Sample concentration detection method, and establishment and optimization method of standard curve group

Abstract

The invention discloses a sample concentration detection method, a standard curve group establishment method, a matrix specificity standard curve optimization method, a standard curve group establishment device and an immunity analyzer, and belongs to the field of diagnostic analysis. Acquiring matrix information of a to-be-detected sample; selecting a matrix specificity standard curve corresponding to the matrix of the sample to be detected; and detecting the sample and calculating the concentration of the analyte in the sample to be detected by using a matrix specificity standard curve selected from a plurality of standard curve groups of which the specificity corresponds to different matrixes. The corresponding substrate specificity standard curves are configured for various types of substrates in advance, and when a detection task is carried out, the corresponding substrate specificity standard curves can be selected and called, so that the detection is more targeted, the substrate effect caused by using a general standard curve can be avoided, the substrate effect can be reduced, the implementation operation is simpler, and the detection efficiency is improved. And the working time of detection personnel can be remarkably saved, and the detection cost is effectively reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of diagnostic analysis, and specifically relates to a sample concentration detection method, a standard curve group establishment method, a matrix-specific standard curve optimization method and corresponding devices, and an immunoassay analyzer. Background Art

[0002] When using in vitro diagnostic analytical equipment to test biological samples such as blood, urine or saliva, endogenous or exogenous matrices will inhibit or enhance certain reactions, or cause physical or chemical interference. This phenomenon is called matrix effect. The existence of matrix effect will interfere with the accuracy and reliability of diagnostic results.

[0003] At present, in order to reduce the impact of matrix effects, the common methods are as follows: dilute the sample or extract the interfering components; use specially developed specific buffers to reduce the impact of interfering components; optimize the reagent components to reduce the matrix effect caused by the reagent.

[0004] The above methods are complicated to operate, increase the time consumption of diagnostic testing and are high in cost. Summary of the invention

[0005] The purpose of the embodiments of the present invention is to provide a sample concentration detection method, a standard curve group establishment method, a standard curve group optimization method and corresponding devices, as well as an immunoassay analyzer, which can solve the problem that the existing methods for reducing matrix effects are complicated to operate, increase the time consumption of diagnostic testing and are high in cost.

[0006] In a first aspect, an embodiment of the present invention provides a method for detecting sample concentration, the method comprising:

[0007] Obtaining matrix information of the sample to be tested;

[0008] Selecting a matrix-specific standard curve corresponding to the matrix of the sample to be tested;

[0009] Detecting a sample and calculating the concentration of the analyte in the sample using the matrix-specific standard curve;

[0010] Wherein, the matrix-specific standard curve is selected from a group of multiple standard curves specifically corresponding to different matrices.

[0011] In a second aspect, an embodiment of the present invention provides a method for establishing a standard curve group, the method comprising:

[0012] obtaining various specific matrix samples containing known concentrations of analytes, wherein the known concentrations serve as reference concentration values;

[0013] Detecting various specific matrix samples by the target kit and calculating using the universal standard curve of the target kit to obtain the measured concentration value of the corresponding analyte;

[0014] For each of the specific matrix samples, a corresponding first average relative deviation is calculated based on the reference concentration value and the measured concentration value;

[0015] Using each of the first average relative deviations to calibrate the corresponding universal standard curve of the target kit to obtain the matrix-specific standard curve of each of the target kits;

[0016] The matrix-specific standard curve records of each of the target kits are stored as a plurality of standard curve sets.

[0017] In a third aspect, an embodiment of the present invention provides a method for optimizing a matrix-specific standard curve, the method being used to optimize any one of the plurality of standard curves of the first aspect of the present invention, the method comprising:

[0018] By determining whether the corrected relative deviation and the corrected average relative deviation are within a preset deviation range, select to use a correction coefficient or a curve fitting method for optimization.

[0019] In a fourth aspect, an embodiment of the present invention provides a device for establishing a standard curve group, the device comprising:

[0020] An acquisition module, used for acquiring various specific matrix samples containing analytes of known concentrations, wherein the known concentrations are used as reference concentration values;

[0021] A detection module, used to detect various specific matrix samples through a target kit and calculate using a universal standard curve of the target kit to obtain a measured concentration value of a corresponding analyte;

[0022] A calculation module, used for calculating and determining a corresponding first average relative deviation according to the reference concentration value and the measured concentration value for each of the specific matrix samples;

[0023] A calibration module, configured to calibrate the universal standard curve of the corresponding target kit using each of the first average relative deviations to obtain a matrix-specific standard curve of each of the target kits;

[0024] The storage module is used to store the matrix-specific standard curve records of each target kit as a plurality of standard curve groups.

[0025] In a fifth aspect, an embodiment of the present invention provides an immunoassay analyzer comprising a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the programs or instructions are executed by the processor, the steps of the method described in the first aspect, the second aspect or the third aspect are implemented.

[0026] In the sample concentration detection method of the embodiment of the present invention, by pre-configuring corresponding matrix-specific standard curves for various types of matrices, when performing a detection task, the corresponding matrix-specific standard curve can be selected to be called, so that the detection is more targeted, and the matrix effect caused by the use of a universal standard curve can be avoided, which helps to reduce the matrix effect. In addition, compared with traditional dilution, extraction, use of buffer or optimization of reagent components, this detection method is simpler to implement, can significantly save the working time of detection personnel, and effectively reduce detection costs.

[0027] In the method for establishing a standard curve set and the method for optimizing a matrix-specific standard curve in the embodiments of the present invention, by using the average relative deviation of the reference concentration value and the measured concentration value to calibrate the universal standard curve of the comparison kit, a matrix-specific standard curve closer to the quality control product can be obtained, which helps to improve the accuracy of the test results. In addition, by adjusting the correction coefficient or replacing the fitting curve, the test results can be made closer to the concentration value of the quality control product, further improving the consistency of the test results and the sample, and improving the accuracy of the test results. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0029] Figure 1 is a flow chart of a sample concentration detection method according to an embodiment of the present invention;

[0030] Figure 2 It is a flowchart of a method for establishing a standard curve group according to an embodiment of the present invention;

[0031] Figure 3 is the first calibrated standard curve of the embodiment of the present invention;

[0032] Figure 4 It is a flowchart of a method for optimizing a matrix-specific standard curve according to an embodiment of the present invention;

[0033] Figure 5 is a second calibrated standard curve according to an embodiment of the present invention;

[0034] Figure 6 is a third calibrated standard curve according to an embodiment of the present invention;

[0035] Figure 7 is a fourth calibrated standard curve according to an embodiment of the present invention;

[0036] Figure 8 It is a structural block diagram of a device for establishing a standard curve group according to an embodiment of the present invention;

[0037] Fig. 9 It is a structural block diagram of an immunoassay analyzer according to an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present invention.

[0039] The terms "first", "second", etc. in the specification and claims of the present invention are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of the same type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0040] The method and device provided by the embodiments of the present invention are described in detail below through specific embodiments and their application scenarios in conjunction with the accompanying drawings.

[0041] Embodiment 1

[0042] The embodiment of the present invention provides a sample concentration detection method, which is used to detect and analyze components in biological samples. The sample concentration detection method can be applied to diagnostic equipment or a computer terminal connected to the diagnostic equipment. Such in vitro diagnostic equipment can be equipment used for medical diagnosis or testing, including but not limited to: biochemical analyzers, chemiluminescent immunoassay analyzers, fluorescent immunoassay analyzers, immunoturbidimetric analyzers, biochemical and immunological integrated machines, and gene sequencers, etc. Since matrix effects are prevalent in the detection process, and existing measures to reduce matrix effects are relatively costly. Therefore, the sample concentration detection method provided in the embodiment of the present invention can reduce the matrix effect at a relatively low cost. The specific implementation steps are as follows: Figure 1 shown.

[0043] S101, obtaining matrix information of the sample to be tested.

[0044] The matrix of the present invention refers to the components other than the analyte in the sample to be tested. In the embodiment of the present invention, the sample to be tested can be a natural sample such as serum, plasma, whole blood, urine, cerebrospinal fluid, or a sample that has been filtered, freeze-dried, and treated with a stabilizer such as an inter-laboratory quality assessment or a third-party quality control product. These different samples to be tested correspond to different matrices, and there may be a matrix effect between them. For these different samples to be tested, their matrix information can be obtained from the sample supply source.

[0045] S102, selecting a matrix-specific standard curve corresponding to the matrix of the sample to be tested.

[0046] In the detection instrument, corresponding matrix-specific standard curves are pre-configured for various different matrices, forming multiple standard curve groups. When a detection task needs to be performed, the matrix type corresponding to the matrix is ​​selected in the operation interface of the detection instrument according to the matrix type of the sample to be detected, so that the detection instrument can automatically match the corresponding matrix-specific standard curve for the matrix of this type. For example, if the detection sample is serum, the serum-specific standard curve is selected accordingly.

[0047] The matrix-specific standard curve of the present invention is constructed by detecting analytes of known concentrations in a specific matrix on the basis of the universal standard curve. In one embodiment of the present invention, the specific method for establishing the matrix-specific standard curve is as described in Example 2.

[0048] S103, detecting a sample and calculating the concentration of the analyte in the sample using the matrix-specific standard curve, wherein the matrix-specific standard curve is selected from a group of multiple standard curves specifically corresponding to different matrices.

[0049] After a matrix-specific standard curve from a plurality of standard curve groups is selected in the detection instrument, the detection instrument brings the signal value obtained from the detection sample into the matrix-specific standard curve, automatically calculates, and outputs the analyte concentration value in the detection sample.

[0050] Therefore, the sample concentration detection method of the embodiment of the present invention configures corresponding matrix-specific standard curves for various types of matrices in advance. When performing a detection task, the corresponding matrix-specific standard curve can be selected to be called, so that the detection is more targeted, and the matrix effect caused by the use of a universal standard curve can be avoided, which helps to reduce the matrix effect. In addition, compared with traditional dilution, extraction, use of buffer or optimization of reagent components, this detection method is simpler to implement and can significantly save the working time of detection personnel and effectively reduce detection costs.

[0051] Embodiment 2

[0052] In the detection reagent industry, manufacturers provide original universal standard curves for their own target test kits. However, the universal standard curve lacks compatibility with specific matrix types, and the concentration accuracy of the analyte calculated based on the universal standard curve is poor. The embodiment of the present invention provides a method for establishing a standard curve group, which can optimize and correct the universal standard curve to improve the accuracy of the test results. Figure 2 's hint.

[0053] S201, obtaining various specific matrix samples containing analytes of known concentrations, wherein the known concentrations are used as reference concentration values.

[0054] In an embodiment of the present invention, according to the different detection tasks, the project samples used in the detection tasks can be natural samples or quality control products used for inter-laboratory quality assessment. For various specific matrix samples, the known concentration of the analyte can be directly obtained through public channels, and the known concentration is used as the reference concentration value of the subsequent correction link. Taking the quality control products used in inter-laboratory quality assessment as an example, the reference concentration value of the known concentration of the analyte in the project sample can be obtained by querying the instructions of the quality control products or taking the test results of recognized third parties as the standard, that is, the concentration value marked out can be used as a reference comparison. For example, in a detection test, the batch numbers of the quality control products used for inter-laboratory quality assessment are 202211, 202212, 202213, 202214 and 202215, and the reference concentration values ​​of the analytes in each batch number are 1.6ng / mL, 13.6ng / mL, 24.4ng / mL, 7.8ng / mL and 19ng / mL, respectively.

[0055] S202, detecting various specific matrix samples by using the target kit and calculating using the universal standard curve of the target kit to obtain the measured concentration value of the corresponding analyte.

[0056] The target kit of the present invention refers to a finished kit for establishing a matrix-specific standard curve, and the kit is equipped with a universal standard curve when it leaves the factory. The detection reagent of the target kit is used to detect samples to be tested with different concentrations of analytes on an immunoanalyzer. During the process, the analyte reacts with the reagent, and after irradiation with a light source, the immunoanalyzer can measure the luminescent signal value of the analyte, which is the number of photons. The universal standard curve of the target kit is used to calculate the multiple groups of measured concentration values ​​of the analyte for the obtained multiple discrete photon numbers. Exemplarily, for a set of quality control products with the aforementioned batch numbers of 202211, 202212, 202213, 202214 and 202215, the measured concentration values ​​of the analytes in each batch number can be obtained from the universal standard curve of the target kit, which are 2.65ng / mL, 26.15ng / mL, 42.33ng / mL, 13.35ng / mL and 32.18ng / mL, respectively.

[0057] S203: For each of the specific matrix samples, a first average relative deviation is calculated based on the reference concentration value and the measured concentration value.

[0058] For each specific matrix sample, a set of reference concentration values ​​and a corresponding set of measured concentration values ​​can be obtained. The measured concentration values ​​and reference concentration values ​​of the corresponding specific matrix samples are substituted into the relative deviation calculation formula: B = (XT) / T × 100%, where B represents the relative deviation, X represents the measured concentration value obtained from the fitted chemiluminescence standard curve, and T represents the reference concentration value.

[0059] Based on the above step S202, for the inter-laboratory quality control product with batch number 202211, the relative deviation B 1 =(2.65-1.6) / 1.6=65.63%, for the inter-laboratory quality control product with batch number 202212, the relative deviation B 2 =(26.15-13.6) / 13.6=92.28%, for the inter-laboratory quality control product with batch number 202213, the relative deviation B 3 =(42.33-24.4) / 24.4=73.48%, for the inter-laboratory quality control product with batch number 202214, the relative deviation B 4 =(13.35-7.8) / 7.8=71.15%, for the inter-laboratory quality control product with batch number 202215, the relative deviation B 5=(32.18-19) / 19=63.97%. The average value of the above relative deviations is calculated to obtain the first average relative deviation B. ave It is about 74%. It can be seen that after preliminary testing, it was found that the test results of the instrument were greatly affected by the matrix effect, indicating that the average value of the measured concentration value was about 74% higher than the average value of the reference concentration value of the quality control product.

[0060] It is easy to understand that for other specific matrix samples, the corresponding first average relative deviation can also be calculated. The specific process can be referred to step S203, which will not be described in detail in the embodiment of the present invention.

[0061] S204, using each of the first average relative deviations to calibrate the corresponding universal standard curve of the target kit to obtain a matrix-specific standard curve of the target kit.

[0062] The first average relative deviation obtained by the above calculation reflects the error size of the universal standard curve of the target kit, so that the universal standard curve can be correspondingly corrected according to the first average relative deviation.

[0063] Specifically, step S204 may include:

[0064] Step a: taking 1 plus the first average relative deviation as the initial correction coefficient of the standard curve signal value.

[0065] Combined with the calculation formula of step S203, it is easy to understand that when the measured concentration value of each batch of quality control products is greater than the reference concentration value, the average relative deviation is a positive value. When the measured concentration value of each batch of quality control products is less than the reference concentration value, the average relative deviation is a negative value. Therefore, 1 plus the first average relative deviation is used as the initial correction coefficient α of the standard curve signal value, and the signal value of the standard curve is corrected. The correction coefficient α can play a role in compensating and correcting the signal value of the standard curve. Exemplarily, for the aforementioned first average relative deviation B ave When it is about 74%, the correction coefficient α may be 1.7.

[0066] Step b, performing regression fitting on the universal standard curve multiplied by the initial correction coefficient to obtain the matrix-specific standard curve.

[0067] For the universal standard curve used initially, the standard curve signal value is multiplied by the correction coefficient α, and then the chemiluminescence standard curve is regenerated through cubic curve regression fitting. Figure 3 , which is a schematic diagram of the chemiluminescence standard curve regenerated after regression fitting, namely the matrix-specific standard curve of the present invention, in which the horizontal axis X is the concentration value and the vertical axis Y is the corrected signal value.

[0068] Through the matrix-specific standard curve, multiple groups of calibration concentration values ​​of the analyte in each batch can be obtained, which are 1.44 ng / mL, 16.04 ng / mL, 28.76 ng / mL, 8.76 ng / mL and 22.84 ng / mL respectively. Referring to step 203, the calibration average relative deviation of the reference concentration value and the calibration concentration value can be calculated. For the external quality control product of batch number 202211, the relative deviation B 1 =(1.44-1.6) / 1.6=-10%, for the inter-laboratory quality control product with batch number 202212, the relative deviation B 2 =(16.04-13.6) / 13.6=17.94%, for the inter-laboratory quality control product with batch number 202213, the relative deviation B 3 =(28.76-24.4) / 24.4=17.87%, for the inter-laboratory quality control product with batch number 202214, the relative deviation B 4 =(8.76-7.8) / 7.8=12.31%, for the inter-laboratory quality control product of batch number 202215, the relative deviation B 5 =(22.84-19) / 19=20.21%. The average value of the above relative deviations is calculated to obtain the corrected average relative deviation B a ' ve It is approximately 11.67%.

[0069] From the results, it can be seen that the relative deviation between the calibration concentration value and the reference concentration value has been greatly improved compared with that before calibration. The relative deviation after calibration is between -10.00% and 20.21%, and the average deviation is about 11.67%. Therefore, by using the average relative deviation between the reference concentration value and the measured concentration value to calibrate the universal standard curve of the comparison kit, a matrix-specific standard curve closer to the quality control product can be obtained, which helps to improve the accuracy of the test results.

[0070] S205, storing the matrix-specific standard curve records of each target kit as a plurality of standard curve groups.

[0071] The matrix-specific standard curves corresponding to the various specific matrix samples obtained in the aforementioned step S204 can be summarized and organized, associated with the corresponding specific matrix samples, and recorded and stored to form a plurality of standard curve groups. Each matrix-specific standard curve in the standard curve group is a curve corrected by using the corresponding first average relative deviation.

[0072] Therefore, after the plurality of curve groups according to the embodiment of the present invention are configured in the analyzer, the detection operator can select the matrix-specific standard curve corresponding to the matrix sample to output a more accurate detection result.

[0073] Embodiment 3

[0074] Based on the above-mentioned example, the standard curve group has been established, and the present invention can further optimize the matrix-specific standard curve according to the obtained correction concentration value. Figure 4 's hint.

[0075] S301, by determining whether the corrected relative deviation and the corrected average relative deviation are within a preset deviation range, select to use a correction coefficient or a curve fitting method for optimization.

[0076] Specifically, based on the matrix-specific standard curves corresponding to various matrix samples obtained in the aforementioned embodiment 2, the corresponding correction concentration values ​​can be obtained by using the matrix-specific standard curves, and the correction relative deviation and the correction average relative deviation can be further obtained. By measuring whether the correction relative deviation and the correction average relative deviation are appropriate, the correction coefficient or curve fitting method can be further selected to optimize the obtained matrix-specific standard curve again to improve the accuracy of the detection results.

[0077] For example, in one implementation, the above step 301 may include: when the corrected average relative deviation is not within a preset deviation range, selecting to use a correction coefficient for optimization. Specifically, when using the correction coefficient for optimization, the following process may be referred to:

[0078] Step a: re-determine a new correction coefficient according to the difference between the corrected average relative deviation and the preset deviation.

[0079] In the embodiment of the present invention, a preset deviation can be set for the analyzer, and this parameter is used to determine whether the test result meets the accuracy requirement. For example, the preset deviation can be set to ±10%. If the calibration average relative deviation is outside this range, it is considered that a new calibration coefficient needs to be replaced to continue the calibration process.

[0080] Step b, repeatedly using the new correction coefficient to correct the matrix-specific standard curve until the matrix-specific standard curve that meets the preset conditions is stored and recorded.

[0081] When the corrected average relative deviation of the test result obtained after the new correction coefficient corrects the matrix-specific standard curve satisfies the requirement of being less than the preset deviation, the corresponding matrix-specific standard curve can be stored. When the correction process is continued, the two correction coefficients can be re-determined according to the following process to further correct the aforementioned matrix-specific standard curve.

[0082] The first step is to determine a first weight and a second weight according to a difference between the corrected average relative deviation and the preset deviation.

[0083] For example, the corrected average relative deviation B obtained by the above calculation is a ' ve , it can be seen that the corrected mean relative deviation B a ' ve It is 11.67%, the absolute value of the preset deviation is 10%, (11.67%-10%) / 10%=0.167, which is between 0.1 and 0.2. Therefore, two smaller increments of 0.1 and 0.2 are determined as the first weight and the second weight respectively to continue to optimize the aforementioned correction coefficient α.

[0084] In the second step, the correction coefficient α is added to the first weight and the second weight to obtain a new correction coefficient, and then the matrix-specific standard curve is regressed and fitted to calculate the corresponding correction concentration value.

[0085] Add the correction coefficient α obtained above to the first weight 0.1 and the second weight 0.2 respectively, and then the new correction coefficient α can be obtained. 1 , α 2 The matrix-specific standard curve is recalibrated by cubic curve regression fitting, and the optimized matrix-specific standard curve is regenerated until the recalculated average relative deviation is within the preset deviation range, and then the corresponding matrix-specific standard curve is stored and recorded.

[0086] like Figure 5 and Figure 6 The schematic diagram is respectively using the correction coefficient α 1 , α 2 The matrix-specific standard curve is regenerated after regression fitting. For example, for the above-mentioned inter-laboratory quality control products with batch numbers 202211, 202212, 202213, 202214 and 202215, when the correction factor is 1.8, Figure 5 The matrix-specific standard curve can obtain the calibration concentration values ​​of the analyte in each batch as 1.38 ng / mL, 15.3 ng / mL, 27.18 ng / mL, 8.36 ng / mL and 21.73 ng / mL. When the calibration factor is 1.9, Figure 6 The matrix-specific standard curve obtained from the calibration concentration values ​​of the analyte in each batch was 1.32 ng / mL, 14.65 ng / mL, 25.82 ng / mL, 8.00 ng / mL and 20.74 ng / mL, respectively.

[0087] Correspondingly, when the correction factor is 1.8, for the inter-laboratory quality control product with batch number 202211, the relative deviation B 1=(1.38-1.6) / 1.6=-13.75%, for the inter-laboratory quality control product with batch number 202212, the relative deviation B 2 =(15.3-13.6) / 13.6=12.50%, for the inter-laboratory quality control product with batch number 202213, the relative deviation B 3 =(27.18-24.4) / 24.4=11.39%, for the inter-laboratory quality control product with batch number 202214, the relative deviation B 4 =(8.36-7.8) / 7.8=7.18%, for the inter-laboratory quality control product with batch number 202215, the relative deviation B 5 =(21.73-19) / 19=14.37%. The average relative deviation of the above relative deviations is calculated to be about 6.34%. It can be seen that after correction by the correction coefficient 1.8, the relative deviation of each group is maintained between -10.00% and 20.21%, and the average relative deviation is lower than 10%, which is within the preset deviation range.

[0088] When the correction factor is 1.9, for the inter-laboratory quality control product with batch number 202211, the relative deviation B 1 =(1.32-1.6) / 1.6=-17.50%, for the inter-laboratory quality control product with batch number 202212, the relative deviation B 2 =(14.65-13.6) / 13.6=7.72%, for the inter-laboratory quality control product with batch number 202213, the relative deviation B 3 =(25.82-24.4) / 24.4=5.82%, for the inter-laboratory quality control product with batch number 202214, the relative deviation B 4 =(8.00-7.8) / 7.8=2.56%, for the inter-laboratory quality control product of batch number 202215, the relative deviation B 5 =(20.74-19) / 19=9.16%. The average relative deviation of the above relative deviations is calculated to be about 1.55%. It can be seen that after correction by the correction coefficient 1.9, the relative deviation of each group is kept between -10.00% and 20.21%, and the average relative deviation is lower than 5%, closer to 0, and the optimization result is better. At this time, the correction coefficient α can be 2 The corresponding matrix-specific standard curve is stored and recorded.

[0089] Therefore, through the above-mentioned iterative optimization of the correction coefficient, when reducing the matrix effect and improving the accuracy of the test results, compared with traditional dilution, extraction, use of buffer or optimization of reagent components, the implementation operation is simpler, which can significantly save the working time of the test personnel and effectively reduce the test cost.

[0090] Exemplarily, in another embodiment, the above step 301 may also include: when the corrected average relative deviation is within the preset deviation range, but at least one corrected relative deviation is not within the preset deviation range, selecting to use a curve fitting method for optimization. That is, when calculating the corrected average relative deviation, if a certain group of corrected relative deviations is large, the matrix-specific standard curve may be further optimized using a curve fitting method. For example, taking the result when the correction coefficient is 1.9 as an example, the relative deviations of the quality control products of each batch number are B 1 =-17.50%, B 2 = =7.72%, B 3 =5.82%, B 4 =2.56%, B 5 =9.16%. After correction by a correction factor of 1.9, the relative deviation of each group remained between -10.00% and 20.21%, and the average relative deviation was lower than 5%, closer to 0, and the correction result was more excellent. However, it was found that after correction by a correction factor of 1.9, for the inter-laboratory quality control product with batch number 202211, the correction concentration value was -17.5%, which exceeded the preset deviation of ±10%. At this time, a new curve fitting method can be further replaced to fit a new matrix-specific standard curve.

[0091] Specifically, when using curve fitting for optimization, the following process can be referred to:

[0092] The correction concentration value is calculated by using the matrix-specific standard curve obtained in the above-mentioned Example 2, and a new curve fitting method is replaced according to the difference between the correction relative deviation and the preset deviation. The matrix-specific standard curve is repeatedly regressed and fitted to optimize the matrix-specific standard curve by using different new curve fitting methods until a matrix-specific standard curve that meets the preset conditions is stored and recorded.

[0093] For example, the regression curve is changed from a cubic curve to a four-parameter curve, and refitted to generate Figure 7 A new matrix-specific standard curve is shown, and the correction concentration values ​​are obtained from the curve graph and the relative deviation is recalculated.

[0094] For the aforementioned quality control products with batch numbers 202211, 202212, 202213, 202214 and 202215, Figure 7 The matrix-specific standard curve obtained from the calibration concentration values ​​of the analyte in each batch was 1.66 ng / mL, 14.15 ng / mL, 26.15 ng / mL, 7.82 ng / mL and 20.56 ng / mL, respectively.

[0095] For the external quality control product of batch number 202211, the relative deviation B 1=(1.66-1.6) / 1.6=3.75%, for the inter-laboratory quality control product with batch number 202212, the relative deviation B 2 =(14.15-13.6) / 13.6=4.04%, for the inter-laboratory quality control product with batch number 202213, the relative deviation B 3 =(26.15-24.4) / 24.4=7.17%, for the inter-laboratory quality control product with batch number 202214, the relative deviation B 4 =(7.82-7.8) / 7.8=0.26%, for the inter-laboratory quality control product of batch number 202215, the relative deviation B 5 =(20.56-19) / 19=8.21%. The average relative deviation of the above relative deviations is about 4.69%. It can be seen that by changing the cubic curve to a four-parameter curve, the recalculated results show that the relative deviation of each group is kept within ±10.00%, and the average relative deviation is lower than 5%, closer to 0, and the calibration result is more excellent. At this time, Figure 7 The corresponding matrix-specific standard curve is stored and recorded for use in actual detection tasks.

[0096] Embodiment 4

[0097] The method for establishing a standard curve group provided by the above-mentioned embodiment of the present invention can be performed by a device for establishing a standard curve group. In the embodiment of the present invention, the device for establishing a standard curve group performs the method for establishing a standard curve group as an example to illustrate the device for establishing a standard curve group provided by the embodiment of the present invention.

[0098] Reference Figure 8 , shows a structural block diagram of a device for establishing a standard curve group according to an embodiment of the present invention, the device comprising:

[0099] An acquisition module 401 is used to acquire various specific matrix samples containing analytes of known concentrations, wherein the known concentrations are used as reference concentration values;

[0100] A detection module 402 is used to detect various specific matrix samples through a target kit and calculate using a universal standard curve of the target kit to obtain a measured concentration value of a corresponding analyte;

[0101] A calculation module 403 is used to calculate and determine a corresponding first average relative deviation for each of the specific matrix samples according to the reference concentration value and the measured concentration value;

[0102] A correction module 404 is used to correct the universal standard curve of the corresponding target kit using each of the first average relative deviations to obtain a matrix-specific standard curve of each of the target kits;

[0103] The storage module 405 is used to store the matrix-specific standard curve records of each target kit as a plurality of standard curve groups.

[0104] Therefore, the standard curve group establishment device can obtain a matrix-specific standard curve that is closer to the quality control product by correcting the universal standard curve of the target kit using the average relative deviation of the reference concentration value and the measured concentration value, which helps to improve the accuracy of the test results.

[0105] like Fig. 9 As shown, an embodiment of the present invention further provides an immunoanalyzer 20, including a processor 201 and a memory 202, wherein the memory 202 stores a program or instruction that can be executed on the processor 201, and when the program or instruction is executed by the processor 201, each step of the sample concentration detection method embodiment, the standard curve group establishment method embodiment or the matrix-specific standard curve optimization method embodiment can be implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0106] It should be noted that the immunoassay analyzer in the embodiment of the present invention includes any one of the aforementioned biochemical analyzer, chemiluminescent immunoassay analyzer, fluorescent immunoassay analyzer, immunoturbidimetric analyzer, biochemical immunoassay integrated machine and gene sequencer.

[0107] It should be noted that, in this article, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the method and device in the embodiment of the present invention is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0108] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal (which can be a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0109] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation modes, which are merely illustrative rather than restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, all of which are within the protection of the present invention.

Claims

1. A method for detecting sample concentration, It is characterized in that The method comprises: Obtaining matrix information of the sample to be tested; Selecting a matrix-specific standard curve corresponding to the matrix of the sample to be tested; Detecting a sample and calculating the concentration of the analyte in the sample to be detected using the matrix-specific standard curve; Wherein, the matrix-specific standard curve is selected from a group of multiple standard curves specifically corresponding to different matrices.

2. A method for establishing a standard curve set, It is characterized in that The method comprises: obtaining various specific matrix samples containing known concentrations of analytes, wherein the known concentrations serve as reference concentration values; Detecting various specific matrix samples by the target kit and calculating using the universal standard curve of the target kit to obtain the measured concentration value of the corresponding analyte; For each of the specific matrix samples, a corresponding first average relative deviation is calculated based on the reference concentration value and the measured concentration value; Using each of the first average relative deviations to calibrate the corresponding universal standard curve of the target kit to obtain the matrix-specific standard curve of each of the target kits; The matrix-specific standard curve records of each of the target kits are stored as a plurality of standard curve sets.

3. The method according to claim 2, It is characterized in that The method of using each of the first average relative deviations to correct the corresponding universal standard curve of the target kit to obtain the matrix-specific standard curve of each of the target kits comprises: Using 1 plus the first average relative deviation as an initial correction coefficient for the standard curve signal value; The universal standard curve multiplied by the initial calibration factor was regressed to obtain the matrix-specific standard curve.

4. A method for optimizing matrix-specific standard curves, It is characterized in that The method is used to optimize any matrix-specific standard curve in the plurality of standard curve sets of claim 2 or 3, and the method comprises: By determining whether the corrected relative deviation and the corrected average relative deviation are within a preset deviation range, select to use a correction coefficient or a curve fitting method for optimization.

5. The method according to claim 4, It is characterized in that The method of determining whether the corrected relative deviation and the corrected average relative deviation are within a preset deviation range and selecting to use a correction coefficient or a curve fitting method for optimization includes: When the corrected average relative deviation is not within the preset deviation range, the correction coefficient is selected for optimization.

6. The method according to claim 4, It is characterized in that The method comprises: Calculating a correction concentration value using the matrix-specific standard curve according to any one of claims 2 to 3, and calculating the correction average relative deviation between the correction concentration value and the reference concentration value; Re-determining a new correction coefficient according to the difference between the corrected average relative deviation and the preset deviation; The matrix-specific standard curve is repeatedly corrected using the new correction coefficient until the matrix-specific standard curve that meets the preset conditions is stored and recorded.

7. The method according to claim 4, It is characterized in that The method of determining whether the corrected relative deviation and the corrected average relative deviation are within a preset deviation range and selecting to use a correction coefficient or a curve fitting method for optimization includes: When the corrected average relative deviation is within the preset deviation range, but at least one corrected relative deviation is not within the preset deviation range, a curve fitting method is selected for optimization.

8. The method according to claim 4, It is characterized in that The method comprises: The correction concentration value is calculated by the matrix-specific standard curve according to any one of claims 2 to 3, and a new curve fitting method is replaced to fit the new matrix-specific standard curve; The matrix-specific standard curve is repeatedly corrected using a new curve fitting method until a matrix-specific standard curve that meets the preset conditions is stored and recorded.

9. A device for establishing a standard curve set, It is characterized in that The device comprises: An acquisition module, used for acquiring various specific matrix samples containing analytes of known concentrations, wherein the known concentrations are used as reference concentration values; A detection module, used to detect various specific matrix samples through a target kit and calculate using a universal standard curve of the target kit to obtain a measured concentration value of a corresponding analyte; A calculation module, used for calculating and determining a corresponding first average relative deviation according to the reference concentration value and the measured concentration value for each of the specific matrix samples; A calibration module, configured to calibrate the universal standard curve of the corresponding target kit using each of the first average relative deviations to obtain a matrix-specific standard curve of each of the target kits; The storage module is used to store the matrix-specific standard curve records of each target kit as a plurality of standard curve groups.

10. An immunoassay analyzer, It is characterized in that The method comprises a processor and a memory, wherein the memory stores a program or instruction that can be run on the processor, and when the program or instruction is executed by the processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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