השוואת שיטות

	הערכת מבחן סינון מותאם	תכנון מחקר דיאגנוסטי
תחום	אפידמיולוגיה	מחקר קליני
משפחה	Process / pipeline	Process / pipeline
שנת המקור	1980s–2000s (formalized alongside diagnostic accuracy methodology)	2003-2015
הוגה השיטה	Methodological synthesis from matched case-control and diagnostic accuracy traditions (Pepe, Zhou, and others)	Bossuyt, Reitsma, and STARD group (2003); clinical epidemiology pioneers
סוג	Observational diagnostic study with matched design	Research Design
מקור מכונן	Pepe, M. S. (2003). The Statistical Evaluation of Medical Tests for Classification and Prediction. Oxford University Press. ISBN: 978-0198509844	Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L. M., ... & de Vet, H. C. (2003). Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative. Annals of Internal Medicine, 138(1), 40–44.
כינויים	matched diagnostic accuracy study, paired screening evaluation, matched-pair test performance study, matched screening assessment	diagnostic accuracy study, test accuracy, STARD, diagnostic evaluation
קשורות	6	2
תקציר	Matched screening test evaluation assesses the sensitivity, specificity, and predictive values of a screening or diagnostic test using a matched design, in which disease-positive cases are paired with one or more disease-free controls selected to share key characteristics such as age, sex, or clinical setting. Matching controls for confounders before measuring test performance produces more precise and less biased estimates of diagnostic accuracy, and enables direct paired comparisons of competing tests within the same subjects.	A diagnostic accuracy study evaluates how well a new diagnostic test (or biomarker, imaging modality, clinical assessment) detects the presence or absence of disease compared to a reference standard (gold standard). Standardized since 2003 by the STARD (Standards for Reporting of Diagnostic Accuracy Studies) initiative, diagnostic accuracy studies are fundamental to clinical medicine, determining whether and how new tests can improve patient diagnosis and treatment.