[Improvement of quantitative method on anti-HBs]

Area of Science:

• Clinical Chemistry
• Immunology
• Radioimmunoassay (RIA)

Background:

• Accurate quantification of anti-HBs is crucial for assessing immunity and guiding vaccination strategies.
• Evaluating different curve fitting models is essential for optimizing RIA methods.

Purpose of the Study:

• To determine the most suitable quantitative method for anti-HBs concentration detection in a laboratory setting.
• To compare the accuracy of log-log and exponential curve models for RIA data analysis.

Main Methods:

• Radioimmunoassay (RIA) was used to detect anti-HBs standard preparations across various concentrations.
• Log-log and exponential curve models were employed to fit the RIA data.
• The fitting efficiency and accuracy of both models were compared using reference samples.

Main Results:

• The exponential curve model demonstrated superior fitting efficiency, with a low error mean square (1.2971) and a high determinate coefficient (0.9904).
• Calculated concentrations using the exponential model were closer to the actual concentration (30.0 mIU/mL), with an average deviation of 6.37%.

Conclusions:

• The exponential curve model is a more practical and accurate method for estimating anti-HBs concentration in serum samples.
• This optimized RIA approach can serve as an optimal quantitative method for anti-HBs detection.