Analytical Validity, Clinical Validity and Clinical Utility
A plain guide to three questions for any health test: does it measure accurately, does the result mean something, and does acting on it improve health. Based on the ACCE and EGAPP framework.
Content last updated . This page has not been medically reviewed.
Three questions, three different answers
A test can be technically excellent and still be useless to you. Evaluators separate the evidence into links in a chain. The U.S. EGAPP working group, set up to review genetic and other genomic tests, describes the chain as starting with the technical performance of the test (analytic validity), then the strength of the link between the result and the condition (clinical validity), and finally the evidence that results can change patient management and improve net health outcomes (clinical utility). [1] EGAPP adopted aspects of the earlier ACCE model, which uses the same ideas. [1] The framework was built for genomic tests; we use it here as a general way of thinking, which is our own application and not a rule stated by that group.The three links in plain words
| Link | Plain question | Example of a failure |
|---|---|---|
| Analytical validity | Does the test measure what it says, the same way each time? | Different laboratories report very different values for the same sample; see Hair Mineral Analysis |
| Clinical validity | Does the result reliably identify or predict the condition? | An antibody is present in many people with no symptoms; see Food-Sensitivity Panels and IgG Tests |
| Clinical utility | Does acting on the result lead to better health than not testing? | A true abnormality is found, but finding and treating it does not help the person [2] |
Why the chain matters
- Evidence for one link is not evidence for the next. EGAPP notes that direct evidence on a test's overall effectiveness is rarely available, so reviewers build a chain of evidence from the separate links. [1] A company that proves its assay is precise has shown the first link only.
- Accuracy is not benefit. The same logic applies to wearables and home kits. See Device vs Clinical Reference: How Validation Works for devices.
- Clinical validity depends on who is tested. Predictive values change with how common the condition is. In one worked example, a test with a 95% positive predictive value in a 50%-prevalence study sample had a 15% positive predictive value at 1% prevalence, with the same sensitivity and specificity. [3] See False Positives, False Negatives and Test Accuracy.
- A biomarker is not an outcome. Moving a number in a good direction does not prove you feel or live better; see Biomarker Changes vs Meaningful Health Outcomes.
Questions to ask about any test
- What exactly is measured, and in what sample?
- Who validated it, in what kind of people, against what reference method? (analytical and clinical validity)
- What happens to people who are told "abnormal" and act on it, compared with people who are not tested? (utility)
- What could go wrong: false alarms, extra procedures, unnecessary restriction? See Multiple Testing and Overdiagnosis.
- Is the laboratory-developed test reviewed by a regulator? In the US, an FDA final rule that would have added laboratory-made tests to the definition of in vitro diagnostic products was vacated by a federal district court on March 31, 2025, and the FDA reverted the text on September 19, 2025. [4] This is not legal advice; other countries differ and we did not verify them.
Frequently asked questions
What do ACCE and EGAPP mean?
ACCE is an evaluation model covering analytic validity, clinical validity, clinical utility and ethical, legal and social issues; EGAPP is a U.S. working group that adopted aspects of it for genomic tests. [1]
Is a test with high accuracy always useful?
No. Accuracy is the first link only; usefulness requires that results change decisions and improve outcomes. [1]
Does this apply to wearables?
The same questions apply, but device validation has its own vocabulary; see the device validation guide linked above.
Can I judge this myself?
You can ask the questions above. A clinician or pharmacist can help interpret the answers.
More details: evidence, limits and cautions
The details behind this page: cautions, limits of the evidence and where sources disagree. Open any note to read it.
Who should check first
References
- Teutsch SM, et al. The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) initiative: methods of the EGAPP Working Group. Genet Med, 2009. Read 2026-10-22.
- Overdiagnosis and overtreatment; how to deal with too much medicine. J Family Med Prim Care, 2020 (PubMed 33110773). Read 2026-10-22.
- Parikh R, et al. Understanding and using sensitivity, specificity and predictive values. Indian J Ophthalmol, 2008 (PubMed 18158403). Read 2026-10-22.
- US Food and Drug Administration. Laboratory Developed Tests. Read 2026-10-22.