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SECRETS: Subject-efficient clinical randomized controlled trials using synthetic intervention.

Sayeri Lala¹, Niraj K Jha¹

¹Department of Electrical and Computer Engineering, Princeton University, Princeton, 08544, NJ, USA.

Contemporary Clinical Trials Communications

|February 14, 2024

Summary

SECRETS enhances clinical trial power by simulating cross-over designs within parallel-group randomized controlled trials (RCTs). This subject-efficient approach reduces the need for large sample sizes, improving trial feasibility.

Keywords:

Clinical randomized controlled trials Counterfactual estimation Hypothesis testing Sample efficiency Synthetic intervention

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Area of Science:

Clinical Trials
Biostatistics
Pharmaceutical Research

Background:

Parallel-group randomized controlled trials (RCTs) are crucial for Phase-3 effectiveness but face challenges with large sample sizes and high failure rates.
Existing methods to increase trial power, such as augmenting data or using cross-over designs, have limitations regarding data comparability and applicability to chronic conditions.

Purpose of the Study:

To introduce SECRETS (Subject-Efficient Clinical Randomized Controlled Trials using Synthetic Intervention), a novel framework to enhance the power of parallel-group RCTs.
To simulate the benefits of a cross-over design using only data from the RCT itself, thereby improving subject efficiency.

Main Methods:

SECRETS employs a state-of-the-art counterfactual estimation algorithm, synthetic intervention (SI), to estimate individual treatment effects (ITEs) for all subjects.
A novel hypothesis testing strategy is introduced to address dependencies among ITEs induced by SI, ensuring reliable treatment effectiveness testing.

Main Results:

SECRETS demonstrated a significant increase in RCT power across three real-world Phase-3 trials, with an average increase of 21.5%.
The framework reduced the required sample size by an average of 2,000 subjects per arm to achieve 80% power and 5% significance.
Analyses confirmed that SECRETS consistently reduces the variance of the average treatment effect, effectively mimicking a cross-over design's benefits.

Conclusions:

SECRETS offers a feasible solution for increasing clinical trial power, particularly when meeting sample size requirements is challenging.
By simulating cross-over designs, SECRETS enhances subject efficiency in parallel-group RCTs, making them more practical and effective.