Secondary Analysis of Randomized Controlled Trials: Methodological Considerations and Best Practices

Abstract

Secondary analyses of randomized controlled trials (RCTs) offer an efficient way to maximize the value of existing trial data and explore clinical questions beyond the original trial scope. This review outlines methodological considerations and best practices, emphasizing their role in evidence-based medicine. We describe major RCT data sources and summarize steps for accessing individual participant data. Key methods include formulating research questions, understanding trial design, data processing, statistical analysis, and clinical interpretation. Types of secondary analyses are discussed including subgroup analysis, biomarker studies, health economics, methodological research, adverse event analysis, and predictive modeling. Common challenges, such as data applicability, missingness, generalizability, and multiple testing, are summarized. With advances in data sharing, secondary analyses are expected to drive scientific discovery and provide more evidence for diagnosis and treatment patterns as long as rigorous standards and transparency are maintained.