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Investigating a sequence of randomized phase II trials to discover promising treatments
Abstract:
We consider clinical trial strategies to study diseases in which there is rapidly developing technology. We assume the availability of a limited number of patients for screening treatments over a time horizon, and that availability of new treatments for test is staggered over time. We assume further that patient response is binary and rapidly observable. We consider the strategy of conducting a sequence of two-armed randomized clinical trials. We carry over the treatment with the larger number of observed successes on the current trial to the next trial for comparison with a new treatment, with this process repeated at each step. For a fixed total number of patients (N), the number of trials one may conduct in sequence (k) is inversely related to the sample size per trial (2n), N = 2nk. We investigate how k and n influence (a) the expected success probability for the treatment selected at the end, and (b) the expected number of total successes for the N patients. The ultimate objective is to select one treatment, the winner at stage k, to test against a standard regimen in a randomized comparative phase III trial.
Insights
This study proposes a sequential clinical trial strategy for rapidly evolving diseases. It optimizes treatment selection by carrying over successful therapies to subsequent trials, maximizing patient success rates.
Area of Science:
- Clinical Trials
- Biostatistics
- Medical Technology
Background:
- Studying diseases with rapidly developing technology presents unique challenges.
- Limited patient pools and staggered treatment availability require adaptive trial designs.
- Binary and rapidly observable patient responses are key assumptions.
Purpose of the Study:
- To develop and evaluate sequential clinical trial strategies for diseases with fast-evolving treatments.
- To optimize the selection of a superior treatment for a subsequent Phase III trial.
- To analyze the impact of trial parameters on expected success probability and total patient successes.
Main Methods:
- Sequential two-armed randomized clinical trials are employed.
- A "winner-carry-over" design is used, where the most successful treatment advances.
- The relationship between the number of trials (k) and sample size per trial (n) is analyzed for a fixed total patient number (N).
Main Results:
- The study investigates how varying k and n affect the expected success probability of the final selected treatment.
- It also examines the influence of k and n on the total expected successes across all N patients.
- The optimal balance between the number of trials and sample size per trial is explored.
Conclusions:
- The proposed sequential trial strategy aims to efficiently identify the most promising treatments in dynamic research areas.
- This approach seeks to maximize the overall success rate for patients within a fixed trial budget (N patients).
- The ultimate goal is to provide a robustly selected treatment for definitive Phase III comparative trials.