التفاصيل البيبلوغرافية
العنوان: |
Using Bayesian hierarchical models for controlled post hoc subgroup analysis of clinical trials: application to smoking cessation treatment in American Indians and Alaska Natives. |
المؤلفون: |
Shergina, Elena, Richter, Kimber P., Makosky Daley, Christine, Faseru, Babalola, Choi, Won S., Gajewski, Byron J. |
المصدر: |
Journal of Biopharmaceutical Statistics; 2024, Vol. 34 Issue 4, p513-525, 13p |
مصطلحات موضوعية: |
ALASKA Natives, SMOKING cessation, CLINICAL trials, TREATMENT effect heterogeneity, SUBGROUP analysis (Experimental design), CLINICAL medicine |
مصطلحات جغرافية: |
ALASKA |
مستخلص: |
Clinical trials powered to detect subgroup effects provide the most reliable data on heterogeneity of treatment effect among different subpopulations. However, pre-specified subgroup analysis is not always practical and post hoc analysis results should be examined cautiously. Bayesian hierarchical modelling provides grounds for defining a controlled post hoc analysis plan that is developed after seeing outcome data for the population but before unblinding the outcome by subgroup. Using simulation based on the results from a tobacco cessation clinical trial conducted among the general population, we defined an analysis plan to assess treatment effect among American Indians and Alaska Natives (AI/AN) enrolled in the study. Patients were randomized into two arms using Bayesian adaptive design. For the opt-in arm, clinicians offered a cessation treatment plan after verifying that a patient was ready to quit. For the opt-out arm, clinicians provided all participants with free cessation medications and referred them to a Quitline. The study was powered to test a hypothesis of significantly higher quit rates for the opt-out arm at one-month post randomization. Overall, one-month abstinence rates were 15.9% and 21.5% (opt-in and opt-out arm, respectively). For AI/AN, one-month abstinence rates were 10.2% and 22.0% (opt-in and opt-out arm, respectively). The posterior probability that the abstinence rate in the treatment arm is higher is 0.96, indicating that AI/AN demonstrate response to treatment at almost the same probability as the whole population. [ABSTRACT FROM AUTHOR] |
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قاعدة البيانات: |
Complementary Index |