A sequential, multiple assignment, randomized trial design with a tailoring function.
Stat Med
; 43(21): 4055-4072, 2024 Sep 20.
Article
en En
| MEDLINE
| ID: mdl-38973591
ABSTRACT
We present a trial design for sequential multiple assignment randomized trials (SMARTs) that use a tailoring function instead of a binary tailoring variable allowing for simultaneous development of the tailoring variable and estimation of dynamic treatment regimens (DTRs). We apply methods for developing DTRs from observational data tree-based regression learning and Q-learning. We compare this to a balanced randomized SMART with equal re-randomization probabilities and a typical SMART design where re-randomization depends on a binary tailoring variable and DTRs are analyzed with weighted and replicated regression. This project addresses a gap in clinical trial methodology by presenting SMARTs where second stage treatment is based on a continuous outcome removing the need for a binary tailoring variable. We demonstrate that data from a SMART using a tailoring function can be used to efficiently estimate DTRs and is more flexible under varying scenarios than a SMART using a tailoring variable.
Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Ensayos Clínicos Controlados Aleatorios como Asunto
Límite:
Humans
Idioma:
En
Año:
2024
Tipo del documento:
Article