It’s time to improve assay specifications

Some of my critiques go back almost 20 years.

These standards have one or more of the following problems:

  • Limits are given for only 95% of the data, so 5% of the data are unspecified
  • The wrong model is used (often total error = bias ± 1.96 X imprecision)
  • Outliers are discarded
  • User error is excluded

The ideal specification should have:

  • Limits for 100% of the data, as exemplified by an error grid
  • A protocol for collecting method comparison data. The protocol should not exclude user error
  • An analysis method, whereby no data is thrown out. The analysis could be as simple as tallying the percentage of data in each error grid zone
  • FMEA and fault tree analysis to evaluate the risk of rare errors


  1. Krouwer JS. Problems with the NCEP (National Cholesterol Education Program) Recommendations for Cholesterol Analytical Performance. Arch Pathol Lab Med 2003;127: 1249 (2003).
  2. Krouwer JS and Cembrowski GS. A review of standards and statistics used to describe blood glucose monitor performance. Journal of Diabetes Science and Technology 2010;4:75-83.
  3. Jan S. Krouwer: A recommended improvement for specifying and estimating serum creatinine performance. Clin Chem 2007;53:1715-1716.
  4. See:

Appendix – Disagreeing with so many experts

Each of the standard organizations comprises a group of experts and four groups equals a lot of experts! I know people in these groups and respect their expertise. These experts are much more knowledgeable than I am in the clinical chemistry of each analyte. However, another domain of interest is how to specify and measure the quality of these assays. I suspect that these groups are underrepresented in this area.


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