방법 비교

	환자 증례 구성(case-mix)을 고려한 위험 조정 진단 정확도 연구	전향적 진단 정확도 연구
분야	역학	역학
계열	Process / pipeline	Process / pipeline
기원 연도	Conceptual roots 1980s–1990s; covariate-adjusted ROC formally introduced 2009	Formalized 2000s; practice dates to mid-20th century
창시자	Margaret Pepe and colleagues; covariate-adjusted ROC formalized by Janes & Pepe (2009)	Established through STARD initiative (Bossuyt, Reitsma et al., 2000s)
유형	Observational clinical study design with covariate adjustment	Observational / evaluative study design
원전	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., ... & Cohen, J. F. (2015). STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies. BMJ, 351, h5527.
별칭	case-mix-adjusted diagnostic accuracy, stratified diagnostic accuracy study, covariate-adjusted diagnostic accuracy, risk-stratified DTA study	prospective DTA study, prospective test accuracy study, forward-looking diagnostic study, prospective index test evaluation
관련	6	6
요약	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 prospective diagnostic accuracy study enrolls participants before any test results are known and follows them forward in time to evaluate how well an index test (the test under evaluation) distinguishes individuals with and without a target condition, using a reference standard applied independently. Key accuracy metrics include sensitivity, specificity, positive and negative predictive values, and the area under the ROC curve. The prospective design reduces many biases inherent in retrospective test evaluations.