Limitations of sensitivity, specificity, likelihood ratio, and bayes' theorem in assessing diagnostic probabilities: a clinical example - PubMed (original) (raw)
Review
Limitations of sensitivity, specificity, likelihood ratio, and bayes' theorem in assessing diagnostic probabilities: a clinical example
K G Moons et al. Epidemiology. 1997 Jan.
Abstract
We evaluated the extent to which the sensitivity, specificity, and likelihood ratio of the exercise test to diagnose coronary artery disease vary across subgroups of a certain patient population. Among 295 patients suspected of coronary artery disease, as independently determined by coronary angiography, we assessed variation in sensitivity and specificity according to patient history, physical examination, exercise test results, and disease severity in 207 patients with and 88 patients without coronary artery disease, respectively. The sensitivity varied substantially according to sex (women 30% and men 64%), systolic blood pressure at baseline (53% to 65%), expected workload (50% to 64%), systolic blood pressure at peak exercise (50% to 67%), relative workload (33% to 68%), and number of diseased vessels (39% to 77%). The specificity varied across subgroups of sex (men 89% and women 97%) and relative workload (85% to 98%). The likelihood ratio varied (3.8 to 17.0) across the same patient subgroups, as did the sensitivity. As each population tends to be heterogeneous with respect to patient characteristics, no single level of these parameters can be given that is adequate for all subgroups. Use of these parameters as a basis for calculating diagnostic probabilities in individual patients using Bayes' theorem has serious limitations.
Comment in
- No burial for Bayes' rule.
Bossuyt PM. Bossuyt PM. Epidemiology. 1997 Jan;8(1):4-5. Epidemiology. 1997. PMID: 9116093 No abstract available.
Similar articles
- Critical analysis of the application of Bayes' theorem to sequential testing in the noninvasive diagnosis of coronary artery disease.
Weintraub WS, Madeira SW Jr, Bodenheimer MM, Seelaus PA, Katz RI, Feldman MS, Agarwal JB, Banka VS, Helfant RH. Weintraub WS, et al. Am J Cardiol. 1984 Jul 1;54(1):43-9. doi: 10.1016/0002-9149(84)90301-1. Am J Cardiol. 1984. PMID: 6741837 - Bayes' theorem--a review.
Schulman P. Schulman P. Cardiol Clin. 1984 Aug;2(3):319-28. Cardiol Clin. 1984. PMID: 6399868 Review. - The determination of the post-test likelihood for coronary disease using Bayes Theorem.
Santinga JT, Flora J, Maple R, Brymer JF, Pitt B. Santinga JT, et al. J Electrocardiol. 1982 Jan;15(1):61-8. doi: 10.1016/s0022-0736(82)80046-0. J Electrocardiol. 1982. PMID: 7069319 - Bayesian probability analysis: a prospective demonstration of its clinical utility in diagnosing coronary disease.
Detrano R, Yiannikas J, Salcedo EE, Rincon G, Go RT, Williams G, Leatherman J. Detrano R, et al. Circulation. 1984 Mar;69(3):541-7. doi: 10.1161/01.cir.69.3.541. Circulation. 1984. PMID: 6692516
Cited by
- Integrating economic considerations into cutpoint selection may help align clinical decision support toward value-based healthcare.
Parsons R, Blythe R, Cramb SM, McPhail SM. Parsons R, et al. J Am Med Inform Assoc. 2023 May 19;30(6):1103-1113. doi: 10.1093/jamia/ocad042. J Am Med Inform Assoc. 2023. PMID: 36970849 Free PMC article. - Naming ability assessment in neurocognitive disorders: a clinician's perspective.
Georgiou EE, Prapiadou S, Thomopoulos V, Skondra M, Charalampopoulou M, Pachi A, Anagnostopoulou Α, Vorvolakos T, Perneczky R, Politis A, Alexopoulos P. Georgiou EE, et al. BMC Psychiatry. 2022 Dec 30;22(1):837. doi: 10.1186/s12888-022-04486-x. BMC Psychiatry. 2022. PMID: 36585667 Free PMC article. - Designing a Novel Clinician Decision Support Tool for the Management of Acute Diarrhea in Bangladesh: Formative Qualitative Study.
Rosen RK, Garbern SC, Gainey M, Lantini R, Nasrin S, Nelson EJ, Elshabassi N, Alam NH, Sultana S, Hasnin T, Qu K, Schmid CH, Levine AC. Rosen RK, et al. JMIR Hum Factors. 2022 Mar 25;9(1):e33325. doi: 10.2196/33325. JMIR Hum Factors. 2022. PMID: 35333190 Free PMC article. - Bayesian updating and sequential testing: overcoming inferential limitations of screening tests.
Balayla J. Balayla J. BMC Med Inform Decis Mak. 2022 Jan 6;22(1):6. doi: 10.1186/s12911-021-01738-w. BMC Med Inform Decis Mak. 2022. PMID: 34991576 Free PMC article.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
Research Materials