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A data-driven examination of which patients follow trial protocol
Maren K Olsen1,2, Karen M Stechuchak1, Anna Hung1,3
1Durham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Health Care System, Durham, NC, USA.
Contemporary Clinical Trials Communications
|September 11, 2020
Summary
This study used a data-driven approach to identify patient characteristics linked to lower adherence in behavioral intervention trials. Understanding these factors can help tailor interventions for better patient outcomes in cardiovascular disease prevention.
Area of Science:
- Behavioral science
- Clinical trial methodology
- Cardiovascular disease research
Background:
- Protocol adherence is crucial for the success of behavioral intervention clinical trials.
- Identifying patient subgroups with varying adherence rates is of increasing interest.
- Three trials (NCT01828567, NCT02360293, NCT01828567) focused on lifestyle behaviors for cardiovascular disease risk were analyzed.
Purpose of the Study:
- To demonstrate a data-driven method for exploring patient characteristics associated with adherence.
- To identify subgroups with the lowest and highest protocol adherence rates.
- To explore heterogeneity in adherence within behavioral intervention trials.
Main Methods:
- Model-based recursive partitioning (MoB) was applied to identify participant characteristics linked to adherence differences.
- Common baseline variables from three trials were used.
- Bootstrap resampling was employed for optimism-corrected c-statistics.
Main Results:
- Protocol adherence rates ranged from 56.9% to 87.5% across the trials.
- MoB identified 2-4 subgroups per trial based on 1-3 variables.
- Factors like pain, education, employment, smoking status, and marital status were associated with adherence differences.
Conclusions:
- Model-based recursive partitioning is a valuable tool for exploring adherence heterogeneity in behavioral intervention trials.
- Identifying subgroups with lower adherence can inform intervention modifications for improved uptake and impact.
- Further validation in similar studies and samples is recommended.
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