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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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