เปรียบเทียบวิธี

	การศึกษาความแม่นยำในการวินิจฉัยแบบปรับความเสี่ยง	การออกแบบการศึกษาความแม่นยำในการวินิจฉัย
สาขาวิชา	ระบาดวิทยา	การวิจัยทางคลินิก
ตระกูล	Process / pipeline	Process / pipeline
ปีกำเนิด	Conceptual roots 1980s–1990s; covariate-adjusted ROC formally introduced 2009	2003-2015
ผู้ริเริ่ม	Margaret Pepe and colleagues; covariate-adjusted ROC formalized by Janes & Pepe (2009)	Bossuyt, Reitsma, and STARD group (2003); clinical epidemiology pioneers
ประเภท	Observational clinical study design with covariate adjustment	Research Design
แหล่งต้นตำรับ	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.
ชื่อเรียกอื่น	case-mix-adjusted diagnostic accuracy, stratified diagnostic accuracy study, covariate-adjusted diagnostic accuracy, risk-stratified DTA study	diagnostic accuracy study, test accuracy, STARD, diagnostic evaluation
ที่เกี่ยวข้อง	6	2
สรุป	A risk-adjusted diagnostic accuracy study evaluates how well an index test identifies a target condition while explicitly accounting for patient-level risk factors that influence either disease prevalence or test performance. By adjusting for case-mix, it yields accuracy estimates — sensitivity, specificity, and AUC — that are not confounded by the composition of the study sample, enabling fairer comparisons across populations and clinical settings.	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.