Verification bias

when only a proportion of the study group receives confirmation of the diagnosis by the reference standard, or if some patients receive a different reference standard at the time of diagnosis.


Verification bias (sometimes referred to as “work-up bias”) occurs during investigations of diagnostic test accuracy when there is a difference in testing strategy between groups of individuals, leading to differing ways of verifying the disease of interest.

Many reference tests are invasive, expensive, or carry a procedural risk (e.g. angiography, biopsy, surgery), and therefore, patients and clinicians may be less likely to pursue further tests if a preliminary test is negative. This may be either partial verification, where only those with a positive test receive the reference standard, or differential verification, where a different reference test is used depending on whether the index test was positive or negative.


A study assessed the accuracy of D-dimer testing for diagnosing pulmonary embolism (PE). Patients that had a positive D-dimer result were further assessed with ventilation–perfusion scans (reference standard 1), whereas patients that had negative D-dimer results were assessed with routine clinical follow up (reference standard 2). Therefore, patients who had asymptomatic pulmonary embolisms, but negative D-dimer results may not have been diagnosed by routine follow up (symptoms may have resolved in the interim).


An assessment of the effect of biases on diagnostic accuracy studies showed that studies that relied on two or more reference standards to verify the results of the index test reported odds ratios that were on average 60% higher than studies that used a single reference standard.

It is difficult to predict the magnitude and direction of the effect of verification bias on the results as its presence can lead to a test being more or less accurate.  

Studies, where the reference standard was an expensive and/or invasive test, are particularly prone to verification bias. For instance, studies assessing the diagnostic accuracy of faecal occult blood test (FOBT) often only use a confirmatory colonoscopy on those that test positive on FOBT.

Although these designs may have been used for ethical or funding restrictions, they introduce the potential for verification bias. A  meta-analysis comparing the diagnostic accuracy of FOBT for colorectal cancer found that ‘the pooled sensitivity of FOBT without verification bias was significantly lower (.36 vs. 0.70) than those studies with this bias. The pooled specificity of the studies without verification bias was also higher (0.96 vs.0.88). The authors concluded that the test may not be may not be sufficiently sensitive to act as an effective screening test for colorectal cancer.

Preventive steps

Preventive steps

Ideally, in a diagnostic accuracy study, all patients should receive the same reference test.  However, obtaining a reference test in every patient may not be ethical, practical, or cost effective, which can lead to verification bias. One way to reduce verification bias in clinical studies is to perform the reference test in a random sample of study participants. Some statistical methods have been developed to correct for verification bias, but these should be used with caution.


Begg CB, Greenes RA. Assessment of diagnostic tests when disease verification is subject to selection biasBiometrics. 1983  39 (1): 207–215

Cronin AM, Vickers AJ. Statistical methods to correct for verification bias in diagnostic studies are inadequate when there are few false negatives: a simulation study BMC Med Res Methodol. 2008 Nov 11;8:75. doi: 10.1186/1471-2288-8-75.

de Groot JA et al.  Verification problems in diagnostic accuracy studies: consequences and solutions. BMJ. 2011 Aug 2;343:d4770.

de Groot JA et al. Adjusting for partial verification or workup bias in meta-analyses of diagnostic accuracy studies. Am J Epidemiol. 2012 Apr 15;175(8):847-53.

Rosman AS, Korsten MA.Effect of verification bias on the sensitivity of fecal occult blood testing: a meta-analysis.J Gen Intern Med 2010;25:1211–1221.

Rutjes AW et al. Evidence of bias and variation in diagnostic accuracy studies.CMAJ. 2006 Feb 14;174(4):469-67.

Whiting PF et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 2011;155:529-536

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