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How is biological variation used to set analytical performance specifications?
A biological variation–based specification uses information about how a measurand varies in people to judge how much analytical variation is acceptable. For imprecision, a common starting point is to set an analytical CV target as a fraction of within-person biological variation.
Worked example at a glance
6.0%
Fictional within-person CV
3.0%
Desirable analytical CV target
2.5%
Observed analytical CV
Understand what is varying
Even when a person is in a stable state, their measurand can vary from one sample to the next. Within-person biological variation, often expressed as CVI, describes that variation relative to the person’s level. Between-person biological variation describes differences between people. Analytical imprecision contributes a separate source of variation to the observed laboratory results. [1] [2]
The reasoning behind a biological variation–based imprecision target is that analytical scatter should be small relative to the within-person variation it accompanies. That can be useful for measurands where biological variation is a sensible basis for the use being considered. An estimate taken from a different specimen type, population or sampling interval may describe a different situation. [1] [2]
Turn one estimate into an imprecision target
Suppose a relevant and credible within-person CV estimate for a fictional measurand is 6.0%. The conventional desirable imprecision target is analytical CV no greater than half CVI. In this example, 0.5 × 6.0% gives a target of 3.0%. The factor is part of the specification model. It does not come from the laboratory’s own precision study. [2] [3]

Now compare the target with a within-laboratory analytical CV estimate of 2.5% at a relevant concentration. The point estimate is below the 3.0% target. A laboratory assessing a real method would check whether the analytical study represents the procedure and intended conditions, and how precisely the CV was estimated.
Check the evidence before adopting the target
Look up the measurand in a curated source such as the EFLM Biological Variation Database. Check the specimen, population, sampling interval and quality of the evidence behind the estimate. Ask whether the clinical use relies on the kind of variation the estimate describes. Biological variation estimates also have uncertainty, so note the source and what would make you revisit the choice. [1] [2]
| Quantity | Value and role |
|---|---|
| Within-person CV | 6.0% · biological variation estimate |
| Desirable target | 3.0% · half the within-person CV |
| Observed CV | 2.5% · estimated under the study conditions |
The same proportion can have different consequences if you use a different CVI. If the relevant estimate were 4.0% rather than 6.0%, the same convention would give 2.0% rather than 3.0%. The laboratory’s observed 2.5% would then sit on the other side of the target. The choice of evidence matters alongside the calculation.
Check whether the target applies to the same form of imprecision you measured. A short repeatability study and a study across routine days can yield different CVs because they cover different sources of variation. Record the concentration and study conditions alongside the observed CV so a reviewer can judge the comparison.
Keep imprecision and bias separate
This calculation sets an imprecision target. Biological variation can also be used to derive a specification for bias, but that addresses systematic difference and uses different inputs in conventional models. State which performance characteristic the target applies to. For a decision tied to a particular clinical threshold, consider whether an outcome-based approach would be more informative. [1] [2]
Example wordingUsing an illustrative within-person CV of 6.0% and the conventional desirable factor of 0.5 gives an analytical imprecision target of 3.0% CV. The observed within-laboratory CV of 2.5% is below this target at the concentration and under the conditions studied.
Member Learning
Practise interpreting a proposed specification
Understanding analytical performance specifications (APS) helps you check the evidence behind a proposed specification and explain whether it is suitable.
Sources and related reading
- Sandberg et al. · EFLM Milan consensus on analytical performance specifications · The three models and the distinction between direct and indirect outcome evidence.
- EFLM Biological Variation Database · Curated estimates and analytical performance specifications derived from biological variation.
- Fraser · Analytical goals for haematology tests · Explains the conventional desirable imprecision criterion of half the within-person variation.
Read what makes a specification fit for purpose · Read how routine laboratory data describe measurement imprecision
By Stephen MacDonald · Suggest a correction · Back to Find a guide