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Keywords
(6)
Diagnostic Test
Predictive Value of Tests
Randomized Trial
Risk Assessment
Screening Test
Sensitivity and Specificity
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Does Prevalence Matter to Physicians in Estimating Posttest Probability of Disease? A Randomized Trial
Does Prevalence Matter to Physicians in Estimating Posttest Probability of Disease? A Randomized Trial,10.1007/s1160601015405,Journal of General In
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Does Prevalence Matter to Physicians in Estimating Posttest Probability of Disease? A Randomized Trial
(
Citations: 2
)
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Thomas Agoritsas
,
Delphine S. Courvoisier
,
Christophe Combescure
,
Marie Deom
,
Thomas V. Perneger
BACKGROUND The probability of a disease following a
diagnostic test
depends on the
sensitivity and specificity
of the test, but also on the prevalence of the disease in the population of interest (or pretest probability). How physicians use this information is not well known. OBJECTIVE To assess whether physicians correctly estimate posttest probability according to various levels of prevalence and explore this skill across respondent groups. DESIGN Randomized trial. PARTICIPANTS Populationbased sample of 1,361 physicians of all clinical specialties. INTERVENTION We described a scenario of a highly accurate
screening test
(sensitivity 99% and specificity 99%) in which we randomly manipulated the prevalence of the disease (1%, 2%, 10%, 25%, 95%, or no information). MAIN MEASURES We asked physicians to estimate the probability of disease following a positive test (categorized as <60%, 60–79%, 80–94%, 95–99.9%, and >99.9%). Each answer was correct for a different version of the scenario, and no answer was possible in the “no information” scenario. We estimated the proportion of physicians proficient in assessing posttest probability as the proportion of correct answers beyond the distribution of answers attributable to guessing. KEY RESULTS Most respondents in each of the six groups (67%–82%) selected a posttest probability of 95–99.9%, regardless of the prevalence of disease and even when no information on prevalence was provided. This answer was correct only for a prevalence of 25%. We estimated that 9.1% (95% CI 6.0–14.0) of respondents knew how to assess correctly the posttest probability. This proportion did not vary with clinical experience or practice setting. CONCLUSIONS Most physicians do not take into account the prevalence of disease when interpreting a positive test result. This may cause unnecessary testing and diagnostic errors.
Journal:
Journal of General Internal Medicine  J GEN INTERN MED
, vol. 26, no. 4, pp. 373378, 2011
DOI:
10.1007/s1160601015405
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Citations
(2)
Posttest Probability According to Prevalence
Thomas Agoritsas
,
Delphine S. Courvoisier
,
Christophe Combescure
,
Marie Deom
,
Thomas V. Perneger
Journal:
Journal of General Internal Medicine  J GEN INTERN MED
, pp. 11
Doctors and Patients’ Susceptibility to Framing Bias: A Randomized Trial
Thomas V. Perneger
,
Thomas Agoritsas
Journal:
Journal of General Internal Medicine  J GEN INTERN MED
, pp. 17