Compara mètodes
Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.
| Pragmatic adaptive experiment× | Disseny de prova adaptatiu× | |
|---|---|---|
| Camp≠ | Disseny experimental | Recerca clínica |
| Família | Process / pipeline | Process / pipeline |
| Any d'origen≠ | 2000s–2010s (convergence period) | 1990s-2000s |
| Autor original≠ | 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 |
| Tipus≠ | Hybrid experimental design | Research Design |
| Font seminal≠ | 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. DOI ↗ | Pocock, S. J. (2005). Current issues in the design and interpretation of clinical trials. BMJ, 330(7500), 1118–1121. link ↗ |
| Àlies≠ | pragmatic adaptive trial, real-world adaptive trial, PAT, adaptive pragmatic RCT | adaptive trial, adaptive design, response-adaptive randomization, RAR |
| Relacionats≠ | 3 | 1 |
| Resum≠ | 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. |
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