Device for predicting BRCA1 / 2 mutation state of Chinese breast cancer patient
By establishing a BRCA1/2 mutation carrier probability prediction model based on logistic regression and using high-risk factors for precise assessment, the problem of the inability to accurately assess the BRCA1/2 mutation carrier probability in Chinese breast cancer patients in existing technologies has been solved, enabling the identification and individualized treatment of genetically high-risk populations.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-08
- Publication Date
- 2026-04-10
AI Technical Summary
Existing predictive models cannot accurately assess the probability of BRCA1/2 mutation carriers in Chinese breast cancer patients, resulting in an inability to effectively identify genetically high-risk individuals and a lack of precise screening methods.
A BRCA1/2 mutation carrier probability prediction model based on logistic regression was established. High-risk factors such as age at breast cancer initial diagnosis, history of bilateral breast cancer, family history of breast cancer and ovarian cancer in first- to third-degree relatives, negative hormone receptor status, and HER2 status were used to predict the probability using the formula Logit(P)=β0+β1X1+β2X2+β3X3+β4X4+β5X5.
It enables precise calculation of the BRCA1/2 mutation carrier probability in Chinese breast cancer patients, identifies high-risk genetic groups, guides individualized gene testing and treatment strategies, and reduces medical costs.
Smart Images
Figure CN121839094A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of biomedicine, and specifically relates to a device for predicting the BRCA1 / 2 mutation status of Chinese breast cancer patients. Background Technology
[0002] Breast cancer is a significant disease affecting women's health. According to the latest epidemiological data, breast cancer has surpassed lung cancer to become the leading cause of cancer incidence among women worldwide, with 420,000 cases reported in China. Compared to other countries, breast cancer patients in my country are characterized by earlier onset and later clinical stage at initial diagnosis. With the aging population and the influence of risk factors such as environmental pollution, the incidence of breast cancer continues to rise.
[0003] 5%-10% of breast cancer cases exhibit familial clustering, and their tumorigenesis has been confirmed to be associated with specific susceptibility genes. Among these, BRCA1 and BRCA2 genes are the two most important breast cancer susceptibility genes. Breast cancer with BRCA1 / 2 mutations has unique pathogenesis and clinicopathological features. Compared with sporadic breast cancer, BRCA1 / 2-mutant breast cancer often presents with multiple family members affected, earlier age of onset, and a higher incidence of contralateral (or bilateral) breast cancer. The risk of developing other related tumors may also be increased for the individual or family members. Therefore, the prevention, early diagnosis, and treatment strategies for BRCA1 / 2-mutant breast cancer differ from those for sporadic breast cancer.
[0004] According to foreign studies, compared with non-mutant patients, breast cancer patients carrying BRCA1 / 2 mutations have a higher proportion of bilateral breast cancer, early-onset, familial, and triple-negative breast cancer. Previous research by the applicant's research team has also confirmed that the mutation rate of pathogenic germline mutations in BRCA1 / 2 in the overall Chinese population is 6.0%; specifically, it is 20.8% in familial breast cancer patients, 19.0% in bilateral breast cancer, 13.3% in triple-negative breast cancer, and 9.7% in early-onset breast cancer (age ≤40 years and no family history). The overall BRCA1 / 2 mutation frequency in Chinese breast cancer is similar to that in European and American populations, but the mutation spectrum differs significantly. In European and American populations, the BRCA1 mutation frequency is higher than BRCA2; however, in Chinese breast cancer patients, the BRCA2 mutation frequency is higher than BRCA1, approximately twice that of BRCA1. Furthermore, approximately 30-40% of BRCA1 / 2 mutation sites in the Chinese population are not found in European and American populations, which may be population-specific. Other factors, such as lymph node status and reproductive status, have an impact on the probability of carrying BRCA1 / 2 mutations, but this remains controversial, especially given the lack of data in Chinese women.
[0005] Currently, China faces practical difficulties in screening for genetically high-risk breast cancer patients. When assessing whether a Chinese breast cancer patient carries germline pathogenic mutations in the BRCA1 / 2 gene, the existing approach involves clinicians informing patients with high-risk factors, such as family history, that they have a higher probability of carrying BRCA1 / 2 germline pathogenic mutations than the general population, without providing precise numerical values. Although models predicting the probability of BRCA1 / 2 mutation carriage in breast cancer have been developed abroad, current research evidence suggests that these models are not well-suited for assessing the Chinese breast cancer population due to significant differences in the characteristics of the Chinese breast cancer population and mutation profile compared to Western populations. Therefore, a model capable of accurately predicting the probability of BRCA1 / 2 mutation carriage in Chinese breast cancer patients is still needed. Summary of the Invention
[0006] To address the aforementioned problems, the purpose of this invention is to provide a device for predicting the BRCA1 / 2 mutation status in Chinese breast cancer patients.
[0007] Specifically, a first aspect of the present invention provides an apparatus for predicting the BRCA1 / 2 mutation status of Chinese breast cancer patients, the apparatus being used to perform a method for predicting the probability of BRCA1 / 2 mutation carrying in Chinese breast cancer patients, the prediction method being based on a BRCA1 / 2 mutation carrying probability prediction model for Chinese breast cancer patients.
[0008] The BRCA1 / 2 mutation carrier probability prediction model for Chinese breast cancer patients is as follows:
[0009] Logit(P)=β0+β1X1+β2X2+β3X3+β4X4+β5X5
[0010] Where: P represents the predicted probability of BRCA1 / 2 mutation carrier in Chinese breast cancer patients, β0 represents the constant of the regression formula, X1, X2, X3, X4, and X5 represent the values of high-risk factors such as age at initial diagnosis of breast cancer, history of bilateral breast cancer, family history of breast cancer and ovarian cancer in first- to third-degree relatives, negative hormone receptor status, and HER2 status, respectively, and β1, β2, β3, β4, and β5 represent the regression coefficients of the corresponding high-risk factors.
[0011] A second aspect of the present invention provides a method for establishing a BRCA1 / 2 mutation carrier probability prediction model for Chinese breast cancer patients, comprising the following steps:
[0012] (1) Obtain the BRCA1 / 2 mutation status of multiple Chinese breast cancer patients;
[0013] (2) Obtain clinicopathological parameters of the multiple Chinese breast cancer patients;
[0014] (3) Based on the BRCA1 / 2 mutation status obtained in step (1) and the clinicopathological parameters obtained in step (2), logistic regression was used to determine the high-risk factors for the probability of BRCA1 / 2 mutation carrying in Chinese breast cancer patients. The high-risk factors include age at initial diagnosis of breast cancer, history of bilateral breast cancer, family history of breast cancer and ovarian cancer in first- to third-degree relatives, negative hormone receptor status, and HER2 status.
[0015] (4) Based on the aforementioned high-risk factors, a model was established using logistic regression to predict the probability of BRCA1 / 2 mutation carriage in Chinese breast cancer patients:
[0016] Logit(P)=β0+β1X1+β2X2+β3X3+β4X4+β5X5
[0017] Where: P represents the predicted probability of BRCA1 / 2 mutation carrier in Chinese breast cancer patients, β0 represents the constant of the regression formula, X1, X2, X3, X4, and X5 represent the values of high-risk factors such as age at initial diagnosis of breast cancer, history of bilateral breast cancer, family history of breast cancer and ovarian cancer in first- to third-degree relatives, negative hormone receptor status, and HER2 status, respectively, and β1, β2, β3, β4, and β5 represent the regression coefficients of the corresponding high-risk factors.
[0018] A third aspect of the present invention provides a prediction model established by the above method.
[0019] The BRCA1 / 2 mutation carrier probability prediction model established in this invention accurately calculates the BRCA1 / 2 mutation carrier probability in Chinese breast cancer patients. This finding has clinical application value. The device of this invention for assessing the BRCA1 / 2 mutation carrier probability of a tested individual can effectively identify high-risk individuals for breast cancer genetically. Based on this, clinicians can assess the individual's BRCA1 / 2 mutation carrier probability by combining the individual's personal history, medical history, and family history of cancer. Furthermore, different genetic counseling and gene testing strategies can be adopted for breast cancer patients. Even further, different clinical interventions can be implemented for breast cancer patients carrying mutations. Therefore, this invention has significant application prospects in the prediction and prevention of tumor incidence risk and personalized treatment.
[0020] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description
[0021] The above and other objects, features and advantages of the present invention will become more apparent from the more detailed description of exemplary embodiments of the invention in conjunction with the accompanying drawings.
[0022] Figure 1 The comparison results of evaluating the various predictive model metrics using AUC and calibration curves are shown.
[0023] Figure 2 The diagram shows a nomogram of the BRCA1 / 2 mutation carrier probability prediction model established in an embodiment of the present invention for Chinese breast cancer patients.
[0024] Figure 3 A commercial web platform is shown, which is based on the BRCA1 / 2 mutation carrier probability prediction model for Chinese breast cancer patients established according to embodiments of the present invention. Detailed Implementation
[0025] Preferred embodiments of the invention will now be described in more detail. While preferred embodiments of the invention are described below, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein.
[0026] A first aspect of the present invention provides an apparatus for predicting the BRCA1 / 2 mutation status of Chinese breast cancer patients, the apparatus being used to perform a method for predicting the probability of BRCA1 / 2 mutation carriage in Chinese breast cancer patients, the prediction method being based on a BRCA1 / 2 mutation carriage probability prediction model for Chinese breast cancer patients.
[0027] The BRCA1 / 2 mutation carrier probability prediction model for Chinese breast cancer patients is as follows:
[0028] Logit(P)=β0+β1X1+β2X2+β3X3+β4X4+β5X5
[0029] Where: P represents the predicted probability of BRCA1 / 2 mutation carrier in Chinese breast cancer patients, β0 represents the constant of the regression formula, X1, X2, X3, X4, and X5 represent the values of high-risk factors such as age at initial diagnosis of breast cancer, history of bilateral breast cancer, family history of breast cancer and ovarian cancer in first- to third-degree relatives, negative hormone receptor status, and HER2 status, respectively, and β1, β2, β3, β4, and β5 represent the regression coefficients of the corresponding high-risk factors.
[0030] According to a preferred embodiment of the present invention, the value of β0 ranges from -2.1 to -2.3, the value of β1 ranges from -0.04 to -0.05, the value of β2 ranges from 1.7 to 1.8, the value of β3 ranges from 1.6 to 1.7, the value of β4 ranges from 0.65 to 0.75, and the value of β5 ranges from 1.05 to 1.15.
[0031] According to a preferred embodiment of the present invention, the model is as follows:
[0032] Logit(P)=-2.2431-0.0432X1+1.7548X2+1.6586X3+0.7069X4+1.0972X5.
[0033] The values for each high-risk factor were determined as follows:
[0034] X1 represents the age at initial diagnosis of breast cancer;
[0035] When a patient has a history of bilateral breast cancer, X2 is 1; when a patient has a history of unilateral breast cancer, X2 is 0.
[0036] When there is ≥1 family history of breast cancer or ovarian cancer in first- to third-degree relatives, X3 is 1; when there is no family history of breast cancer or ovarian cancer in first- to third-degree relatives, X3 is 0.
[0037] When the negative hormone receptor is negative, X4 is 1; when the negative hormone receptor is positive, X4 is 0. The negative hormone receptor is the estrogen receptor and the progesterone receptor. If one of them is negative, X4 will be 1.
[0038] When the HER2 status is negative, X5 is 1; when the HER2 status is positive, X5 is 0.
[0039] According to the present invention, the method for predicting the probability of BRCA1 / 2 mutation carriage in Chinese breast cancer patients may include the following steps:
[0040] Obtain data from the test subjects;
[0041] The data of the subject is input into the model to calculate the BRCA1 / 2 mutation carrier probability of the subject.
[0042] The apparatus of the present invention can be any device capable of implementing the prediction method, such as a computer or a mobile phone. Specifically, the apparatus includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the prediction method. Alternatively, the apparatus can also be a nodal chart card based on the model.
[0043] A second aspect of the present invention provides a method for establishing a BRCA1 / 2 mutation carrier probability prediction model for Chinese breast cancer patients, comprising the following steps:
[0044] (1) Obtain the BRCA1 / 2 mutation status of multiple Chinese breast cancer patients;
[0045] (2) Obtain clinicopathological parameters of the multiple Chinese breast cancer patients;
[0046] (3) Based on the BRCA1 / 2 mutation status obtained in step (1) and the clinicopathological parameters obtained in step (2), logistic regression was used to determine the high-risk factors for the probability of BRCA1 / 2 mutation carrying in Chinese breast cancer patients. The high-risk factors include age at initial diagnosis of breast cancer, history of bilateral breast cancer, family history of breast cancer and ovarian cancer in first- to third-degree relatives, negative hormone receptor status, and HER2 status.
[0047] (4) Based on the aforementioned high-risk factors, a model was established using logistic regression to predict the probability of BRCA1 / 2 mutation carriage in Chinese breast cancer patients:
[0048] Logit(P)=β0+β1X1+β2X2+β3X3+β4X4+β5X5
[0049] Where: P represents the predicted probability of BRCA1 / 2 mutation carrier in Chinese breast cancer patients, β0 represents the constant of the regression formula, X1, X2, X3, X4, and X5 represent the values of high-risk factors such as age at initial diagnosis of breast cancer, history of bilateral breast cancer, family history of breast cancer and ovarian cancer in first- to third-degree relatives, negative hormone receptor status, and HER2 status, respectively, and β1, β2, β3, β4, and β5 represent the regression coefficients of the corresponding high-risk factors.
[0050] To ensure model accuracy, the amount of data should be maximized and the data inclusion criteria should be strictly controlled. Specifically, the number of Chinese breast cancer patients included in the data for modeling is 6,000 to 6,500. All of these breast cancer patients are primary breast cancer patients and are unrelated by blood. They are preferably female, and more preferably Han Chinese.
[0051] The BRCA1 / 2 mutation carrier probability prediction described in this invention can be detected using various techniques known in the art. In a specific embodiment of this invention, DNA sequencing technology and multiplex ligation-dependent probe amplification (MLPA) technology were used to obtain the BRCA1 / 2 mutation status of multiple Chinese breast cancer patients.
[0052] According to the present invention, each regression coefficient is determined by a logistic regression model, wherein β0 ranges from -2.1 to -2.3, β1 ranges from -0.04 to -0.05, β2 ranges from 1.7 to 1.8, β3 ranges from 1.6 to 1.7, β4 ranges from 0.65 to 0.75, and β5 ranges from 1.05 to 1.15.
[0053] More specifically, the model is:
[0054] Logit(P)=-2.2431-0.0432X1+1.7548X2+1.6586X3+0.7069X4+1.0972X5.
[0055] According to the present invention, the method for determining the numerical values of each high-risk factor includes:
[0056] X1 represents the age at initial diagnosis of breast cancer;
[0057] When a patient has a history of bilateral breast cancer, X2 is 1; when a patient has a history of unilateral breast cancer, X2 is 0.
[0058] When there is ≥1 family history of breast cancer or ovarian cancer in first- to third-degree relatives, X3 is 1; when there is no family history of breast cancer or ovarian cancer in first- to third-degree relatives, X3 is 0.
[0059] When the negative hormone receptor status is negative, X4 is 1; when the negative hormone receptor status is positive, X4 is 0.
[0060] When the HER2 status is negative or positive, X5 is 1; when the HER2 status is positive, X5 is 0.
[0061] In this invention, the negative hormone receptors refer to estrogen receptors and progesterone receptors. If one of them is negative, X4 is equivalent to a value of 1.
[0062] The present invention also provides a prediction model established by the above method.
[0063] The method of this invention predicts the probability of an individual carrying BRCA1 / 2 mutations based on high-risk factors, which can effectively identify genetically high-risk groups for tumors. This allows for targeted genetic testing, genetic counseling, and family management, avoiding excessive genetic testing and reducing medical costs. Furthermore, it can identify genetically high-risk groups for breast cancer based on high-risk factors, enabling targeted treatment and improving therapeutic efficacy.
[0064] Specifically, in genetic counseling, when the test results are greater than the risk threshold of clinical practice guidelines (e.g., >10%), individuals diagnosed as being at high risk for breast cancer genetically are advised to undergo genetic counseling and discuss the selection of examination methods such as gene testing with their clinicians.
[0065] The predictive model developed using this invention can directly calculate an individual's BRCA1 / 2 mutation carrier probability, specifically using a nomogram scoring method (e.g., Figure 2 (as shown), or use a commercial web platform (such as...) Figure 3(As shown) Direct risk prediction is performed. Nomograms are suitable for risk assessment of one-to-one, small sample populations. The principle is to calculate the scores corresponding to the five high-risk factors on the nomogram separately, add them together to obtain the total score, and then look up the corresponding risk value on the nomogram to obtain the BRCA1 / 2 mutation carrier probability of the individual being tested. Alternatively, a computer device can be developed, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above method.
[0066] In practical implementation, those skilled in the art can choose any of the above-mentioned techniques to detect the BRCA1 / 2 mutation carrier probability in breast cancer patients according to the actual situation. A combination of multiple techniques can also be used to detect the BRCA1 / 2 mutation carrier probability in breast cancer patients. In one specific embodiment of the present invention, a nomogram is used. Because nomograms are simple and easy to operate using a chart format, they have the advantages of simplicity and economy when clinicians and patients conduct one-on-one genetic counseling and make clinical decisions. When applying the solution of the present invention to risk assessment of a large population of test subjects, the nomogram does not have the advantage of speed. In this case, specific computer software or specially developed programs can be used for batch calculation. For example, specific computer software such as R language can be used for processing. By inputting information on five high-risk factors, the calculation process does not require manual operation, thereby realizing the calculation and result presentation.
[0067] Furthermore, the present invention can also provide a detection device for assessing the probability of BRCA1 / 2 mutation carrier in an individual, mainly comprising a detection unit and a data analysis unit, wherein:
[0068] The detection unit is used to detect high-risk factors affecting the probability of BRCA1 / 2 mutation carrier status in the tested individual and obtain the detection results. High-risk factors include: age at initial diagnosis of breast cancer, history of bilateral breast cancer, family history of breast and ovarian cancer, hormone receptor status, and HER2 status. The data analysis unit is used to analyze and process the detection results from the detection unit.
[0069] The detection device for assessing the BRCA1 / 2 mutation carrier probability of an individual as described in this invention can be a virtual device, as long as it can realize the functions of the detection unit and the data analysis unit. The detection unit can include various statistical software, web pages, or detection instruments; the data analysis unit can be any computing instrument, module, or virtual device capable of analyzing and processing the detection results of the detection unit to obtain the BRCA1 / 2 mutation carrier probability of the individual. For example, it can be pre-designed genetic risk assessment software, which can output the BRCA1 / 2 mutation carrier probability value by inputting the detection results of the detection unit into the program.
[0070] Example 1: Assessment of BRCA1 / 2 mutation carrier probability in 6331 breast cancer patients
[0071] (1) Case selection
[0072] Inclusion criteria for the case sample: Patients pathologically diagnosed with primary breast cancer, all of whom were Han Chinese and unrelated by blood. Cases meeting these criteria were eligible for inclusion in this study. The final number of included cases was 6331.
[0073] (2) Data collection
[0074] The BRCA1 / 2 mutation status of 6331 Chinese breast cancer patients was determined using DNA sequencing and multiplex ligation probe amplification techniques.
[0075] Clinical data were collected from 6,331 Chinese breast cancer patients.
[0076] (3) Identification of high-risk factors
[0077] Based on the BRCA1 / 2 mutation status and clinicopathological parameters obtained in step (2), logistic regression was used to identify five high-risk factors for the probability of BRCA1 / 2 mutation carrier status in Chinese breast cancer patients, including age at initial diagnosis of breast cancer, history of bilateral breast cancer, family history of positive breast cancer and ovarian cancer in first- to third-degree relatives, negative hormone receptor status, and negative HER2 status. The analysis results showed that all five high-risk factors were significantly associated with the probability of BRCA1 / 2 mutation carrier status.
[0078] (4) Prediction model establishment
[0079] Based on the aforementioned high-risk factors, a model was established using logistic regression to predict the probability of BRCA1 / 2 mutation carriage in Chinese breast cancer patients:
[0080] Logit(P) = -2.2431 - 0.0432 [Age at initial breast cancer diagnosis] + 1.7548 [History of bilateral breast cancer] + 1.6586 [Family history of positive breast and ovarian cancer in first- to third-degree relatives] + 0.7069 [Negative hormone receptor status] + 1.0972 [Negative HER2 status]
[0081] The values for each risk factor are determined as follows:
[0082] X1 represents the age at initial diagnosis of breast cancer;
[0083] When a patient has a history of bilateral breast cancer, X2 is 1; when a patient has a history of unilateral breast cancer, X2 is 0.
[0084] When there is ≥1 family history of breast cancer or ovarian cancer in first- to third-degree relatives, X3 is 1; when there is no family history of breast cancer or ovarian cancer in first- to third-degree relatives, X3 is 0.
[0085] When the negative hormone receptor status is positive, X4 is 1; when the negative hormone receptor status is negative, X4 is 0.
[0086] When the HER2 status is positive, X5 is 1; when the HER2 status is negative, X5 is 0.
[0087] Example 2
[0088] In this embodiment, data from 3836 breast cancer patients in China were used to validate the model established in Example 1. AUC and calibration curves were used as indicators to evaluate the predictive model, and the results were compared with three foreign models. The results are as follows: Figure 1 As shown, the risk prediction model established in this invention performs best, with an AUC of 0.77, which is superior to foreign prediction models (0.65-0.73).
[0089] Example 3
[0090] The analysis of clients undergoing tumor genetic counseling and individualized treatment will follow these steps:
[0091] (1) Conduct questionnaires and collect family history of cancer.
[0092] Collect information on the visitor's age, personal history, past medical history, and detailed family history of cancer. The following information was obtained: The visitor is 35 years old, has bilateral breast cancer, is estrogen receptor-negative, progesterone receptor-negative, and HER2-negative; her mother was 40 years old and had left breast cancer.
[0093] (2) Extract information on 5 high-risk factors and visualize them using a nomogram (e.g., Figure 2 The method is used to complete the risk assessment report for the research subjects.
[0094] Based on the scores corresponding to each high-risk factor: age at initial diagnosis of breast cancer (78 points), bilateral breast cancer (58 points), family history of breast and ovarian cancer (54 points), hormone receptor (24 points), HER2 receptor (36 points), the total score is 250 points. The corresponding nomogram shows that the probability of the visitor carrying the BRCA1 / 2 mutation is 81.2%.
[0095] (3) Genetic risk assessment
[0096] Inform the visitor that due to high-risk factors such as early-onset breast cancer and a family history of breast cancer, the probability of carrying the BRCA1 / 2 mutation is 81.2% according to the model formula, which means they belong to a high-risk genetic group.
[0097] (4) Individualized treatment
[0098] Genetic counseling is recommended, and genetic testing is advised for patients with a BRCA1 / 2 mutation carrier probability exceeding 10%. If subsequent genetic testing is positive, clinicians can provide individualized treatment and family risk management for the client.
[0099] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.
Claims
1. A device for predicting BRCA1 / 2 mutation status in Chinese breast cancer patients, characterized in that, The device is used to perform a method for predicting the probability of BRCA1 / 2 mutation carrier in Chinese breast cancer patients, the prediction method being based on a BRCA1 / 2 mutation carrier probability prediction model for Chinese breast cancer patients. The BRCA1 / 2 mutation carrier probability prediction model for Chinese breast cancer patients is as follows: Logit(P)=β0+β1X1+β2X2+β3X3+β4X4+β5X5 Where: P represents the predicted probability of BRCA1 / 2 mutation carrier in Chinese breast cancer patients, β0 represents the constant of the regression formula, X1, X2, X3, X4, and X5 represent the values of high-risk factors such as age at initial diagnosis of breast cancer, history of bilateral breast cancer, family history of breast cancer and ovarian cancer in first- to third-degree relatives, negative hormone receptor status, and HER2 status, respectively, and β1, β2, β3, β4, and β5 represent the regression coefficients of the corresponding high-risk factors.
2. The device for predicting BRCA1 / 2 mutation status in Chinese breast cancer patients according to claim 1, wherein, The values of β0 range from -2.1 to -2.3, β1 range from -0.04 to -0.05, β2 range from 1.7 to 1.8, β3 range from 1.6 to 1.7, β4 range from 0.65 to 0.75, and β5 range from 1.05 to 1.
15.
3. The device for predicting BRCA1 / 2 mutation status in Chinese breast cancer patients according to claim 2, wherein, The model is as follows: Logit(P)=-2.2431-0.0432X1+1.7548X2+1.6586X3+0.7069X4+1.0972X5.
4. The device for predicting BRCA1 / 2 mutation status in Chinese breast cancer patients according to claim 1, wherein, The values for each high-risk factor were determined as follows: X1 represents the age at initial diagnosis of breast cancer; When a patient has a history of bilateral breast cancer, X2 is 1; when a patient has a history of unilateral breast cancer, X2 is 0. When there is ≥1 family history of breast cancer or ovarian cancer in first- to third-degree relatives, X3 is 1; when there is no family history of breast cancer or ovarian cancer in first- to third-degree relatives, X3 is 0. When the negative hormone receptor status is negative, X4 is 1; when the negative hormone receptor status is positive, X4 is 0; the negative hormone receptors are estrogen receptors and progesterone receptors. When the HER2 status is negative, X5 is 1; when the HER2 status is positive, X5 is 0.
5. The device for predicting BRCA1 / 2 mutation status in Chinese breast cancer patients according to claim 1, wherein, The method for predicting the probability of BRCA1 / 2 mutation carrier status in Chinese breast cancer patients includes the following steps: Obtain data from the test subjects; The data of the subject is input into the model to calculate the BRCA1 / 2 mutation carrier probability of the subject.
6. The device for predicting BRCA1 / 2 mutation status in Chinese breast cancer patients according to claim 1, wherein, The device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the prediction method; or, the device is a nodal chart card based on the model.
7. A method for establishing a BRCA1 / 2 mutation carrier probability prediction model in Chinese breast cancer patients, comprising the following steps: (1) Obtain the BRCA1 / 2 mutation status of multiple Chinese breast cancer patients; (2) Obtain clinicopathological parameters of the multiple Chinese breast cancer patients; (3) Based on the BRCA1 / 2 mutation status obtained in step (1) and the clinicopathological parameters obtained in step (2), logistic regression was used to determine the high-risk factors for the probability of BRCA1 / 2 mutation carrying in Chinese breast cancer patients. The high-risk factors include age at initial diagnosis of breast cancer, history of bilateral breast cancer, family history of breast cancer and ovarian cancer in first- to third-degree relatives, negative hormone receptor status, and HER2 status. (4) Based on the aforementioned high-risk factors, a model was established using logistic regression to predict the probability of BRCA1 / 2 mutation carriage in Chinese breast cancer patients: Logit(P)=β0+β1X1+β2X2+β3X3+β4X4+β5X5 Where: P represents the predicted probability of BRCA1 / 2 mutation carrier in Chinese breast cancer patients, β0 represents the constant of the regression formula, X1, X2, X3, X4, and X5 represent the values of high-risk factors such as age at initial diagnosis of breast cancer, history of bilateral breast cancer, family history of breast cancer and ovarian cancer in first- to third-degree relatives, negative hormone receptor status, and HER2 status, respectively, and β1, β2, β3, β4, and β5 represent the regression coefficients of the corresponding high-risk factors.
8. The method according to claim 7, wherein, The number of Chinese breast cancer patients mentioned in step (1) is 6,000 to 6,500; all of the Chinese breast cancer patients have primary breast cancer and are unrelated by blood; the BRCA1 / 2 mutation status of the Chinese breast cancer patients is obtained using DNA sequencing technology and multiplex ligation probe amplification technology.
9. The method according to claim 7, wherein, The model is as follows: Logit(P)=-2.2431-0.0432X1+1.7548X2+1.6586X3+0.7069X4+1.0972X5; The values for each high-risk factor were determined as follows: X1 represents the age at initial diagnosis of breast cancer; When a patient has a history of bilateral breast cancer, X2 is 1; when a patient has a history of unilateral breast cancer, X2 is 0. When there is ≥1 family history of breast cancer or ovarian cancer in first- to third-degree relatives, X3 is 1; when there is no family history of breast cancer or ovarian cancer in first- to third-degree relatives, X3 is 0. When the negative hormone receptor status is negative, X4 is 1; when the negative hormone receptor status is positive, X4 is 0; the negative hormone receptors are estrogen receptors and progesterone receptors. When the HER2 status is negative, X5 is 1; when the HER2 status is positive, X5 is 0.
10. A prediction model established by the method described in any one of claims 7-9.