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An adaptive power prior for sequential clinical trials - Application to bridging studies.

ABSTRACT: During drug evaluation trials, information from clinical trials previously conducted on another population, indications or schedules may be available. In these cases, it might be desirable to share information by efficiently using the available resources. In this work, we developed an adaptive power prior with a commensurability parameter for using historical or external information. It allows, at each stage, full borrowing when the data are not in conflict, no borrowing when the data are in conflict or "tuned" borrowing when the data are in between. We propose to apply our adaptive power prior method to bridging studies between Caucasians and Asians, and we focus on the sequential adaptive allocation design, although other design settings can be used. We weight the prior information in two steps: the effective sample size approach is used to set the maximum desirable amount of information to be shared from historical data at each step of the trial; then, in a sort of Empirical Bayes approach, a commensurability parameter is chosen using a measure of distribution distance. This approach avoids elicitation and computational issues regarding the usual Empirical Bayes approach. We propose several versions of our method, and we conducted an extensive simulation study evaluating the robustness and sensitivity to prior choices.

SUBMITTER: Ollier A

PROVIDER: S-EPMC7433690 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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An adaptive power prior for sequential clinical trials - Application to bridging studies.

Ollier Adrien A Morita Satoshi S Ursino Moreno M Zohar Sarah S

Statistical methods in medical research 20191115 8

During drug evaluation trials, information from clinical trials previously conducted on another population, indications or schedules may be available. In these cases, it might be desirable to share information by efficiently using the available resources. In this work, we developed an adaptive power prior with a commensurability parameter for using historical or external information. It allows, at each stage, full borrowing when the data are not in conflict, no borrowing when the data are in con ...[more]

PMID: 31729275

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Project description:Currently, a growing placebo response rate has been observed in clinical trials for antidepressant drugs, a phenomenon that has made it increasingly difficult to demonstrate efficacy. The sequential parallel comparison design (SPCD) is a clinical trial design that was proposed to address this issue. The SPCD theoretically has the potential to reduce the sample-size requirement for a clinical trial and to simultaneously enrich the study population to be less responsive to the placebo.Because the basic SPCD already reduces the placebo response by removing placebo responders between the first and second phases of a trial, the purpose of this study was to examine whether we can further improve the efficiency of the basic SPCD and whether we can do so when the projected underlying drug and placebo response rates differ considerably from the actual ones.Three adaptive designs that used interim analyses to readjust the length of study duration for individual patients were tested to reduce the sample-size requirement or increase the statistical power of the SPCD. Various simulations of clinical trials using the SPCD with interim analyses were conducted to test these designs through calculations of empirical power.From the simulations, we found that the adaptive designs can recover unnecessary resources spent in the traditional SPCD trial format with overestimated initial sample sizes and provide moderate gains in power. Under the first design, results showed up to a 25% reduction in person-days, with most power losses below 5%. In the second design, results showed up to a 8% reduction in person-days with negligible loss of power. In the third design using sample-size re-estimation, up to 25% power was recovered from underestimated sample-size scenarios.Given the numerous possible test parameters that could have been chosen for the simulations, the study's results are limited to situations described by the parameters that were used and may not generalize to all possible scenarios. Furthermore, dropout of patients is not considered in this study.It is possible to make an already complex design such as the SPCD adaptive, and thus more efficient, potentially overcoming the problem of placebo response at lower cost. Ultimately, such a design may expedite the approval of future effective treatments.

Project description:BackgroundTrial design plays a key role in clinical trials. Traditional group sequential design has been used in cardiovascular clinical trials over decades as the trials can potentially be stopped early, therefore, it can reduce pre-planned sample size and trial resources. In contrast, trials with adoptive designs provide greater flexibility and are more efficient due to the ability to modify trial design according to the interim analysis results. In this systematic review, we aim to explore characteristics of adaptive and traditional group sequential trials in practice and to gain an understanding how these trial designs are currently being reported in cardiology.MethodsPubMed, Embase and Cochrane Central Register of Controlled Trials database were searched from January 1980 to June 2022. Randomised controlled phase 2/3 trials with either adaptive or traditional group sequential design in patients with cardiovascular disease were included. Descriptive statistics were used to present the collected data.ResultsOf 456 articles found in the initial search, 56 were identified including 43 (76.8%) trials with traditional group sequential design and 13 (23.2%) with adaptive. Most trials were large, multicentre, led by the USA (50%) and Europe (28.6%), and were funded by companies (78.6%). For trials with group sequential design, frequency of interim analyses was determined mainly by the number of events (47%). 67% of the trials stopped early, in which 14 (32.6%) were due to efficacy, and 5 (11.6%) for futility. The commonly used stopping rule to terminate trials was O'Brien- Fleming-type alpha spending function (10 (23.3%)). For trials with adaptive designs, 54% of the trials stopped early, in which 4 (30.8%) were due to futility, and 2 (15.4%) for efficacy. Sample size re-estimation was commonly used (8 (61.5%)). In 69% of the trials, simulation including Bayesian approach was used to define the statistical stopping rules. The adaptive designs have been increasingly used (from 0 to 1999 to 38.6% after 2015 amongst adaptive trials). 25% of the trials reported "adaptive" in abstract or title of the studies.ConclusionsThe application of adaptive trials is increasingly popular in cardiovascular clinical trials. The reporting of adaptive design needs improving.

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An adaptive power prior for sequential clinical trials - Application to bridging studies.

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An adaptive power prior for sequential clinical trials - Application to bridging studies.

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