Quality Standards

Now that there are new measurement uncertainty goals, it's time to check if any instruments can hit them. Using the performance data from a recent study of the Vitros 5600 and Vitros 250 instruments from an Indian laboratory, we assess the acceptability of the mu of their methods.

A majority of performance on a Vitros 5600 and a Vitros 250 in India cannot hit desirable measurement uncertainty goals

Sten Westgard, MS
February 2025

A recent study in the looked at a laboratory in Montpellier, France at the performance of the Roche cobas 8000 series. They used a heterogenous mix of performance specifications, as well as a leading approach to risk-management (using Sigma metrics to inform the risk priority number RPN):

Comparison of Analytical Performance of Dry Chemistry Analysers Vitros 5600 and Vitros 250: A Cross-sectional study. ER Sindhu, E Zacharias, KS Mini, T Bindu, P Faizal, TA Ajith. National Journal of Laboratory Medicine. 2025 Jan, Vol-14(1): BO01-BO06. doi:10.7860/njlm/2025/67956.2890

The imprecision information comes from BioRad controls run daily during July 2022 to October 22 (4 months). 6 months is more preferable,  but this is not a short term look at precision. While the study evaluated the precision and the comparison between the two instruments, we're going to use the imprecision collected and compare it against the new goals for measurement uncertainty.

The short answer: 15 out of 28 levels on 14 assays on the Vitros 5600 - just over half - cannot meet desirable uncertainty goals. 8 out of 28 measures cannot meet the minimum uncertainty goals. The EFLM biological-variation-derived minimum CVs are far more forgiving: only 3 of 28 measurements cannot meet those goals.

The short answer: 18 out of 28 levels on 14 assays on the Vitros 350 - just over 60% of the measurements - cannot meet desirable uncertainty goals. 11 out of 28 measures cannot meet the minimum uncertainty goals. The EFLM biological-variation-derived minimum CVs are far more forgiving: only 7 of 28 measurements cannot meet those goals.

Of course, this is not taking into account any bias that might be present. There were statistically significant differences between most of the analytes. If those biases were to be included in the measurement uncertainty, even if we pretend the bias is merely an additional variance, even fewer analytes would pass.

There may be reasons why so many analytes failed to meet measurement uncertainty specifications. BioRad controls might not be fully commutable, plagued by matrix effects. The lab itself might be operating poorly, or may not be fully competent in the preparation or aliquotting of the controls.

There is a small chance that if the uncertainty of calibration and reference were smaller than the 50% of the u:result budget traditionally allocated to them, more variance can be tolerated at the u:rw level. The study didn't include those numbers, and it's rare to see any study take those into account or report them.

As other examples have already shown, what's far more likely is that the new mu goals are too demanding, unrealistically so, and their widespread application will result in unproductive stress and strife in laboratories around the world. The most probable outcome is that these new mu goals will simply be ignored by most laboratories, much as most labs already ignore the bulk of the measurement uncertainty approach.