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Computer Simulation in Medical Diagnostic Assay Calibration Evaluation

Computer Simulation in Medical Diagnostic Assay Calibration Evaluation . Ping Shi Ph.D Abbott Laboratories Sept. 16, 2005. Contents. Background of Calibration Calibration Evaluation Computer Simulation Comments. What is Calibration?. Definition (ANSI/NCSL,1994)

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Computer Simulation in Medical Diagnostic Assay Calibration Evaluation

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  1. Computer Simulation in Medical Diagnostic Assay Calibration Evaluation Ping Shi Ph.D Abbott Laboratories Sept. 16, 2005

  2. Contents • Background of Calibration • Calibration Evaluation • Computer Simulation • Comments

  3. What is Calibration? • Definition (ANSI/NCSL,1994) The set of operations which establish, under specified conditions, the relationship between values indicated by a measuring instrument or measuring system, and the corresponding standard or known values derived from the standard.

  4. Calibration Process • Reference standard with known values (calibrators) to cover the range of interest.

  5. Calibration Process • Measurements on the calibrators with the instrument/reagent lot to be calibrated.

  6. Calibration Process • Mathematical function relationship between the measured responses and the known values of the reference standards, called a Calibration Curve.

  7. Calibration Process • Translation of the measurements of samples to the values of interest by the inverse of the calibration curve.

  8. Calibration Curves

  9. Calibration Determination • Calibrator values • Model and weight in calibration curve fitting • Number of replicate at each calibrator level • Stored calibration curve use

  10. Evaluation of Calibration • Accuracy - Bias • Precision - Variance Components (of calibration, and more important, of instrument, reagent lot, run, etc.) • Sensitivity • Specificity

  11. Problems • Very limited calibration curves available due to: • Instrument capacity • Testing material limitation • Time limitation • Manpower/Laboratory availability

  12. Simulation Approach • Build mean and SD profiles • Simulate calibration curves based on the profiles • Evaluate and select calibration methods

  13. Mean and SD Profiles • Run multiple replicates at each of several samples with known values across assay dynamical region.

  14. Mean and SD Profiles • Build mean and SD profiles of response variable over the region based on the test results.

  15. Calibration Curve Simulation • Simulate a sample mean at each of six calibrator concentration levels based on the profiles • sample_mean= mean+SD/sqrt(n)*random(seed)

  16. Calibration Curve Simulation • Fit the calibration curve • Replicate the process to get multiple simulated calibration curves

  17. Calibration Method Evaluation • Evaluate bias, precision, sensitivity and specificity for each calibration method.

  18. Comments • The same approach applies to other calibration methods such as the ones used in qualitative assays. • When evaluating calibration curves, different criteria might be used in different region due to clinical importance.

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