Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Analiza adaptivă a relației doză-răspuns× | Studiu clinic adaptiv de Faza II× | |
|---|---|---|
| Domeniu | Epidemiologie | Epidemiologie |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 2000s (key papers 2005–2007; ICH E4 guidance 1994 for classical dose-response) | 1994 (formal framework); widespread adoption 2000s–2010s |
| Autorul original≠ | Frank Bretz, José Pinheiro and colleagues; foundational MCP-Mod framework | Peter Bauer & Klaus Kohne (formal statistical framework, 1994); broader adaptive trial methodology developed through FDA and ICH guidance in the 2000s |
| Tip≠ | Adaptive statistical design and analysis | Experimental clinical trial design |
| Sursa seminală≠ | Bretz, F., Pinheiro, J. C., & Branson, M. (2005). Combining multiple comparisons and modeling techniques in dose-response studies. Biometrics, 61(3), 738-748. DOI ↗ | Bauer, P., & Kohne, K. (1994). Evaluation of experiments with adaptive interim analyses. Biometrics, 50(4), 1029–1041. DOI ↗ |
| Denumiri alternative | adaptive DRA, adaptive dose-finding analysis, adaptive exposure-response analysis, adaptive D-R modeling | Adaptive Ph II trial, seamless adaptive Phase II, adaptive dose-finding trial, response-adaptive Phase II |
| Înrudite≠ | 6 | 1 |
| Rezumat≠ | Adaptive dose-response analysis combines pre-specified dose-response modeling with planned interim looks that allow modifications — such as dropping ineffective doses or reallocating sample size — while maintaining statistical integrity. The most widely cited framework is MCP-Mod (Multiple Comparisons and Modeling), endorsed by the EMA and FDA as a fit-for-purpose methodology for dose-finding studies in drug development. | An adaptive Phase II clinical trial is a prospective experimental design in which pre-specified rules allow the study protocol to be modified — such as dropping arms, adjusting sample size, or narrowing the patient population — based on accumulating interim data, without inflating the Type I error rate. The design is widely used in early-phase drug development to screen candidate doses or treatments efficiently while preserving statistical validity. |
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