[Methods for mathematical data processing in enzyme immunoassay. I. Theoretical bases].

Area of Science:

• Biochemistry
• Clinical Chemistry
• Laboratory Medicine

Background:

• Enzyme immunoassay (EIA) is a widely used diagnostic technique.
• Accurate mathematical processing of EIA data is essential for reliable clinical results.
• Variations in data processing methods can impact diagnostic outcomes.

Purpose of the Study:

• To provide guidelines for selecting appropriate mathematical methods for EIA data analysis.
• To compare different methods of standard curve construction and concentration calculation in EIA.
• To evaluate the impact of data processing choices on clinical diagnostic accuracy.

Main Methods:

• Comparative analysis of experimental data presentation and standard curve construction techniques.
• Evaluation of commonly used photometric equipment and software in Russian clinical laboratories for EIA.
• Simulation of competitive analysis to assess the influence of standard graph modes on results.

Main Results:

• The choice of standard graph construction significantly affects the calculated concentration of test agents.
• Incorrect data processing can lead to erroneous calculations in control serum, causing false rejections.
• Inaccurate calculations near decision points in patient samples can result in underdiagnosis.

Conclusions:

• Mathematical processing of EIA data requires careful selection of methods to ensure accuracy.
• Inappropriate data analysis in EIA can compromise diagnostic reliability and patient care.
• Standardized guidelines for EIA data processing are needed to improve clinical laboratory performance.