Порівняння методів

	Прагматичний адаптивний експеримент	Адаптивний дизайн дослідження
Галузь	Планування експерименту	Клінічні дослідження
Родина	Process / pipeline	Process / pipeline
Рік появи	2000s–2010s (convergence period)	1990s-2000s
Автор методу	Synthesized from pragmatic trial tradition (Schwartz & Lellouch, 1967) and adaptive design methodology; formalized convergence in 2000s–2010s	Stephen Pocock, Christopher Jennison, and statistical methodologists; FDA formalized guidance 2019
Тип	Hybrid experimental design	Research Design
Основоположне джерело	Pallmann, P., Bedding, A. W., Choodari-Oskooei, B., Dimairo, M., Flight, L., Hampson, L. V., ... & Sydes, M. R. (2018). Adaptive designs in clinical trials: why use them, and how to run and report them. BMC Medicine, 16(1), 29.	Pocock, S. J. (2005). Current issues in the design and interpretation of clinical trials. BMJ, 330(7500), 1118–1121.
Інші назви	pragmatic adaptive trial, real-world adaptive trial, PAT, adaptive pragmatic RCT	adaptive trial, adaptive design, response-adaptive randomization, RAR
Пов'язані	3	1
Підсумок	A pragmatic adaptive experiment is a hybrid clinical trial design that combines the real-world generalizability of pragmatic trials with the statistical flexibility of adaptive designs. It enrolls a broad, representative patient population under routine care conditions, while using pre-specified interim analyses to modify trial parameters — such as sample size, allocation ratios, or arm selection — as outcome data accumulate. The result is a design that is both externally valid and resource-efficient.	An adaptive trial design allows pre-specified modifications to the trial based on interim data—such as sample size re-estimation, stopping for futility or efficacy, dropping ineffective arms, or shifting randomization ratios toward better-performing treatments. Developed systematically in the 1990s–2000s by statisticians like Pocock and Jennison, and formalized by the FDA in 2019, adaptive designs accelerate drug development, reduce exposure to ineffective treatments, and improve efficiency without inflating false-positive rates when properly executed.