Comparer des méthodes

	Évaluation bayésienne des tests de dépistage	Évaluation des tests et programmes de dépistage
Domaine	Épidémiologie	Épidémiologie
Famille	Process / pipeline	Process / pipeline
Année d'origine	1763 (theorem); clinical screening application formalized ~1959–1970s	1968 (Wilson-Jungner principles); statistical framework developed 1970s–2000s
Auteur d'origine	Thomas Bayes (theorem, 1763); applied to clinical screening by Ledley & Lusted (1959)	Wilson & Jungner (WHO criteria, 1968); foundational work by Pepe, Altman, and others in statistical test evaluation
Type	Bayesian analytical framework for test evaluation	Observational diagnostic / epidemiological evaluation design
Source fondatrice	Fletcher, R. H., Fletcher, S. W., & Fletcher, G. S. (2014). Clinical Epidemiology: The Essentials (5th ed.). Lippincott Williams & Wilkins. ISBN: 978-1451144475	Wilson, J. M. G., & Jungner, G. (1968). Principles and Practice of Screening for Disease. World Health Organization. Public Health Papers No. 34.
Alias	Bayesian diagnostic test evaluation, Bayesian predictive value analysis, posterior predictive value approach, Bayes theorem screening	screening study, screening performance evaluation, screening accuracy assessment, STE
Apparentées	6	6
Résumé	Bayesian screening test evaluation applies Bayes' theorem to quantify how a screening test result changes the probability that an individual truly has a disease. Rather than reporting sensitivity and specificity in isolation, the approach centres on predictive values — the probability of disease given a positive or negative test — which depend critically on disease prevalence in the population being screened. The framework allows systematic updating of pre-test probability to post-test probability and supports decision-making under uncertainty.	Screening test evaluation is a systematic epidemiological approach for assessing whether a test or program can accurately and cost-effectively identify individuals with a condition before symptoms appear. It quantifies diagnostic performance metrics — sensitivity, specificity, predictive values, and the ROC curve — and evaluates whether a screening program meets established public health criteria for adoption and harm-benefit balance.