Σύγκριση μεθόδων

	Μελέτη Προσαρμοστικής Διαγνωστικής Ακρίβειας	Προσαρμοστική Μελέτη Κοόρτης
Πεδίο	Επιδημιολογία	Επιδημιολογία
Οικογένεια	Process / pipeline	Process / pipeline
Έτος προέλευσης	2000s–2010s (adaptive designs codified for diagnostics ~2010s)	2000s–2010s (systematic formalisation)
Δημιουργός	Adaptation of STARD framework (Bossuyt et al.) combined with adaptive design principles (Jennison & Turnbull; FDA guidance)	Extension of classic cohort methods; adaptive design principles formalised by regulatory and epidemiology communities in the 2000s–2010s
Τύπος	Adaptive observational/experimental study design	Observational / adaptive epidemiological design
Θεμελιώδης πηγή	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.	VanderWeele, T. J., & Hernan, M. A. (2012). Results on differential and dependent measurement error of the exposure and the outcome using signed directed acyclic graphs. American Journal of Epidemiology, 175(12), 1303–1310.
Εναλλακτικές ονομασίες	adaptive DTA study, adaptive diagnostic test evaluation, adaptive test accuracy trial, adaptive STARD study	adaptive longitudinal study, flexible cohort design, adaptive prospective cohort, ACS
Συναφείς	6	4
Σύνοψη	An adaptive diagnostic accuracy study evaluates how well an index test distinguishes between patients with and without a target condition, while incorporating pre-specified interim analyses that allow modifications — such as sample size re-estimation, threshold adjustment, or subgroup enrichment — based on accumulating data. This design improves efficiency and ethical conduct compared to fixed-sample diagnostic studies, particularly when prior prevalence or test performance data are uncertain.	An adaptive cohort study is a longitudinal observational design that follows a defined group of individuals over time to assess exposure-outcome relationships, while incorporating pre-specified adaptation rules that allow protocol modifications — such as sample-size re-estimation, subgroup enrichment, or measurement schedule adjustments — based on accumulating interim data. Adaptations are made without compromising validity, guided by a statistical analysis plan agreed upon before data collection begins.