Using Trial Sequential Analysis for estimating the sample sizes of further trials: example using smoking cessation...

Area of Science:

• Clinical Trials Methodology
• Health Intervention Research
• Biostatistics

Background:

• Assessing health intervention benefits and harms is resource-intensive, often necessitating pilot and randomized clinical trials.
• Pilot trial data informs the design and sample size of subsequent randomized clinical trials.
• Pilot trial findings on benefits and harms are frequently overlooked once a main trial commences.

Purpose of the Study:

• To demonstrate the application of Trial Sequential Analysis (TSA) software for sample size estimation in behavioral smoking cessation trials.
• To illustrate combining data from new and existing trials using TSA for intervention effect assessment.
• To provide a practical example of using TSA for sample size determination and research funding arguments.

Main Methods:

• Utilized Trial Sequential Analysis (TSA) software incorporating data from feasibility and pilot trials.
• Applied TSA methods to estimate the required sample size for a planned behavioral smoking cessation trial.
• Integrated data from a new trial with prior trial data within the TSA framework.

Main Results:

• Successfully employed TSA software to determine a practical sample size for a new randomized clinical trial.
• The worked example demonstrated the feasibility of using TSA for sample size calculation.
• The TSA-derived sample size was instrumental in securing research funding for the trial.

Conclusions:

• Trial Sequential Analysis (TSA) effectively uses data from pilot and other trials to estimate sample sizes for future randomized clinical trials.
• This approach can yield smaller sample size estimates compared to conventional methods by leveraging available data.
• TSA offers a valuable tool for optimizing the design and resource allocation in clinical trial planning.