Anshlab) AMH detection platform, Kangrun estradiol detection platform, and Siemens estradiol detection platform.

[0035] Specifically, when the first platform is a Roche AMH detection platform, the second platform can be a Kangrun chemiluminescent AMH detection platform, a Beckman AMH detection platform, a Kangrun enzyme immunoassay (Anshlab) AMH detection platform, a Kangrun estradiol detection platform, and a Siemens estradiol detection platform.

[0036] Specifically, when the first platform is a Kangrun chemiluminescent AMH detection platform, the second platform can be a Roche AMH detection platform, a Beckman AMH detection platform, a Kangrun enzyme immunoassay (Anshlab) AMH detection platform, a Kangrun estradiol detection platform, and a Siemens estradiol detection platform.

[0037] Specifically, when the first platform is a Beckman AMH detection platform, the second platform can be a Roche AMH detection platform, a Kangrun chemiluminescent AMH detection platform, a Kangrun enzyme immunoassay (Anshlab) AMH detection platform, a Kangrun estradiol detection platform, and a Siemens estradiol detection platform.

[0038] Specifically, when the first platform is the Kangrun enzyme immunoassay (Anshlab) AMH detection platform, the second platform can be the Roche AMH detection platform, the Kangrun chemiluminescent AMH detection platform, the Beckman AMH detection platform, the Kangrun estradiol detection platform, and the Siemens estradiol detection platform.

[0039] Specifically, when the first platform is a Kangrun estradiol detection platform, the second platform can be a Roche AMH detection platform, a Kangrun chemiluminescent AMH detection platform, a Beckman AMH detection platform, a Kangrun enzyme immunoassay (Anshlab) AMH detection platform, and a Siemens estradiol detection platform.

[0040] Specifically, when the first platform is a Siemens estradiol detection platform, the second platform can be a Roche AMH detection platform, a Kangrun chemiluminescent AMH detection platform, a Beckman AMH detection platform, a Kangrun enzyme immunoassay (Anshlab) AMH detection platform, a Kangrun estradiol detection platform, and a Siemens estradiol detection platform.

[0041] In this application, the sex hormone is anti-Mullerian hormone (AMH), where the first platform is a Roche AMH detection platform and the second platform is a Kangrun chemiluminescence AMH detection platform, using Passing-Bablok regression to convert the detection results of the Roche AMH detection platform and the Kangrun chemiluminescence AMH detection platform; Specifically, the formula for converting Kangrun chemiluminescent AMH(X) to Roche AMH(Y) is as follows: Roche AMH=a1+b1*Kangrun chemiluminescent AMH; In the formula, a1 is an arbitrary value selected from −0.0035 to 0.0303, and b1 is an arbitrary value selected from 0.85 to 0.8844. Furthermore, a1 may be -0.0035, -0.0015, 0, 0.001, 0.002, 0.003, 0.004, 0.005, 0.006, 0.007, 0.008, 0.009, 0.010, 0.012, 0.014, 0.016, 0.018, 0.020, 0.022, 0.024, 0.026, 0.028, 0.030, or 0.0303; b1 may be 0.85, 0.86, 0.87, 0.88, 0.881, 0.882, 0.883, 0.884, 0.8841, 0.8842, 0.8843, 0.8844.

[0042] Specifically, the formula for converting Roche AMH(X) to Kangrun chemiluminescent AMH(Y) is as follows: Kangrun chemiluminescence AMH = a2 + b2 * Roche AMH; In the formula, a2 is an arbitrary value selected from −0.0356 to 0.00393, and b2 is an arbitrary value selected from 1.1307 to 1.1765.

[0043] Furthermore, a2 may be −0.0356, −0.0366, −0.0376, −0.0386 or −0.0393; b2 may be 1.1307, 1.1407, 1.1507, 1.1607, 1.1707, or 1.1765.

[0044] In the present application, the sex hormone is anti-Mullerian hormone (AMH), wherein the first platform is a Beckman AMH detection platform and the second platform is a Roche AMH detection platform, using spline regression to convert the detection results of the Beckman AMH detection platform and the Roche AMH detection platform; Specifically, the formula for converting Roche AMH(X) to Beckman AMH(Y) is: Beckman AMH=a3+b3*Roche AMH+c3*g1(Roche AMH-1)+d3*g2(Roche AMH-9), where Roche AMH<=1 ng / ml, then g1=0 and g2=0, in which case the formula becomes: Beckman AMH=a3+b3*Roche AMH If Roche AMH > 1 ng / ml and <= 9 ng / ml, then g1 = 1 and g2 = 0, in which case the formula becomes: Beckman AMH=a3+b3*Roche AMH+c3*(Roche AMH-1) If Roche AMH>9ng / ml, then g1=1 and g2=1, in which case the formula becomes: Beckman AMH=a3+b3*Roche AMH+c3*(Roche AMH-1)+d3*(Roche AMH-9) In the formula, a3 is an arbitrary value selected from -0.28809 to 0.30461, b3 is an arbitrary value selected from 0.665236 to 1.430824, c3 is an arbitrary value selected from 0.073606 to 0.900514, and d3 is an arbitrary value selected from -0.70344 to -0.42116, Furthermore, a3 may be −0.28809, −0.18809, 0, 0.18809, 0.28809, or 0.30461. b3 may be 0.665236, 0.765236, 0.865236, 0.965236, 1, or 1.430824. c3 may be 0.073606, 0.083606, 0.093606, 0.103606, 0.203606, 0.303606, 0.403606, 0.503606, 0.603606, 0.703606, 0.803606, or 0.900514. d3 may be -0.70344, -0.60344, -0.50344, or -0.42116.

[0045] Specifically, the formula for converting Beckman AMH(X) to Roche AMH(Y) is: Roche AMH=a4+b4*Beckman AMH+c4*g1(Beckman AMH-0.5)+d4*g2(Beckman AMH-1) where if the Beckman AMH value is <=0.5 ng / ml, then g1=0 and g2=0, in which case the formula becomes: Roche AMH=a4+b4*Beckman AMH If the Beckman AMH value is >0.5 ng / ml and <=1 ng / ml, then g1=1 and g2=0, in which case the formula becomes: Roche AMH=a4+b4*Beckman AMH+c4*(Beckman AMH-0.5) If the Beckman AMH value is >1 ng / ml, then g1 = 1 and g2 = 1, in which case the formula becomes: Roche AMH=a4+b4*Beckman AMH+c4*(Beckman AMH-0.5)+d4*(Beckman AMH-1), In the formula, a4 is an arbitrary value selected from -0.42466 to 0.41822, b4 is an arbitrary value selected from -0.11202 to 2.17363, c4 is an arbitrary value selected from -1.96122 to 1.21734, and d4 is an arbitrary value selected from -0.49419 to 0.66553.

[0046] Furthermore, a4 may be -0.42466, -0.32466, -0.22466, -0.12466, -0.02466, 0, 0.12466, 0.22466, 0.32466, or 0.41822. b4 may be -0.11202, -0.01202, 0, 0.11202, 0.21202, 0.31202, 0.41202, 0.51202, 0.61202, 0.71202, 0.81202, 0.91202, 1.11202, 1.21202, 1.31202, 1.41202, 1.51202, 1.61202, 1.71202, 1.81202, 1.91202, 2.01202, 2.11202, or 2.17363. c4 is -1.96122, -1.86122, -1.76122, -1.66122, -1.56122, -1.46122, -1.36122, -1.26122, -1.16122, -1.06122, -0.96122, -0.86122, -0.76122, -0.66122, -0.56122, -0.4612 It may be 2, -0.36122, -0.26122, -0.16122, -0.06122, 0, 0.16122, 0.26122, 0.36122, 0.46122, 0.56122, 0.66122, 0.76122, 0.86122, 0.96122, 1.06122, 1.16122, or 1.21734. d4 may be -0.49419, -0.39419, -0.29419, -0.19419, -0.09419, 0, 0.09419, 0.19419, 0.29419, 0.39419, 0.49419, 0.59419, or 0.66553.

[0047] In the present application, the sex hormone is anti-Mullerian hormone (AMH), wherein the first platform is a Beckman AMH detection platform and the second platform is a Kangrun chemiluminescent AMH detection platform, using spline regression to convert the detection results of the Beckman AMH detection platform and the Kangrun chemiluminescent AMH detection platform; Specifically, the formula for converting Beckman AMH(X) to Kangrun chemiluminescent AMH(Y) is: Kangrun chemiluminescence AMH=a5+b5*Beckman AMH+c5*g1(Beckman AMH-1)+d5*g2(Beckman AMH-4)+e5*g3(Beckman AMH-13) where, if the Beckman AMH value is <=1 ng / ml, then g1=0, g2=0, and g3=0, and in this case, the formula becomes: Kangrun chemiluminescence AMH = a5 + b5 * Beckman AMH If the Beckman AMH value is >1 ng / ml and <=4 ng / ml, then g1=1, g2=0, and g3=0, and in this case the formula becomes: Kangrun chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) If the Beckman AMH value is >4 ng / ml and <=13 ng / ml, then g1=1, g2=1, and g3=0, and in this case the formula becomes: Kangrun chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) + d5 * (Beckman AMH-4) If the Beckman AMH value is >13 ng / ml, then g1 = 1, g2 = 1, and g3 = 1, and in this case, the formula becomes: Kangrun chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) + d5 * (Beckman AMH-4) + e5 * (Beckman AMH-13) In the formula, a5 is any value selected from -0.24101 to 0.26258, b5 is any value selected from 0.72643 to 1.42037, c5 is any value selected from -0.78107 to 0.04326, d5 is any value selected from 0.29488 to 0.57880, and e5 is any value selected from -0.71455 to -0.47130. Furthermore, a5 may be -0.24101, -0.14101, -0.04101, 0, 0.14101, 0.24101, or 0.26258. b5 may be 0.72643, 0.82643, 0.92643, 1.12643, 1.22643, 1.32643, or 1.42037. c5 may be -0.78107, -0.68107, -0.58107, -0.48107, -0.38107, -0.28107, -0.18107, -0.08107, 0, or 0.04326. d5 may be 0.29488, 0.39488, 0.49488, or 0.57880. e5 may be -0.71455, -0.61455, -0.51455, or -0.47130.

[0048] Specifically, the formula for converting Kangrun chemiluminescent AMH(X) to Beckman AMH(Y) is: Beckman AMH = a6 + b6 * Kangrun Chemiluminescent AMH + c6 * g1 (Kangrun Chemiluminescent AMH-0.5) + d6 * g2 (Kangrun Chemiluminescent AMH-13) In the formula, when the Kangrun chemiluminescence AMH value is less than 0.5 ng / ml, g1=0 and g2=0. In this case, the formula becomes: Beckman AMH = a6 + b6 * Kangrun chemiluminescent AMH When the Kangrun chemiluminescence AMH value is >0.5 and <=13 ng / ml, g1=1 and g2=0, and in this case, the formula becomes: Beckman AMH = a6 + b6 * Kangrun chemiluminescent AMH + c6 * (Kangrun chemiluminescent AMH-0.5) If the Kangrun chemiluminescence AMH value is >13 ng / ml, then g1=1 and g2=1, and in this case, the formula becomes: Beckman AMH = a6 + b6 * Kangrun Chemiluminescent AMH + c6 * (Kangrun Chemiluminescent AMH-0.5) + d6 * (Kangrun Chemiluminescent AMH-13) In the formula, a6 is any value selected from -0.45082 to 0.54656, b6 is any value selected from -0.35329 to 1.82169, c6 is any value selected from -0.63742 to 1.56010, and d6 is any value selected from -0.52283 to -0.22757.

[0049] Furthermore, a6 may be -0.45082, -0.35082, -0.25082, -0.15082, -0.05082, 0, 0.05082, 0.15082, 0.25082, 0.35082, 0.45082, or 0.54656. b6 may be -0.35329, -0.25329, -0.15329, -0.05329, 0, 0.05329, 0.15329, 0.25329, 0.35329, 0.45329, 0.55329, 0.65329, 0.75329, 0.85329, 0.95329, 1.05329, 1.15329, 1.25329, 1.35329, 1.45329, 1.55329, 1.16329, 1.17329, or 1.82169. c6 may be -0.63742, -0.53742, -0.43742, -0.33742, -0.23742, -0.13742, -0.03742, 0, 0.03742, 0.13742, 0.23742, 0.33742, 0.43742, 0.53742, 0.63742, 0.73742, 0.83742, 0.93742, 1.03742, 1.13742, 1.23742, 1.33742, 1.43742, or 1.56010. d6 may be -0.52283, -0.42283, -0.32283, or -0.22757.

[0050] In this application, the sex hormone is anti-Mullerian hormone (AMH), wherein the sex hormone is anti-Mullerian hormone (AMH), the first platform is a Kangrun chemiluminescence AMH detection platform, and the second platform is a Kangrun enzyme immunoassay (Anshlab) AMH detection platform, using spline regression to convert the detection results of the Kangrun chemiluminescence AMH detection platform and the Kangrun enzyme immunoassay (Anshlab) AMH detection platform; Specifically, the formula for converting Kangrun chemiluminescent AMH (X) to Kangrun enzyme immunoassay (Anshlab) AMH (Y) is as follows: Kangrun Enzyme Immunosorbent Assay (Anshlab) AMH = a7 + b7 * Kangrun Chemiluminescent AMH + c7 * g1 * (Kangrun Chemiluminescent AMH-2) + d7 * g2 * (Kangrun Chemiluminescent AMH-4) + e7 * g3 * (Kangrun Chemiluminescent AMH-7) In the formula, a7 is an arbitrary value selected from -0.31000 to 0.20149, b7 is an arbitrary value selected from 0.73863 to 1.10064, c7 is an arbitrary value selected from -0.08941 to 0.51000, d7 is an arbitrary value selected from 0.08121 to 0.54582, and e7 is an arbitrary value selected from -0.70493 to -0.42738. Furthermore, a7 may be -0.31000, -0.21000, -0.11000, -0.01000, 0, 0.01000, 0.11000, or 0.20149. b7 may be 0.73863, 0.83863, 0.93863, 1.03863, or 1.10064. c7 may be -0.08941, 0, 0.08941, 0.18941, 0.28941, 0.38941, 0.48941, or 0.51000. d7 may be 0.08121, 0.18121, 0.28121, 0.38121, 0.48121, or 0.54582. e7 may be -0.70493, -0.60493, -0.50493, or -0.42738.

[0051] Furthermore, if Kangrun chemiluminescent AMH <= 2 ng / ml, then g1 = 0, in which case the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescence AMH; When Kangrun chemiluminescent AMH is >2 ng / ml and <=4 ng / ml, g1=1 and g2=0, in which case the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 (Kangrun chemiluminescent AMH-2), When Kangrun chemiluminescent AMH is >4 ng / ml and <=7 ng / ml, then g1=1 and g2=1, and in this case, the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 (Kangrun chemiluminescent AMH-2) + d7 * g2 (Kangrun chemiluminescent AMH-4), If Kangrun chemiluminescent AMH > 7 ng / ml, then g1 = 1, g2 = 1, and g3 = 1, and in this case, the formula becomes Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 (Kangrun chemiluminescent AMH-2) + d7 * g2 (Kangrun chemiluminescent AMH-4) + e7 * g3 (Kangrun chemiluminescent AMH-7).

[0052] In this application, when the sex hormone is estradiol E2, where the first platform is Kangrun estradiol detection platform and the second platform is Siemens estradiol detection platform, convert the detection results of Kangrun estradiol and Siemens estradiol using spline regression; Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value + c8 * g1 (Kangrun E2 detection value - 660) + d8 * g2 (Kangrun E2 detection value - 2030) During the ceremony, When the Kangrun E2 detection value is ≦660 pmol / L, g1=0 and g2=0. In this case, the above formula becomes: Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value When the Kangrun E2 detection value is >660 pmol / L and <=2030 pmol / L, g1=0 and g2=0. In this case, the above formula becomes: Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value + c8 * (Kangrun E2 detection value - 660) If the Kangrun E2 detection value is >2030 pmol / L, then g1 = 0 and g2 = 1, and in this case, the above formula becomes: Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value + c8 * (Kangrun E2 detection value - 660) + d8 * (Kangrun E2 detection value - 2030) In the formula, a7 is any value selected from -93.069 to -6.91207, b7 is any value selected from 1.310892 to 1.569808, c7 is any value selected from -0.8957 to -0.52322, and d7 is any value selected from -0.08505 to 0.085318.

[0053] Furthermore, a7 may be −93.069, −83.069, −73.069, −63.069, −53.069, −43.069, −33.069, −23.069, −13.069, or −6.91207. b7 may be 1.310892, 1.410892, 1.510892, or 1.569808. c7 may be -0.8957, -0.7957, -0.68957, -0.5957, or -0.52322. d7 may be -0.08505, -0.07505, -0.06505, -0.05505, -0.04505, -0.03505, -0.02505, -0.01505, 0, 0.01505, 0.02505, 0.03505, 0.04505, 0.05505, 0.06505, 0.07505, or 0.085318.

[0054] The present application provides a system for converting hormone data detected by different detection methods, the system comprising: a sub-module that obtains a first detection value of the hormone from a first platform; a sub-module that obtains a second detection value of the hormone from a second platform; a sub-module for fitting the first detected value and the second detected value using Passing-Bablok regression; a sub-module for determining whether there is a systematic difference between the first detected value and the second detected value based on the fitting result of the Passing-Bablok regression; a sub-module for determining whether there is a systematic difference between the first detected value and the second detected value based on the fitting result of the Passing-Bablok regression; if there is no systematic difference between the first detected value and the second detected value, transforming the first detected value or the second detected value based on a fitting formula of Passing-Bablok regression; If there is a systematic difference between the first and second detection values, a step of fitting the first and second detection values ​​based on spline regression and converting the first or second detection value based on the fitting formula of the spline regression is performed.

[0055] In the present application, determining whether there is a systematic difference between the first detection value and the second detection value based on the fitting result of the Passing-Bablok regression is determining whether there is a systematic difference between the first detection value and the second detection value by calculating the 95% confidence interval of the intercept of the linear regression result.

[0056] In the present application, if the 95% confidence interval of the intercept includes 0, it is determined that there is no systematic difference between the first detection value and the second detection value; If the 95% confidence interval of the intercept does not include 0, it is determined that there is a systematic difference between the first and second detected values.

[0057] In the present application, when fitting the first detected value and the second detected value based on spline regression, the specific nodes and statistical indicators are used to identify the nodes of the spline regression.

[0058] In the present application, said statistical index is the AIC (Akaike Information Criterion) index or the BIC (Bayes Information Criterion) index.

[0059] In the present application, the hormone is a sex hormone, and the sex hormone is selected from hypothalamic-pituitary-gonadal axis hormones including hypothalamic hormones, pituitary prolactin (PRL), follicle-stimulating hormone (FSH), luteinizing hormone (LH), anti-Müllerian hormone (AMH), inhibin B, estradiol (E2), testosterone (T), dehydroepiandrosterone sulfate (DHEA-S), estriol (E3), progesterone (P), preferably anti-Müllerian hormone (AMH) or estradiol (E2).

[0060] In this application, the sex hormone is anti-Mullerian hormone (AMH), where the first platform is a Roche AMH detection platform and the second platform is a Kangrun chemiluminescence AMH detection platform, using Passing-Bablok regression to convert the detection results of the Roche AMH detection platform and the Kangrun chemiluminescence AMH detection platform; Specifically, the formula for converting Kangrun chemiluminescent AMH(X) to Roche AMH(Y) is as follows: Roche AMH=a1+b1*Kangrun chemiluminescent AMH; In the formula, a1 is an arbitrary value selected from −0.0035 to 0.0303, and b1 is an arbitrary value selected from 0.85 to 0.8844. Furthermore, a1 may be -0.0035, -0.0015, 0, 0.001, 0.002, 0.003, 0.004, 0.005, 0.006, 0.007, 0.008, 0.009, 0.010, 0.012, 0.014, 0.016, 0.018, 0.020, 0.022, 0.024, 0.026, 0.028, 0.030, or 0.0303; b1 may be 0.85, 0.86, 0.87, 0.88, 0.881, 0.882, 0.883, 0.884, 0.8841, 0.8842, 0.8843, 0.8844.

[0061] Specifically, the formula for converting Roche AMH(X) to Kangrun chemiluminescent AMH(Y) is as follows: Kangrun chemiluminescence AMH = a2 + b2 * Roche AMH; In the formula, a2 is an arbitrary value selected from −0.0356 to 0.00393, and b2 is an arbitrary value selected from 1.1307 to 1.1765.

[0062] Furthermore, a2 may be −0.0356, −0.0366, −0.0376, −0.0386 or −0.0393; b2 may be 1.1307, 1.1407, 1.1507, 1.1607, 1.1707, or 1.1765.

[0063] In the present application, the sex hormone is anti-Mullerian hormone (AMH), wherein the first platform is a Beckman AMH detection platform and the second platform is a Roche AMH detection platform, using spline regression to convert the detection results of the Beckman AMH detection platform and the Roche AMH detection platform; Specifically, the formula for converting Roche AMH(X) to Beckman AMH(Y) is: Beckman AMH=a3+b3*Roche AMH+c3*g1(Roche AMH-1)+d3*g2(Roche AMH-9), where Roche AMH<=1 ng / ml, then g1=0 and g2=0, in which case the formula becomes: Beckman AMH=a3+b3*Roche AMH If Roche AMH > 1 ng / ml and <= 9 ng / ml, then g1 = 1 and g2 = 0, in which case the formula becomes: Beckman AMH=a3+b3*Roche AMH+c3*(Roche AMH-1) If Roche AMH>9ng / ml, then g1=1 and g2=1, in which case the formula becomes: Beckman AMH=a3+b3*Roche AMH+c3*(Roche AMH-1)+d3*(Roche AMH-9) In the formula, a3 is an arbitrary value selected from -0.28809 to 0.30461, b3 is an arbitrary value selected from 0.665236 to 1.430824, c3 is an arbitrary value selected from 0.073606 to 0.900514, and d3 is an arbitrary value selected from -0.70344 to -0.42116, Furthermore, a3 may be −0.28809, −0.18809, 0, 0.18809, 0.28809, or 0.30461. b3 may be 0.665236, 0.765236, 0.865236, 0.965236, 1, or 1.430824. c3 may be 0.073606, 0.083606, 0.093606, 0.103606, 0.203606, 0.303606, 0.403606, 0.503606, 0.603606, 0.703606, 0.803606, or 0.900514. d3 may be -0.70344, -0.60344, -0.50344, or -0.42116.

[0064] Specifically, the formula for converting Beckman AMH(X) to Roche AMH(Y) is: Roche AMH=a4+b4*Beckman AMH+c4*g1(Beckman AMH-0.5)+d4*g2(Beckman AMH-1) where if the Beckman AMH value is <=0.5 ng / ml, then g1=0 and g2=0, in which case the formula becomes: Roche AMH=a4+b4*Beckman AMH If the Beckman AMH value is >0.5 ng / ml and <=1 ng / ml, then g1=1 and g2=0, in which case the formula becomes: Roche AMH=a4+b4*Beckman AMH+c4*(Beckman AMH-0.5) If the Beckman AMH value is >1 ng / ml, then g1 = 1 and g2 = 1, in which case the formula becomes: Roche AMH=a4+b4*Beckman AMH+c4*(Beckman AMH-0.5)+d4*(Beckman AMH-1), In the formula, a4 is an arbitrary value selected from -0.42466 to 0.41822, b4 is an arbitrary value selected from -0.11202 to 2.17363, c4 is an arbitrary value selected from -1.96122 to 1.21734, and d4 is an arbitrary value selected from -0.49419 to 0.66553.

[0065] Furthermore, a4 may be -0.42466, -0.32466, -0.22466, -0.12466, -0.02466, 0, 0.12466, 0.22466, 0.32466, or 0.41822. b4 may be -0.11202, -0.01202, 0, 0.11202, 0.21202, 0.31202, 0.41202, 0.51202, 0.61202, 0.71202, 0.81202, 0.91202, 1.11202, 1.21202, 1.31202, 1.41202, 1.51202, 1.61202, 1.71202, 1.81202, 1.91202, 2.01202, 2.11202, or 2.17363. c4 is -1.96122, -1.86122, -1.76122, -1.66122, -1.56122, -1.46122, -1.36122, -1.26122, -1.16122, -1.06122, -0.96122, -0.86122, -0.76122, -0.66122, -0.56122, -0.4612 It may be 2, -0.36122, -0.26122, -0.16122, -0.06122, 0, 0.16122, 0.26122, 0.36122, 0.46122, 0.56122, 0.66122, 0.76122, 0.86122, 0.96122, 1.06122, 1.16122, or 1.21734. d4 may be -0.49419, -0.39419, -0.29419, -0.19419, -0.09419, 0, 0.09419, 0.19419, 0.29419, 0.39419, 0.49419, 0.59419, or 0.66553.

[0066] In the present application, the sex hormone is anti-Mullerian hormone (AMH), wherein the first platform is a Beckman AMH detection platform and the second platform is a Kangrun chemiluminescent AMH detection platform, using spline regression to convert the detection results of the Beckman AMH detection platform and the Kangrun chemiluminescent AMH detection platform; Specifically, the formula for converting Beckman AMH(X) to Kangrun chemiluminescent AMH(Y) is: Kangrun chemiluminescence AMH=a5+b5*Beckman AMH+c5*g1(Beckman AMH-1)+d5*g2(Beckman AMH-4)+e5*g3(Beckman AMH-13) where, if the Beckman AMH value is <=1 ng / ml, then g1=0, g2=0, and g3=0, and in this case, the formula becomes: Kangrun chemiluminescence AMH = a5 + b5 * Beckman AMH If the Beckman AMH value is >1 ng / ml and <=4 ng / ml, then g1=1, g2=0, and g3=0, and in this case the formula becomes: Kangrun chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) If the Beckman AMH value is >4 ng / ml and <=13 ng / ml, then g1=1, g2=1, and g3=0, and in this case the formula becomes: Kangrun chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) + d5 * (Beckman AMH-4) If the Beckman AMH value is >13 ng / ml, then g1 = 1, g2 = 1, and g3 = 1, and in this case, the formula becomes: Kangrun chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) + d5 * (Beckman AMH-4) + e5 * (Beckman AMH-13) In the formula, a5 is any value selected from -0.24101 to 0.26258, b5 is any value selected from 0.72643 to 1.42037, c5 is any value selected from -0.78107 to 0.04326, d5 is any value selected from 0.29488 to 0.57880, and e5 is any value selected from -0.71455 to -0.47130. Furthermore, a5 may be -0.24101, -0.14101, -0.04101, 0, 0.14101, 0.24101, or 0.26258. b5 may be 0.72643, 0.82643, 0.92643, 1.12643, 1.22643, 1.32643, or 1.42037. c5 may be -0.78107, -0.68107, -0.58107, -0.48107, -0.38107, -0.28107, -0.18107, -0.08107, 0, or 0.04326. d5 may be 0.29488, 0.39488, 0.49488, or 0.57880. e5 may be -0.71455, -0.61455, -0.51455, or -0.47130.

[0067] Specifically, the formula for converting Kangrun chemiluminescent AMH(X) to Beckman AMH(Y) is: Beckman AMH = a6 + b6 * Kangrun Chemiluminescent AMH + c6 * g1 (Kangrun Chemiluminescent AMH-0.5) + d6 * g2 (Kangrun Chemiluminescent AMH-13) In the formula, when the Kangrun chemiluminescence AMH value is less than 0.5 ng / ml, g1=0 and g2=0. In this case, the formula becomes: Beckman AMH = a6 + b6 * Kangrun chemiluminescent AMH When the Kangrun chemiluminescence AMH value is >0.5 and <=13 ng / ml, g1=1 and g2=0, and in this case, the formula becomes: Beckman AMH = a6 + b6 * Kangrun chemiluminescent AMH + c6 * (Kangrun chemiluminescent AMH-0.5) If the Kangrun chemiluminescence AMH value is >13 ng / ml, then g1=1 and g2=1, and in this case, the formula becomes: Beckman AMH = a6 + b6 * Kangrun Chemiluminescent AMH + c6 * (Kangrun Chemiluminescent AMH-0.5) + d6 * (Kangrun Chemiluminescent AMH-13) In the formula, a6 is any value selected from -0.45082 to 0.54656, b6 is any value selected from -0.35329 to 1.82169, c6 is any value selected from -0.63742 to 1.56010, and d6 is any value selected from -0.52283 to -0.22757.

[0068] Furthermore, a6 may be -0.45082, -0.35082, -0.25082, -0.15082, -0.05082, 0, 0.05082, 0.15082, 0.25082, 0.35082, 0.45082, or 0.54656. b6 may be -0.35329, -0.25329, -0.15329, -0.05329, 0, 0.05329, 0.15329, 0.25329, 0.35329, 0.45329, 0.55329, 0.65329, 0.75329, 0.85329, 0.95329, 1.05329, 1.15329, 1.25329, 1.35329, 1.45329, 1.55329, 1.16329, 1.17329, or 1.82169. c6 may be -0.63742, -0.53742, -0.43742, -0.33742, -0.23742, -0.13742, -0.03742, 0, 0.03742, 0.13742, 0.23742, 0.33742, 0.43742, 0.53742, 0.63742, 0.73742, 0.83742, 0.93742, 1.03742, 1.13742, 1.23742, 1.33742, 1.43742, or 1.56010. d6 may be -0.52283, -0.42283, -0.32283, or -0.22757.

[0069] In this application, when the sex hormone is anti-Mullerian hormone (AMH), and the first platform is a Kangrun chemiluminescence AMH detection platform and the second platform is a Kangrun enzyme immunoassay (Anshlab) AMH detection platform, using spline regression to convert the detection results of the Kangrun chemiluminescence AMH detection platform and the Kangrun enzyme immunoassay (Anshlab) AMH detection platform; Specifically, the formula for converting Kangrun chemiluminescent AMH (X) to Kangrun enzyme immunoassay (Anshlab) AMH (Y) is as follows: Kangrun Enzyme Immunosorbent Assay (Anshlab) AMH = a7 + b7 * Kangrun Chemiluminescent AMH + c7 * g1 * (Kangrun Chemiluminescent AMH-2) + d7 * g2 * (Kangrun Chemiluminescent AMH-4) + e7 * g3 * (Kangrun Chemiluminescent AMH-7) In the formula, a7 is an arbitrary value selected from -0.31000 to 0.20149, b7 is an arbitrary value selected from 0.73863 to 1.10064, c7 is an arbitrary value selected from -0.08941 to 0.51000, d7 is an arbitrary value selected from 0.08121 to 0.54582, and e7 is an arbitrary value selected from -0.70493 to -0.42738. Furthermore, a7 may be -0.31000, -0.21000, -0.11000, -0.01000, 0, 0.01000, 0.11000, or 0.20149. b7 may be 0.73863, 0.83863, 0.93863, 1.03863, or 1.10064. c7 may be -0.08941, 0, 0.08941, 0.18941, 0.28941, 0.38941, 0.48941, or 0.51000. d7 may be 0.08121, 0.18121, 0.28121, 0.38121, 0.48121, or 0.54582. e7 may be -0.70493, -0.60493, -0.50493, or -0.42738.

[0070] Furthermore, if Kangrun chemiluminescent AMH <= 2 ng / ml, then g1 = 0, in which case the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescence AMH; When Kangrun chemiluminescent AMH is >2 ng / ml and <=4 ng / ml, g1=1 and g2=0, in which case the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 (Kangrun chemiluminescent AMH-2), When Kangrun chemiluminescent AMH is >4 ng / ml and <=7 ng / ml, then g1=1 and g2=1, and in this case, the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 (Kangrun chemiluminescent AMH-2) + d7 * g2 (Kangrun chemiluminescent AMH-4), If Kangrun chemiluminescent AMH > 7 ng / ml, then g1 = 1, g2 = 1, and g3 = 1, and in this case, the formula becomes Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 (Kangrun chemiluminescent AMH-2) + d7 * g2 (Kangrun chemiluminescent AMH-4) + e7 * g3 (Kangrun chemiluminescent AMH-7).

[0071] In this application, when the sex hormone is estradiol E2, where the first platform is Kangrun estradiol detection platform and the second platform is Siemens estradiol detection platform, convert the detection results of Kangrun estradiol and Siemens estradiol using spline regression; Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value + c8 * g1 (Kangrun E2 detection value - 660) + d8 * g2 (Kangrun E2 detection value - 2030) During the ceremony, When the Kangrun E2 detection value is ≦660 pmol / L, g1=0 and g2=0. In this case, the above formula becomes: Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value When the Kangrun E2 detection value is >660 pmol / L and <=2030 pmol / L, g1=0 and g2=0. In this case, the above formula becomes: Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value + c8 * (Kangrun E2 detection value - 660) If the Kangrun E2 detection value is >2030 pmol / L, then g1 = 0 and g2 = 1, and in this case, the above formula becomes: Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value + c8 * (Kangrun E2 detection value - 660) + d8 * (Kangrun E2 detection value - 2030) In the formula, a7 is any value selected from -93.069 to -6.91207, b7 is any value selected from 1.310892 to 1.569808, c7 is any value selected from -0.8957 to -0.52322, and d7 is any value selected from -0.08505 to 0.085318.

[0072] Furthermore, a7 may be −93.069, −83.069, −73.069, −63.069, −53.069, −43.069, −33.069, −23.069, −13.069, or −6.91207. b7 may be 1.310892, 1.410892, 1.510892, or 1.569808. c7 may be -0.8957, -0.7957, -0.68957, -0.5957, or -0.52322. d7 may be -0.08505, -0.07505, -0.06505, -0.05505, -0.04505, -0.03505, -0.02505, -0.01505, 0, 0.01505, 0.02505, 0.03505, 0.04505, 0.05505, 0.06505, 0.07505, or 0.085318. [Example]

[0073] Example 1 Sample selection was based on the historical AMH data distribution of the Reproductive Center of Peking University Third Hospital, as shown in Table 1. The AMH concentrations of the collected samples were routinely detected using the Kangrun detection method. The inventors randomly selected 300 serum AMH samples from the Reproductive Center of Peking University Third Hospital between November 2021 and February 2022. These samples were collected from female patients undergoing standard in vitro fertilization (IVF) procedures. The samples were collected from the hospital's IVF center and frozen at -80°C. These patients signed written consent to donate their remaining serum for research purposes after their initial blood tests. Table 1 summarizes all AMH detection results using the Kangrun method, expressed in nanograms per milliliter (ng / ml).

[0074] [Table 1]

[0075] Example 2 For each sample obtained in Example 1, two tubes of frozen serum were thawed and then analyzed for AMH using the Roche method. The other tube was analyzed using the Kangrun chemiluminescence method and the Beckman method on the same day after thawing. As a result, AMH results were obtained using three methods (referred to as "Roche AMH," "Beckman AMH," and "Kangrun chemiluminescence AMH," respectively).

[0076] If the detection result of the serum sample collected in Example 1 exceeds the upper limit of the measurement range of each method, the sample is diluted using the reagents provided by the manufacturer of the method and detected again.

[0077] Roche detection was performed on a Roche Cobas e 602 instrument using the Elecsys (Roche) AMH kit, Beckman detection was performed on a Beckman DxI 800 instrument using the Beckman Access AMH kit, and Kangrun detection was performed on a Kangrun Kaeser 6600 instrument using the Kangrun chemiluminescent AMH kit.

[0078] Quality control of the AMH detection results by the three methods was performed using quality control materials (control samples) provided with each AMH kit. The difference between the measured value of the control sample and the predetermined target value was expressed as deviation. The deviation of ±12% and the coefficient of variation (CV) of 8% or less were within the controllable range, and the detection results were within the acceptable range. Table 2 below shows the precision and accuracy results of each AMH detection. For each detection method, the analytical CV value was 5% or less, and the deviation was ±7%, indicating that the three methods established in the examples of this application are stable and the detection results meet the requirements.

[0079] [Table 2]

[0080] Example 3 Considering the widespread use of the three different AMH detection kits mentioned above, it is necessary to find a way to accurately standardize the AMH data detected by the three methods in order to integrate these data.

[0081] Generally speaking, if the AMH detection data from the Beckman method, the Kangrun chemiluminescence method, and the Roche method satisfy an overall relationship, Passing-Bablok regression can be used to convert between any two of the three data sets. Passing-Bablok regression uses a nonparametric method to fit the parameters a and b of the linear equation y = a + bx. If the 95% confidence interval (CI) for the intercept a does not include 0 or the 95% CI for the slope b does not include 1, this indicates a systematic or proportional difference between the two AMH detection results.

[0082] If the detection results of the two platform methods do not satisfy the overall relationship, you can consider using spline regression to find a transformation between the detection data of the two platforms. Spline regression is a piecewise polynomial function with smooth connections at the nodes. It can be a linear relationship (a straight line connecting at the nodes), a quadratic relationship, or a cubic relationship. In spline regression, based on the relationship between the independent and dependent variables, linear spline regression can be used to attempt to construct a linear regression with smooth connections at the nodes.

[0083] In Example 3, an attempt was also made to plot a Bland-Altman plot to examine the systematic deviation and variance differences in different numerical ranges. In this example, the fitting effect of the data was evaluated using the coefficient of determination (R 2 ), R after calibration 2 The accuracy was evaluated by the root mean square error (RMSE), Aker information criterion (AIC), and corrected AIC (AICc). 2 and after calibration R 2The higher the , the better the performance of the fitting model. The lower the RMSE, AIC, and AICc, the better the fitting effect. All statistical analyses in this example were performed using JMP PRO v16.0 (Cary, NC, USA).

[0084] (1) Step 1: Passing-Bablok regression between the three AMH detection results Assuming that Roche AMH and Kangrun chemiluminescent AMH satisfy an overall relationship, a linear relationship between the two measurements was constructed using the Passing-Bablok regression method. Figure 1A shows the fitting results for Roche AMH and Kangrun chemiluminescent AMH. In Figure 1A, the dashed line reflects the theoretical fitting results between the two AMH measurements, and the solid line is the result of the Passing-Bablok regression. As can be seen in Figure 1A, the solid line deviates from the dashed line, and this difference must be statistically tested.

[0085] Furthermore, a Bland-Altman plot was performed to examine the agreement between the results of the Roche AMH and Kangrun chemiluminescent AMH assays, and the results are shown in Figure 1B. The horizontal axis represents the mean values ​​of Kangrun chemiluminescent AMH and Roche AMH, and the vertical axis represents the difference between Kangrun chemiluminescent AMH and Roche AMH. The solid gray line in Figure 1B is the reference line, i.e., a value of 0 (representing a mean difference of 0 between the two AMH assay results), and the central solid and dashed lines represent the mean value obtained by subtracting Roche AMH from Kangrun chemiluminescent AMH and its 95% confidence interval. The outer gray border (i.e., the gray area in the figure) represents the 95% distribution range of the difference (mean ± 1.96 × standard deviation), also known as the limits of agreement. Theoretically, the closer the central solid line is to the reference line, the greater the agreement between the two measurements. If 95% of the points are within the dashed gray border and normally distributed around the central solid line, it can be concluded that the two AMH measurements are in agreement. In this example, the number of observations beyond the gray line is 8.5%, and the data distribution is obviously non-normal, especially in the high-value range. Therefore, based on the analysis results of the above example, it is considered that the two AMH measurement results are inconsistent.

[0086] Furthermore, Figure 1C shows a mountain-shaped graph comparing the Kangrun chemiluminescent AMH and Roche AMH results. The vertical axis of the mountain-shaped graph represents the Kangrun minus Roche detection value, and the vertical axis represents the percentile of the cumulative distribution. When the cumulative distribution probability is less than 50%, it is the cumulative distribution probability; when it is greater than 50%, it is 1-cumulative distribution probability. If the two AMH detection results are consistent, they should be symmetrically distributed around 0. As can be seen in Figure 1C, the data for "Kangrun chemiluminescent AMH-Roche AMH" show a right-skewed tail, and the difference between "Kangrun chemiluminescent AMH-Roche AMH" is mostly greater than 0. The right tail is very long, indicating that some data points for "Kangrun chemiluminescent AMH-Roche AMH" are very high. On the other hand, when the cumulative distribution is less than 50%, the difference between the two AMH detection methods is small.

[0087] The intercept for converting AMH results from the Roche method to those from the Kangrun chemiluminescence method was -0.0124, and its 95% confidence interval (CI) included 0, indicating no systematic difference between Kangrun AMH and Roche AMH. The slope was 1.1517, and its 95% CI did not include 1, indicating a possible proportional difference between the two AMH results. Furthermore, using Passing-Bablok regression, the inventors performed additional pairwise transformations between the three AMH measurements. The intercepts and slopes of the pairwise transformation fitting results are summarized in Table 3 below.

[0088] The inventors further standardized each two sets of data according to the fitting formula shown in Table 3. Table 4 shows the selected 30 sets of data, and all transformed or standardized data were calculated using Passing-Bablok regression (results not described in detail).

[0089] [Table 3] where Cl represents the confidence interval.

[0090] As can be seen from the above analysis, when Kangrun chemiluminescent AMH is converted to Roche AMH, and when Roche AMH is converted to Kangrun chemiluminescent AMH, the fitting results using Passing-Bablok regression show that the intercept contains 0. Therefore, it can be confirmed that the conversion formulas for converting Kangrun chemiluminescent AMH to Roche AMH and Roche AMH to Kangrun chemiluminescent AMH are as follows: The formula for converting Kangrun chemiluminescent AMH(X) to Roche AMH(Y) is: Roche AMH=a1+b1*Kangrun chemiluminescent AMH and In the formula, a1 is an arbitrary value selected from −0.0035 to 0.0303, and b1 is an arbitrary value selected from 0.85 to 0.8844. The formula for converting Roche AMH(X) to Kangrun chemiluminescent AMH(Y) is: Kangrun chemiluminescent AMH=a2+b2*Roche AMH and In the formula, a2 is an arbitrary value selected from −0.0356 to 0.00393, and b2 is an arbitrary value selected from 1.1307 to 1.1765.

[0091] (2) Step 2: Spline regression between the three AMH detection results The Passing-Bablok regression in Example 3(1) assumes that the correlation between the two AMH detections satisfies an overall relationship. However, as shown in Table 4 below and the remaining data transformed or standardized using Passing-Bablok regression, in the four transformations, namely, the transformation from Kangrun chemiluminescent AMH to Roche AMH and the transformation from Roche AMH to anything other than Kangrun chemiluminescent AMH, the intercepts of the 95% CI do not include 0, and the fitting effect at low values ​​is clearly poor. This indicates that there is no overall relationship between either of the two. Therefore, in Example 3(2), further transformations were performed using spline regression.

[0092] [Table 4] JPEG2026505571000005.jpg61166

[0093] Taking the conversion of Roche AMH to Beckman AMH as an example, the AMH value measured by Roche was used as the independent variable x, and the AMH value measured by Beckman was used as the dependent variable y. According to the relationship between the independent and dependent variables in the data of the example, a linear spline regression was further adopted, i.e., a linear regression with smooth connections at the nodes was constructed. In Example 3 (2), the selection of the nodes was mainly based on a comprehensive consideration of the specific nodes of clinically meaningful data, the relationship in the scatter plot, and the magnitude of the BIC index. Based on this, the inventors set two nodes of the spline regression, namely, 1 ng / ml and 9 ng / ml, based on numerous studies.

[0094] [Table 5]

[0095] According to the results in Table 5, the correspondence between Beckman AMH and Roche AMH is established as follows: Beckman AMH=a3+b3*Roche AMH+c3*g1(Roche AMH-1)+d3*g2(Roche AMH-9), In the formula, when Roche AMH<=1ng / ml, g1=0 and g2=0. In this case, the above formula becomes: Beckman AMH=a3+b3*Roche AMH If Roche AMH > 1ng / ml and <= 9ng / ml, then g1 = 1 and g2 = 0. In this case, the above formula becomes: Beckman AMH=a3+b3*Roche AMH+c3*(Roche AMH-1) If Roche AMH > 9ng / ml, g1 = 1 and g2 = 1. In this case, the above formula becomes: Beckman AMH=a3+b3*Roche AMH+c3*(Roche AMH-1)+d3*(Roche AMH-9) In the formula, a3 is any value selected from -0.28809 to 0.30461, b3 is any value selected from 0.665236 to 1.430824, c3 is any value selected from 0.073606 to 0.900514, and d3 is any value selected from -0.70344 to -0.42116.

[0096] Table 6 shows a comparison of the fitting effects of spline regression and Passing-Bablok regression. The RMSE, AIC, and AICc of spline regression are lower than those of Passing-Bablok regression, and R 2 and after calibration R 2 is higher than that of the Passing-Bablok regression. Table 7 shows the spline regression estimates for converting AMH results from the Roche method to the Beckman method.

[0097] [Table 6]

[0098] [Table 7]

[0099] Furthermore, we explain how to convert Beckman AMH(x) to Roche AMH(y) based on the regression results.

[0100] [Table 8]

[0101] According to the results in Table 8, the correspondence between Roche AMH(y) and Beckman AMH(x) is established as follows: Roche AMH=a4+b4*Beckman AMH+c4*g1(Beckman AMH-0.5)+d4*g2(Beckman AMH-1) where, if the Beckman AMH value is <=0.5ng / ml, then g1=0 and g2=0, and in this case, the above formula becomes: Roche AMH=a4+b4*Beckman AMH If the Beckman AMH value is >0.5ng / ml and <=1ng / ml, then g1=1 and g2=0, and in this case the above formula becomes: Roche AMH=a4+b4*Beckman AMH+c4*(Beckman AMH-0.5) If the Beckman AMH value is >1ng / ml, then g1=1 and g2=1, and in this case, the above formula becomes: Roche AMH=a4+b4*Beckman AMH+c4*(Beckman AMH-0.5)+d4*(Beckman AMH-1), In the formula, a4 is any value selected from -0.42466 to 0.41822, b4 is any value selected from -0.11202 to 2.17363, c4 is any value selected from -1.96122 to 1.21734, and d4 is any value selected from -0.49419 to 0.66553.

[0102] Taking Beckman AMH vs. Roche AMH as an example, the AMH value measured by Beckman was used as the independent variable x, and the AMH value measured by Roche was used as the dependent variable y. According to the relationship between the independent and dependent variables in the data of the example, a linear spline regression was further adopted, i.e., a linear regression with smooth connections at the nodes was constructed. In Example 3 (2), the node selection was based on the principle that "the smaller the change, the better the equation." Based on this, the inventor set two nodes of the spline regression, namely, 0.5 ng / ml and 1 ng / ml, based on numerous studies.

[0103] Furthermore, we explain how to convert Beckman AMH(x) to Kangrun AMH(y) based on the regression results.

[0104] [Table 9]

[0105] According to the results in Table 9, the correspondence relationship between Beckman AMH(x) and Kangrun chemiluminescence AMH(y) is established as follows: Kangrun chemiluminescence AMH=a5+b5*Beckman AMH+c5*g1(Beckman AMH-1)+d5*g2(Beckman AMH-4)+e5*g3(Beckman AMH-13) In the formula, if the Beckman AMH value is <= 1 ng / ml, then g1 = 0, g2 = 0, and g3 = 0. In this case, the above formula becomes: Kangrun chemiluminescence AMH = a5 + b5 * Beckman AMH If the Beckman AMH value is >1ng / ml and <=4ng / ml, then g1=1, g2=0, and g3=0. In this case, the above formula becomes: Kangrun chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) If the Beckman AMH value is >4ng / ml and <=13ng / ml, then g1=1, g2=1, and g3=0. In this case, the above formula becomes: Kangrun chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) + d5 * (Beckman AMH-4) If the Beckman AMH value is >13ng / ml, then g1=1, g2=1, and g3=1. In this case, the above formula becomes: Kangrun chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) + d5 * (Beckman AMH-4) + e5 * (Beckman AMH-13) In the formula, a5 is any value selected from -0.24101 to 0.26258, b5 is any value selected from 0.72643 to 1.42037, c5 is any value selected from 0.78107 to 0.04326, d5 is any value selected from 0.29488 to 0.57880, and e5 is any value selected from -0.71455 to -0.47130.

[0106] Taking Beckman AMH vs. Kangrun chemiluminescence AMH as an example, the AMH value measured by Beckman was used as the independent variable x, and the AMH value measured by Kangrun chemiluminescence was used as the dependent variable y. According to the relationship between the independent and dependent variables in the data of the example, a linear spline regression was further adopted, i.e., a linear regression with smooth connections at the nodes was constructed. In Example 3 (2), the node selection was based on the principle that "the smaller the change, the better the equation." Based on this, the inventors set three nodes of the spline regression, namely, 1 ng / ml, 4 ng / ml, and 13 ng / ml, based on numerous studies.

[0107] Furthermore, we explain how to convert Kangrun chemiluminescence AMH(x) to Beckman AMH(y) based on the regression results.

[0108] [Table 10]

[0109] According to the results in Table 10, the correspondence between Beckman AMH and Kangrun chemiluminescent AMH is established as follows: Beckman AMH = a6 + b6 * Kangrun Chemiluminescent AMH + c6 * g1 (Kangrun Chemiluminescent AMH-0.5) + d6 * g2 (Kangrun Chemiluminescent AMH-13) In the formula, when the Kangrun chemiluminescence AMH value is less than 0.5, g1=0 and g2=0. In this case, the above formula becomes as follows: Beckman AMH = a6 + b6 * Kangrun chemiluminescent AMH If the Kangrun chemiluminescence AMH value is >0.5 and <=13, then g1=1 and g2=0. In this case, the above formula becomes: Beckman AMH = a6 + b6 * Kangrun chemiluminescent AMH + c6 * (Kangrun chemiluminescent AMH-0.5) If the Kangrun chemiluminescence AMH value is >13, then g1 = 1 and g2 = 1. In this case, the above formula becomes: Beckman AMH = a6 + b6 * Kangrun Chemiluminescent AMH + c6 * (Kangrun Chemiluminescent AMH-0.5) + d6 * (Kangrun Chemiluminescent AMH-13) In the formula, a6 is any value selected from -0.45082 to 0.54656, b6 is any value selected from -0.35329 to 1.82169, c6 is any value selected from -0.63742 to 1.56010, and d6 is any value selected from -0.52283 to 0.22757.

[0110] Taking Kangrun chemiluminescence AMH vs. Beckman AMH as an example, the AMH value measured by Kangrun chemiluminescence was used as the independent variable x, and the AMH value measured by Beckman was used as the dependent variable y. According to the relationship between the independent and dependent variables in the data of the example, a linear spline regression was further adopted, i.e., a linear regression with smooth connections at the nodes was constructed. In Example 3 (2), the node selection was based on the principle that "the smaller the change, the better the equation." Based on this, the inventors, after extensive research, set three nodes for the spline regression, namely, 0.5 ng / ml and 13 ng / ml.

[0111] Based on the complete analysis in Example 3, a spline regression equation was used when the intercept did not include zero, and the Passing-Bablok regression equation was used to convert between Roche AMH and Kangrun chemiluminescent AMH when the intercept included zero.

[0112] [Table 11] JPEG2026505571000013.jpg93164

[0113] Recently, AMH has been considered to be the driving force regulating ovarian reserve and PCOS. However, significant differences in AMH detection methods significantly hinder the application of AMH-related artificial intelligence tools. More importantly, the significant differences in detection methods result in multiple AMH tests being conducted at different testing centers and hospitals. The inventors of this application first proposed the idea of ​​using Passing-Bablok + spline regression to convert AMH concentrations from one detection method to another. Through thorough research, they identified the most suitable method and system for standardizing or converting data from the three detection methods, which is convenient for practical application.

[0114] The idea behind the Passing-Bablok regression + spline regression method in this application is to first apply Passing-Bablok regression to detect whether there is a systematic difference, i.e., whether the 95% CI of the intercept of the Passing-Bablok regression result includes 0. If there is no systematic difference, i.e., if the intercept includes the value 0, then Passing-Bablok regression can be used to convert AMH detection between the two platforms. If there is a systematic difference, then spline regression is used. In the spline regression process, the AIC method can be applied to select the number of nodes. The smaller the AIC, the smaller the variation. The specific values ​​of these nodes were then thoroughly researched and adjusted according to the conversion values ​​calculated in the examples and their original values, and finally the most appropriate check node data was identified.

[0115] Three AMH detection methods were used in this study, and the applicants found that the detection values ​​of some individual samples using the Roche AMH detection method were much lower than those of the other two platforms. Biotin interference is believed to be the primary cause of occasional low values ​​when using the Roche AMH detection method. For the AMH kit, Roche chose to use a biotinylated AMH secondary antibody. This introduced the possibility of biotin interference into the design, whereas this was not the case with the other two kits. A small number of patients visiting ART clinics often take supplements or medications containing biotin, such as vitamin B7, vitamin H, and coenzyme R. For those taking biotin-containing supplements, biotin is present in the blood and binds to the avermectin magnetic beads, reducing the number of binding sites on the avermectin magnetic beads and resulting in lower AMH readings on the Roche platform.

[0116] In this example, the inventors first found no systematic differences between the Roche and Kangrun chemiluminescence methods, with the 95% CI of the intercepts covering 0, indicating only proportional differences. Three commercially available AMH detection methods demonstrated excellent results in terms of accuracy and precision. In our study, conversion of the three detection methods allowed for switching from one AMH detection method to another without the need for additional testing. This may therefore be useful for the application of AMH-related tools and potentially reduce the costs associated with visiting various clinics for patients undergoing artificial reproductive technology.

[0117] Example 4 For E2 detection, serum samples were provided by patients visiting the Reproductive Center of Peking University Third Hospital. After the initial blood test, subjects provided written consent to donate their remaining serum for research. This experiment received ethical approval from the Institutional Review Committee of Peking University Third Hospital, China.

[0118] E2 detection The same serum samples were frozen and thawed and then detected separately using two different manufacturers' E2 assays: the SIEMENS Immulite 2000 automated immunoassay system (Siemens Medical Diagnostics, Shanghai, China) and the KANGRUN Keaser 6600 automated immunoassay system (KANGRUN Inc., Guangzhou, Guangdong, China). E2 assays on both automated systems were performed once according to the manufacturer's recommendations. All E2 assay results were reported in pmol / L. Quality control for the E2 assay was provided by Bio-RAD Laboratories (Lyphochek Immunoassay Plus Control, Trilevel, catalog number 370, lot number 40370). The coefficient of variation for the tertiary control was less than 10%.

[0119] 4.1 Passing-Bablok regression results Passing-Bablok regression was used to construct a linear relationship between the Siemens E2 detection values ​​and the Kangrun E2 detection values. Figure 2 shows the fitting results. In Figure 2, the black dashed line reflects a situation where the two measurements are in perfect agreement, while the black straight fitting line is the result of Passing-Bablok regression. As can be seen from the figure, the linear relationship between the two measurements differs slightly from the dashed line, and this difference needs to be statistically tested.

[0120] Table 12 shows the results of the Passing-Bablok regression analysis. The results show that the 95% confidence interval for the intercept estimate does not include 0, indicating that the intercept term is statistically different from 0. The 95% confidence interval for the slope estimate does not include 1, indicating that the slope is statistically different from 1. The intercept primarily reflects a systematic difference. The 95% confidence interval does not include 0, indicating a systematic difference between the two measurements. The slope primarily reflects a difference in proportion. The 95% confidence interval does not include 1, suggesting that there may be a proportional difference between the two measurements.

[0121] [Table 12]

[0122] Figure 3 shows a Bland-Altman plot. The Bland-Altman plot complements the Passing-Bablok regression and graphically examines the agreement between two measurements. In Figure 3, the horizontal axis represents the mean of the Kangrun E2 detection value and the Siemens E2 detection value, and the vertical axis represents the difference between the Kangrun E2 detection value and the Siemens E2 detection value. The solid black line in the figure is the reference line, or zero value. The solid and dashed lines in the center represent the mean difference and its 95% confidence interval, respectively. The upper and lower lines in the gray frame (i.e., the gray area in the figure) represent the 95% distribution range of the difference (mean ± 1.96 × standard deviation), also known as the agreement limits. Theoretically, if the difference distribution follows a normal distribution, 95% of the differences should fall within the agreement limits.

[0123] The higher the agreement between the two measurements, the closer the center solid line representing the mean difference is to the reference line (the gray solid line representing a mean difference of 0). The agreement between the two methods evaluated was evaluated based on the number of data points outside the 95% agreement limits, the maximum difference within the agreement limits, and clinical acceptability. In this example, there were relatively many observations outside the agreement limits, most of which were negative, indicating large differences between Siemens and Kangrun in many detection values.

[0124] Figure 4 shows a peak graph of the Siemens E2 detection values ​​and the Kangrun E2 detection values. The horizontal axis of the peak graph represents the difference between the Siemens E2 detection values ​​and the Kangrun E2 detection values, while the vertical axis represents a conversion of the cumulative distribution graph. When the cumulative distribution probability is less than 50%, it is the cumulative distribution probability, and when it is greater than 50%, it is 1 - the cumulative distribution probability. If the two results are consistent, they should be distributed symmetrically around 0. As can be seen from Figure 4, the "Siemens E2 detection values ​​- Kangrun E2 detection values" is clearly left-leaning, and the values ​​for "Siemens E2 detection values ​​- Kangrun E2 detection values" are mostly below 0. The left tail is relatively long, indicating that some of the values ​​for "Siemens E2 detection values ​​- Kangrun E2 detection values" are very low. When combined with the Bland-Altman graph in Figure 3, it can be seen that there are many low values ​​for "Siemens E2 detection values ​​- Kangrun E2 detection values."

[0125] 4.2 Spline regression results (1) First, determine the number of nodes and their values. The number of nodes was determined primarily based on clinical and statistical indicators. Statistical indicators included BIC and AIC, with lower BIC and AIC values ​​indicating better models. Ultimately, based on the statistical indicators for different numbers of nodes and taking into account the actual clinical situation, we decided to select a model with two nodes. The two nodes were 660 pmol / L and 2030 pmol / L, respectively. (2) Fitting the model according to the number of nodes A linear spline regression model with two nodes was fitted and the results of the statistical analysis are shown in Table 13.

[0126] [Table 13]

[0127] According to the results in Table 13, the correspondence relationship between the Siemens E2 detection value (y) and the Kangrun E2 detection value (x) is established as follows: Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value + c8 * g1 (Kangrun E2 detection value - 660) + d8 * g2 (Kangrun E2 detection value - 2030) During the ceremony, If the Kangrun E2 detection value is less than 660 pmol / L, g1 = 0 and g2 = 0. In this case, the above formula becomes as follows: Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value When the Kangrun E2 detection value is >660 pmol / L and <=2030 pmol / L, g1=0 and g2=0. In this case, the above formula becomes: Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value + c8 * (Kangrun E2 detection value - 660) If the Kangrun E2 detection value is >2030 pmol / L, g1 = 0 and g2 = 1. In this case, the above formula becomes: Siemens E2 detection value = a8 + b8 * Kangrun E2 detection value + c8 * (Kangrun E2 detection value - 660) + d8 * (Kangrun E2 detection value - 2030) In the formula, a8 is any value selected from -93.069 to -6.91207, b8 is any value selected from 1.310892 to 1.569808, c8 is any value selected from -0.8957 to -0.52322, and d8 is any value selected from -0.08505 to 0.085318.

[0128] Taking the Kangrun E2 detection value versus the Siemens E2 detection value as an example, the E2 detection value measured by Kangrun was used as the independent variable x, and the E2 detection value measured by Siemens was used as the dependent variable y. According to the relationship between the independent and dependent variables in the data in this example, a linear spline regression was further adopted, i.e., a linear regression with smooth connections at the nodes was constructed. In this Example 4, the node selection was based on the principle that "the smaller the change, the better the equation." Based on this, the inventors, after extensive research, set two nodes for the spline regression, namely, 660 pmol / ml and 2030 pmol / ml.

[0129] (3) Evaluation of fitting model Table 14 shows a comparison of the fitting effects of spline regression and Passing-Bablok regression. The root mean square error, AIC, and AICc of spline regression are all lower than those of Passing-Bablok regression, and R 2 and adjusted R 2 It can be seen that is higher than that of linear regression, suggesting that spline regression has a better fitting effect.

[0130] [Table 14]

[0131] (4) Spline regression prediction Figure 5 shows a comparison of the predictions of Passing-Bablok regression and spline regression. Passing-Bablok regression has obvious bias in the low value range (Kangrun E2 detection value less than 1000), while spline regression shows more reasonable predictions.

[0132] Example 5 Of the two frozen serum samples obtained in Example 1, one was thawed and then detected by the Kangrun chemiluminescence method, and the other was detected by the Kangrun enzyme immunoassay (Anshlab) AMH detection method.

[0133] Generally speaking, if the overall relationship between the Kangrun chemiluminescence AMH detection data and the Kangrun enzyme immunoassay (Anshlab) AMH detection data is satisfactory, Passing-Bablok regression can be used to transform the two sets of data. Passing-Bablok regression uses a nonparametric method to fit the parameters a and b of the linear equation y = a + bx. If the 95% confidence interval (CI) for the intercept a does not include 0 or the 95% CI for the slope b does not include 1, this indicates a systematic or proportional difference between the two AMH detection results.

[0134] If the detection results of the two platform methods do not satisfy the overall relationship, you can consider using spline regression to find a transformation between the detection data of the two platforms. Spline regression is a piecewise polynomial function with smooth connections at the nodes. It can be a linear relationship (a straight line connecting at the nodes), a quadratic relationship, or a cubic relationship. In spline regression, based on the relationship between the independent and dependent variables, linear spline regression can be used to attempt to construct a linear regression with smooth connections at the nodes.

[0135] To further determine the number of nodes, linear spline regression was used for practical convenience.

[0136] The number of nodes is determined based on the BIC index. The lower the BIC, the better the model fitting effect. We specified 1 to 5 nodes. The results showed that the model fitting effect was best when there were 3 nodes. The results are shown in Figure 6.

[0137] The three nodes were set at 2 ng / mL, 3.7 ng / mL, and 6.9 ng / mL, respectively. For practical convenience, these were rounded off to set the three nodes at 2 ng / mL, 4 ng / mL, and 7 ng / mL, and the data was divided into four segments as shown in Figure 7.

[0138] Below is the linear spline regression fitting. The fitting effect of the three-node linear spline regression is as follows: The R2 and calibrated R2 were 0.9326 and 0.9322, respectively, and the AIC and AICC were 713.816 and 713.936, respectively.

[0139] [Table 15] *Slope 1 represents the slope of the first segment of data, slope 2 represents the change in the second segment of data compared to the slope of the first segment of data, slope 3 represents the change in the third segment of data compared to the slope of the second segment of data, and slope 4 represents the change in the fourth segment of data compared to the slope of the third segment of data. This summarizes the formula as follows: The formula for converting Kangrun chemiluminescent AMH (X) to Kangrun enzyme immunoassay (Anshlab) AMH (Y) is as follows: Kangrun Enzyme Immunosorbent Assay (Anshlab) AMH = a7 + b7 * Kangrun Chemiluminescent AMH + c7 * g1 * (Kangrun Chemiluminescent AMH-2) + d7 * g2 * (Kangrun Chemiluminescent AMH-4) + e7 * g3 * (Kangrun Chemiluminescent AMH-7) In the formula, a7 is an arbitrary value selected from -0.31000 to 0.20149, b7 is an arbitrary value selected from 0.73863 to 1.10064, c7 is an arbitrary value selected from -0.08941 to 0.51000, d7 is an arbitrary value selected from 0.08121 to 0.54582, and e7 is an arbitrary value selected from -0.70493 to -0.42738. moreover, If Kangrun chemiluminescence AMH<=2ng / ml, then g1=0, and in this case, the above formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescence AMH; When Kangrun chemiluminescent AMH is >2ng / ml and <=4ng / ml, g1=1 and g2=0. In this case, the above formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 (Kangrun chemiluminescent AMH-2), When Kangrun chemiluminescent AMH is >4ng / ml and <=7ng / ml, g1=1 and g2=1, and in this case, the above formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 (Kangrun chemiluminescent AMH-2) + d7 * g2 (Kangrun chemiluminescent AMH-4), If Kangrun chemiluminescence AMH > 7ng / ml, then g1 = 1, g2 = 1, and g3 = 1, and in this case, the above formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 (Kangrun chemiluminescent AMH-2) + d7 * g2 (Kangrun chemiluminescent AMH-4) + e7 * g3 (Kangrun chemiluminescent AMH-7).

[0140] The prediction results are shown in Figure 8. The prediction results for the first three segments of data below 7 ng / ml are shown in Figure 9.

[0141] This application uses Passing-Bablok regression and spline regression to establish a conversion relationship between Kangrun and Siemens. The assumption of Passing-Bablok regression is that both detection results are random, and its main purpose is to examine the consistency of both detection results. By comparing the difference between the intercept and 0 and the difference between the slope and 1, respectively, if both detections are not statistically significant, the two detection results can be considered consistent and interchangeable. Otherwise, the two detection results cannot be considered consistent, cannot be interchangeable, and must be converted using a different corresponding formula. If there is a clear linear relationship between the two detection results, they can be converted using Passing-Bablok regression. If there is no linear relationship, spline regression can be considered. Clear conversion formulas can be provided for both Passing-Bablok regression and spline regression.

[0142] Although the embodiments of the present invention have been described above, the present invention is not limited to the specific embodiments and application fields described above. The specific embodiments described above are not limiting, but merely illustrative and instructive. Under the teachings of this specification, those skilled in the art may create many modifications without departing from the scope of protection of the claims of the present invention, and all of these modifications are encompassed by the protection of the present invention.

Claims

1. 1. A method for converting hormone data detected by different detection methods, comprising: obtaining a first detection value of the hormone from a first platform; obtaining a second detection value of the hormone from a second platform; fitting the first detected value and the second detected value using Passing-Bablok regression; determining whether there is a systematic difference between the first detected value and the second detected value based on the fitting result of the Passing-Bablok regression; If there is no systematic difference between the first detected value and the second detected value, converting the first detected value or the second detected value based on a fitting formula of the Passing-Bablok regression; and if there is a systematic difference between the first detected value and the second detected value, fitting the first detected value and the second detected value based on a spline regression, and converting the first detected value or the second detected value based on a fitting formula of the spline regression.

2. 2. The method of claim 1, wherein determining whether there is a systematic difference between the first detection value and the second detection value based on the fitting result of the Passing-Bablok regression comprises determining whether there is a systematic difference between the first detection value and the second detection value by calculating a 95% confidence interval of an intercept of the Passing-Bablok regression result.

3. If the 95% confidence interval of the intercept includes 0, it is determined that there is no systematic difference between the first detection value and the second detection value; If the 95% confidence interval of the intercept does not include 0, it is determined that there is a systematic difference between the first detection value and the second detection value. The method of claim 2.

4. and identifying nodes of the spline regression using characteristic nodes and statistical indicators when fitting the first detected value and the second detected value based on the spline regression. The method according to any one of claims 1 to 3.

5. The method according to claim 4, wherein the statistical index is the AIC (Akaike Information Criterion) index or the BIC (Bayes Information Criterion) index.

6. The hormone is a sex hormone, and preferably, the sex hormone is a hypothalamic hormone, pituitary prolactin (PRL), follicle-stimulating hormone (FSH), luteinizing hormone (LH), anti-Mullerian hormone (AMH), inhibin B, estradiol (E ２ ), testosterone (T), dehydroepiandrosterone sulfate (DHEA-S), estriol (E ３ ), progesterone (P), preferably anti-Mullerian hormone (AMH)) or estradiol (E ２ The method according to any one of claims 1 to 5, wherein

7. Where the sex hormone is anti-Mullerian hormone (AMH), the first platform is a Roche AMH detection platform, and the second platform is a Kangrun chemiluminescent AMH detection platform, converting the detection results of the Roche AMH detection platform and the Kangrun chemiluminescent AMH detection platform using Passing-Bablok regression; Preferably, the formula for converting Kangrun chemiluminescent AMH(X) to Roche AMH(Y) is: Roche AMH = a1 + b1 * Kangrun chemiluminescent AMH; In the formula, a1 is any value selected from −0.0035 to 0.0303, and b1 is any value selected from 0.85 to 0.8844. Preferably, the formula for converting Roche AMH(X) to Kangrun chemiluminescent AMH(Y) is: Kangrun chemiluminescence AMH = a2 + b2 * Roche AMH; In the formula, a2 is any value selected from −0.0356 to 0.00393, and b2 is any value selected from 1.1307 to 1.1765. The method of claim 6.

8. wherein the sex hormone is anti-Mullerian hormone (AMH), the first platform is a Beckman AMH detection platform, and the second platform is a Roche AMH detection platform, converting the detection results of the Beckman AMH detection platform and the Roche AMH detection platform using spline regression; Preferably, the formula for converting Roche AMH(X) to Beckman AMH(Y) is: Beckman AMH=a3+b3*Roche AMH+c3*g1 (Roche AMH-1)+d3*g2 (Roche AMH-9), where Roche AMH <= 1 ng / ml, then g1 = 0 and g2 = 0, in which case the formula becomes: Beckman AMH=a3+b3*Roche AMH When Roche AMH > 1 ng / ml and <= 9 ng / ml, then g1 = 1 and g2 = 0, in which case the formula becomes: Beckman AMH=a3+b3*Roche AMH+c3*(Roche AMH-1) If Roche AMH > 9 ng / ml, then g1 = 1 and g2 = 1, in which case the formula becomes: Beckman AMH=a3+b3*Roche AMH+c3*(Roche AMH-1)+d3*(Roche AMH-9) In the formula, a3 is any value selected from −0.28809 to 0.30461, b3 is any value selected from 0.665236 to 1.430824, c3 is any value selected from 0.073606 to 0.900514, and d3 is any value selected from −0.70344 to −0.42116; Preferably, the formula for converting Beckman AMH(X) to Roche AMH(Y) is: Roche AMH=a4+b4*Beckman AMH+c4*g1 (Beckman AMH-0.5)+d4*g2 (Beckman AMH-1) where if the Beckman AMH value is <=0.5 ng / ml, then g1=0 and g2=0, in which case the formula becomes: Roche AMH=a4+b4*Beckman AMH When the Beckman AMH value is >0.5 ng / ml and <=1 ng / ml, then g1=1 and g2=0, in which case the formula becomes: Roche AMH=a4+b4*Beckman AMH+c4*(Beckman AMH-0.5) If the Beckman AMH value is >1 ng / ml, then g1 = 1 and g2 = 1, in which case the formula becomes: Roche AMH=a4+b4*Beckman AMH+c4*(Beckman AMH-0.5)+d4*(Beckman AMH-1), In the formula, a4 is any value selected from −0.42466 to 0.41822, b4 is any value selected from −0.11202 to 2.17363, c4 is any value selected from −1.96122 to 1.21734, and d4 is any value selected from −0.49419 to 0.66553. The method of claim 6.

9. Where the sex hormone is anti-Mullerian hormone (AMH), the first platform is a Beckman AMH detection platform, and the second platform is a Kangrún chemiluminescent AMH detection platform, converting the detection results of the Beckman AMH detection platform and the Kangrún chemiluminescent AMH detection platform using spline regression; Preferably, the formula for converting Beckman AMH(X) to Kangrun chemiluminescent AMH(Y) is: Kangrun chemiluminescence AMH=a5+b5*Beckman AMH+c5*g1 (Beckman AMH-1)+d5*g2 (Beckman AMH-4)+e5*g3 (Beckman AMH-13) where, if the Beckman AMH value is <= 1 ng / ml, then g1 = 0, g2 = 0, and g3 = 0, and in this case the formula becomes: Kangrun chemiluminescence AMH = a5 + b5 * Beckman AMH When Beckman AMH values ​​are >1 ng / ml and <=4 ng / ml, then g1=1, g2=0, and g3=0, and the formula then becomes: Kangrun Chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) If the Beckman AMH value is >4 ng / ml and <=13 ng / ml, then g1=1, g2=1, and g3=0, in which case the formula becomes: Kangrun Chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) + d5 * (Beckman AMH-4) If the Beckman AMH value is >13 ng / ml, then g1 = 1, g2 = 1, and g3 = 1, and in this case the formula becomes: Kangrun Chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) + d5 * (Beckman AMH-4) + e5 * (Beckman AMH-13) In the formula, a5 is any value selected from −0.24101 to 0.26258, b5 is any value selected from 0.72643 to 1.42037, c5 is any value selected from −0.78107 to 0.04326, d5 is any value selected from 0.29488 to 0.57880, and e5 is any value selected from −0.71455 to −0.47130. Preferably, the formula for converting Kangrun chemiluminescent AMH(X) to Beckman AMH(Y) is: Beckman AMH = a6 + b6 * Kangrun Chemiluminescent AMH + c6 * g1 (Kangrun Chemiluminescent AMH-0.5) + d6 * g2 (Kangrun Chemiluminescent AMH-13) where, if the Kangrun chemiluminescence AMH value <= 0.5 ng / ml, then g1 = 0 and g2 = 0, in which case the formula becomes: Beckman AMH = a6 + b6 * Kangrung chemiluminescent AMH If the Kangrun chemiluminescence AMH value is >0.5 and <=13 ng / ml, then g1=1 and g2=0, in which case the formula becomes: Beckman AMH = a6 + b6 * Kangrun Chemiluminescent AMH + c6 * (Kangrun Chemiluminescent AMH - 0.5) If the Kangrun chemiluminescent AMH value is >13 ng / ml, then g1=1 and g2=1, in which case the formula becomes: Beckman AMH = a6 + b6 * Kangrun Chemiluminescent AMH + c6 * (Kangrun Chemiluminescent AMH-0.5) + d6 * (Kangrun Chemiluminescent AMH-13) In the formula, a6 is any value selected from −0.45082 to 0.54656, b6 is any value selected from −0.35329 to 1.82169, c6 is any value selected from −0.63742 to 1.56010, and d6 is any value selected from −0.52283 to −0.22757. The method of claim 6.

10. When the sex hormone is anti-Mullerian hormone (AMH), the sex hormone is anti-Mullerian hormone (AMH), the first platform is a Kangrün chemiluminescent AMH detection platform, and the second platform is a Kangrün enzyme immunoassay (Anshlab) AMH detection platform, using spline regression to transform the detection results of the Kangrün chemiluminescent AMH detection platform and the Kangrün enzyme immunoassay (Anshlab) AMH detection platform; Preferably, the formula for converting Kangrún Chemiluminescent AMH(X) to Kangrún Enzyme Immuno (Anshlab) AMH(Y) is: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 * (Kangrun chemiluminescent AMH-2) + d7 * g2 * (Kangrun chemiluminescent AMH-4) + e7 * g3 * (Kangrun chemiluminescent AMH-7) In the formula, a7 is any value selected from −0.31000 to 0.20149, b7 is any value selected from 0.73863 to 1.10064, c7 is any value selected from −0.08941 to 0.51000, d7 is any value selected from 0.08121 to 0.54582, and e7 is any value selected from −0.70493 to −0.42738; Furthermore, if Kangrun chemiluminescent AMH <= 2 ng / ml, then g1 = 0, in which case the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH; When Kangrun chemiluminescent AMH > 2 ng / ml and <= 4 ng / ml, then g1 = 1 and g2 = 0, in which case the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 (Kangrun chemiluminescent AMH-2), When Kangrun chemiluminescent AMH > 4 ng / ml and <= 7 ng / ml, then g1 = 1 and g2 = 1, in which case the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 (Kangrun chemiluminescent AMH-2) + d7 * g2 (Kangrun chemiluminescent AMH-4), If Kangrun chemiluminescent AMH > 7 ng / ml, then g1 = 1, g2 = 1, and g3 = 1, in which case the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 (Kangrun chemiluminescent AMH-2) + d7 * g2 (Kangrun chemiluminescent AMH-4) + e7 * g3 (Kangrun chemiluminescent AMH-7) The method of claim 6.

11. The sex hormone is estradiol E ２ and wherein the first platform is a Kangrün estradiol detection platform and the second platform is a Siemens estradiol detection platform, converting the detection results of Kangrün estradiol and Siemens estradiol using spline regression; Siemens E ２ Detected value = a8 + b8 * Kangrun E ２ Detection value + c8 * g1 (Kangrun E ２ Detected value - 660) + d8 * g2 (Kangrun E ２ Detected value -2030) During the ceremony, Kangrun E ２ If the detected value is less than 660 pmol / L, g1=0 and g2=0. In this case, the above formula becomes as follows: Siemens E ２ Detected value = a8 + b8 * Kangrun E ２ Detection value Kangrun E ２ If the detected value is >660 pmol / L and <=2030 pmol / L, then g1=0 and g2=0, and in this case, the formula becomes: Siemens E ２ Detected value = a8 + b8 * Kangrun E ２ Detection value + c8 * (Kangrun E ２ Detected value -660) Kangrun E ２ If the detected value is greater than 2030 pmol / L, g1=0 and g2=1. In this case, the above formula becomes as follows: Siemens E ２ Detected value = a8 + b8 * Kangrun E ２ Detection value + c8 * (Kangrun E ２ Detected value - 660) + d8 * (Kangrun E ２ Detected value -2030) In the formula, a7 is any value selected from −93.069 to −6.91207, b7 is any value selected from 1.310892 to 1.569808, c7 is any value selected from −0.8957 to −0.52322, and d7 is any value selected from −0.08505 to 0.085318. The method of claim 7.

12. 1. A system for converting hormone data detected by different detection methods, comprising: a sub-module that obtains a first detection value of the hormone from a first platform; a sub-module that obtains a second detection value of the hormone from a second platform; a sub-module for fitting the first detected value and the second detected value using Passing-Bablok regression; a sub-module for determining whether there is a systematic difference between the first detected value and the second detected value based on a fitting result of the Passing-Bablok regression; a sub-module for determining whether there is a systematic difference between the first detection value and the second detection value based on the fitting result of the Passing-Bablok regression, If there is no systematic difference between the first detected value and the second detected value, converting the first detected value or the second detected value based on a fitting equation of the Passing-Bablok regression; If there is a systematic difference between the first detected value and the second detected value, the system performs a step of fitting the first detected value and the second detected value based on a spline regression and converting the first detected value or the second detected value based on a fitting formula of the spline regression.

13. 13. The system of claim 12, wherein determining whether there is a systematic difference between the first detection value and the second detection value based on the fitting result of the Passing-Bablok regression comprises determining whether there is a systematic difference between the first detection value and the second detection value by calculating a 95% confidence interval of an intercept of a linear regression result.

14. If the 95% confidence interval of the intercept includes 0, it is determined that there is no systematic difference between the first detection value and the second detection value; If the 95% confidence interval of the intercept does not include 0, it is determined that there is a systematic difference between the first detection value and the second detection value. The system of claim 13.

15. and identifying nodes of the spline regression using characteristic nodes and statistical indicators when fitting the first detected value and the second detected value based on the spline regression. A system according to any one of claims 12 to 14.

16. The system of claim 15 , wherein the statistical index is an AIC (Akaike Information Criterion) index or a BIC (Bayes Information Criterion) index.

17. The hormones are sex hormones, and the sex hormones include hypothalamic hormones, pituitary prolactin (PRL), follicle-stimulating hormone (FSH), luteinizing hormone (LH), anti-Mullerian hormone (AMH), inhibin B, estradiol (E ２ ), testosterone (T), dehydroepiandrosterone sulfate (DHEA-S), estriol (E ３ ), progesterone (P), preferably anti-Mullerian hormone (AMH)) or estradiol (E ２ 17. The system according to claim 12, wherein

18. Where the sex hormone is anti-Mullerian hormone (AMH), the first platform is a Roche AMH detection platform, and the second platform is a Kangrun chemiluminescent AMH detection platform, converting the detection results of the Roche AMH detection platform and the Kangrun chemiluminescent AMH detection platform using Passing-Bablok regression; Preferably, the formula for converting Kangrun chemiluminescent AMH(X) to Roche AMH(Y) is: Roche AMH = a1 + b1 * Kangrun chemiluminescent AMH; In the formula, a1 is any value selected from −0.0035 to 0.0303, and b1 is any value selected from 0.85 to 0.8844. Preferably, the formula for converting Roche AMH(X) to Kangrun chemiluminescent AMH(Y) is: Kangrun chemiluminescence AMH = a2 + b2 * Roche AMH; In the formula, a2 is any value selected from −0.0356 to 0.00393, and b2 is any value selected from 1.1307 to 1.1765.

20. The system of claim 17.

19. wherein the sex hormone is anti-Mullerian hormone (AMH), the first platform is a Beckman AMH detection platform, and the second platform is a Roche AMH detection platform, converting the detection results of the Beckman AMH detection platform and the Roche AMH detection platform using spline regression; Preferably, the formula for converting Roche AMH(X) to Beckman AMH(Y) is: Beckman AMH=a3+b3*Roche AMH+c3*g1 (Roche AMH-1)+d3*g2 (Roche AMH-9), where Roche AMH <= 1 ng / ml, then g1 = 0 and g2 = 0, in which case the formula becomes: Beckman AMH=a3+b3*Roche AMH When Roche AMH > 1 ng / ml and <= 9 ng / ml, then g1 = 1 and g2 = 0, in which case the formula becomes: Beckman AMH=a3+b3*Roche AMH+c3*(Roche AMH-1) If Roche AMH > 9 ng / ml, then g1 = 1 and g2 = 1, in which case the formula becomes: Beckman AMH=a3+b3*Roche AMH+c3*(Roche AMH-1)+d3*(Roche AMH-9) In the formula, a3 is any value selected from −0.28809 to 0.30461, b3 is any value selected from 0.665236 to 1.430824, c3 is any value selected from 0.073606 to 0.900514, and d3 is any value selected from −0.70344 to −0.42116; Preferably, the formula for converting Beckman AMH(X) to Roche AMH(Y) is: Roche AMH=a4+b4*Beckman AMH+c4*g1 (Beckman AMH-0.5)+d4*g2 (Beckman AMH-1) where if the Beckman AMH value is <=0.5 ng / ml, then g1=0 and g2=0, in which case the formula becomes: Roche AMH=a4+b4*Beckman AMH When the Beckman AMH value is >0.5 ng / ml and <=1 ng / ml, then g1=1 and g2=0, in which case the formula becomes: Roche AMH=a4+b4*Beckman AMH+c4*(Beckman AMH-0.5) If the Beckman AMH value is >1 ng / ml, then g1 = 1 and g2 = 1, in which case the formula becomes: Roche AMH=a4+b4*Beckman AMH+c4*(Beckman AMH-0.5)+d4*(Beckman AMH-1), In the formula, a4 is any value selected from −0.42466 to 0.41822, b4 is any value selected from −0.11202 to 2.17363, c4 is any value selected from −1.96122 to 1.21734, and d4 is any value selected from −0.49419 to 0.66553.

20. The system of claim 17.

20. Where the sex hormone is anti-Mullerian hormone (AMH), the first platform is a Beckman AMH detection platform, and the second platform is a Kangrún chemiluminescent AMH detection platform, converting the detection results of the Beckman AMH detection platform and the Kangrún chemiluminescent AMH detection platform using spline regression; Preferably, the formula for converting Beckman AMH(X) to Kangrun chemiluminescent AMH(Y) is: Kangrun chemiluminescence AMH=a5+b5*Beckman AMH+c5*g1 (Beckman AMH-1)+d5*g2 (Beckman AMH-4)+e5*g3 (Beckman AMH-13) where, if the Beckman AMH value is <= 1 ng / ml, then g1 = 0, g2 = 0, and g3 = 0, and in this case the formula becomes: Kangrun chemiluminescence AMH = a5 + b5 * Beckman AMH When Beckman AMH values ​​are >1 ng / ml and <=4 ng / ml, then g1=1, g2=0, and g3=0, and the formula then becomes: Kangrun Chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) If the Beckman AMH value is >4 ng / ml and <=13 ng / ml, then g1=1, g2=1, and g3=0, in which case the formula becomes: Kangrun Chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) + d5 * (Beckman AMH-4) If the Beckman AMH value is >13 ng / ml, then g1 = 1, g2 = 1, and g3 = 1, and in this case the formula becomes: Kangrun Chemiluminescent AMH = a5 + b5 * Beckman AMH + c5 * (Beckman AMH-1) + d5 * (Beckman AMH-4) + e5 * (Beckman AMH-13) In the formula, a5 is any value selected from −0.24101 to 0.26258, b5 is any value selected from 0.72643 to 1.42037, c5 is any value selected from −0.78107 to 0.04326, d5 is any value selected from 0.29488 to 0.57880, and e5 is any value selected from −0.71455 to −0.47130. Preferably, the formula for converting Kangrun chemiluminescent AMH(X) to Beckman AMH(Y) is: Beckman AMH = a6 + b6 * Kangrun Chemiluminescent AMH + c6 * g1 (Kangrun Chemiluminescent AMH-0.5) + d6 * g2 (Kangrun Chemiluminescent AMH-13) where, if the Kangrun chemiluminescence AMH value <= 0.5 ng / ml, then g1 = 0 and g2 = 0, in which case the formula becomes: Beckman AMH = a6 + b6 * Kangrung chemiluminescent AMH If the Kangrun chemiluminescence AMH value is >0.5 and <=13 ng / ml, then g1=1 and g2=0, in which case the formula becomes: Beckman AMH = a6 + b6 * Kangrun Chemiluminescent AMH + c6 * (Kangrun Chemiluminescent AMH - 0.5) If the Kangrun chemiluminescent AMH value is >13 ng / ml, then g1=1 and g2=1, in which case the formula becomes: Beckman AMH = a6 + b6 * Kangrun Chemiluminescent AMH + c6 * (Kangrun Chemiluminescent AMH-0.5) + d6 * (Kangrun Chemiluminescent AMH-13) In the formula, a6 is any value selected from −0.45082 to 0.54656, b6 is any value selected from −0.35329 to 1.82169, c6 is any value selected from −0.63742 to 1.56010, and d6 is any value selected from −0.52283 to −0.22757.

20. The system of claim 17.

21. When the sex hormone is anti-Mullerian hormone (AMH), the sex hormone is anti-Mullerian hormone (AMH), the first platform is a Kangrün chemiluminescent AMH detection platform, and the second platform is a Kangrün enzyme immunoassay (Anshlab) AMH detection platform, using spline regression to transform the detection results of the Kangrün chemiluminescent AMH detection platform and the Kangrün enzyme immunoassay (Anshlab) AMH detection platform; Preferably, the formula for converting Kangrún Chemiluminescent AMH(X) to Kangrún Enzyme Immuno (Anshlab) AMH(Y) is: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 * (Kangrun chemiluminescent AMH-2) + d7 * g2 * (Kangrun chemiluminescent AMH-4) + e7 * g3 * (Kangrun chemiluminescent AMH-7) In the formula, a7 is any value selected from −0.31000 to 0.20149, b7 is any value selected from 0.73863 to 1.10064, c7 is any value selected from −0.08941 to 0.51000, d7 is any value selected from 0.08121 to 0.54582, and e7 is any value selected from −0.70493 to −0.42738; Furthermore, if Kangrun chemiluminescent AMH <= 2 ng / ml, then g1 = 0, in which case the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH; When Kangrun chemiluminescent AMH > 2 ng / ml and <= 4 ng / ml, then g1 = 1 and g2 = 0, in which case the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 (Kangrun chemiluminescent AMH-2), When Kangrun chemiluminescent AMH > 4 ng / ml and <= 7 ng / ml, then g1 = 1 and g2 = 1, in which case the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 (Kangrun chemiluminescent AMH-2) + d7 * g2 (Kangrun chemiluminescent AMH-4), If Kangrun chemiluminescent AMH > 7 ng / ml, then g1 = 1, g2 = 1, and g3 = 1, in which case the formula becomes: Kangrun enzyme immunoassay (Anshlab) AMH = a7 + b7 * Kangrun chemiluminescent AMH + c7 * g1 (Kangrun chemiluminescent AMH-2) + d7 * g2 (Kangrun chemiluminescent AMH-4) + e7 * g3 (Kangrun chemiluminescent AMH-7) 20. The system of claim 17.

22. The sex hormone is estradiol E ２ and wherein the first platform is a Kangrün estradiol detection platform and the second platform is a Siemens estradiol detection platform, converting the detection results of Kangrün estradiol and Siemens estradiol using spline regression; Siemens E ２ Detected value = a8 + b8 * Kangrun E ２ Detection value + c8 * g1 (Kangrun E ２ Detected value - 660) + d8 * g2 (Kangrun E ２ Detected value -2030) During the ceremony, Kangrun E ２ If the detected value is less than 660 pmol / L, g1=0 and g2=0. In this case, the above formula becomes as follows: Siemens E ２ Detected value = a8 + b8 * Kangrun E ２ Detection value Kangrun E ２ If the detected value is >660 pmol / L and <=2030 pmol / L, then g1=0 and g2=0, and in this case, the formula becomes: Siemens E ２ Detected value = a8 + b8 * Kangrun E ２ Detection value + c8 * (Kangrun E ２ Detected value -660) Kangrun E ２ If the detected value is greater than 2030 pmol / L, g1=0 and g2=1. In this case, the above formula becomes as follows: Siemens E ２ Detected value = a8 + b8 * Kangrun E ２ Detection value + c8 * (Kangrun E ２ Detected value - 660) + d8 * (Kangrun E ２ Detected value -2030) In the formula, a7 is any value selected from −93.069 to −6.91207, b7 is any value selected from 1.310892 to 1.569808, c7 is any value selected from −0.8957 to −0.52322, and d7 is any value selected from −0.08505 to 0.085318.

20. The system of claim 17.

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