Diversity by Design: Real-World Data to Enhance Representation in Clinical Cancer Research.
review · Level V
Where this comes from
- Record sourced from PubMed, PMID 40834138.
- Also identified by DOI 10.1158/1078-0432.CCR-25-1255.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
Inclusive and diverse enrollment in clinical trials promotes trust in clinical research and its findings by improving generalizability and fostering health and health care equities. Diverse participation also facilitates the detection of potential differences in treatment response across subgroups, thereby enhancing precision medicine efforts. Yet, patients with cancer who participate in clinical trials are more likely to be Caucasian, younger, and healthier compared with their representation in the broader cancer population. Given emerging health authority guidance and other related initiatives calling for more representative trials, there is an urgent need to develop and implement strategies to improve enrollment of a study population that reflects the intended use population. Real-world data/evidence (RWD/E) can help set trial enrollment targets and strategy, identify drivers and barriers in recruiting diverse populations, and provide supplemental evidence on underrepresented populations, thus improving the external validity of clinical trial results. In this perspective review, we outline a diversity dimension framework that includes demographic, clinical, treatment environment, and other elements and discuss opportunities and challenges with which RWD/E could enhance clinical trial representativeness and diversity. Specifically, we discuss the diversity dimensions relevant to oncology clinical development and various approaches in utilizing RWD to improve diversity across stages of clinical development, with use cases.
Medical subject headings
- Neoplasms
- Clinical Trials as Topic
- Patient Selection
- Research Design
- Biomedical Research
- Cultural Diversity