Diversity by Design: Real-World Data to Enhance Representation in Clinical Cancer Research.

Area of Science:

• Clinical research methodology
• Health equity and access
• Data science in healthcare

Background:

• Clinical trials often lack diversity, with underrepresentation of minority and non-healthy populations.
• This lack of diversity limits generalizability and hinders precision medicine efforts.
• Regulatory bodies and initiatives increasingly emphasize the need for more representative trial populations.

Purpose of the Study:

• To explore the utility of real-world data/evidence (RWD/E) in enhancing clinical trial diversity and representativeness.
• To propose a framework for diversity dimensions in clinical development.
• To discuss opportunities and challenges in leveraging RWD/E for inclusive trial enrollment.

Main Methods:

• Perspective review of existing literature and initiatives.
• Development of a diversity dimension framework (demographic, clinical, treatment environment).
• Discussion of RWD/E applications across clinical development stages.

Main Results:

• RWD/E can inform trial enrollment targets and strategies.
• RWD/E can identify barriers to recruiting diverse patient populations.
• RWD/E can provide supplemental evidence for under-represented groups, improving external validity.

Conclusions:

• Real-world data/evidence offers significant potential to improve clinical trial diversity.
• Strategic use of RWD/E is essential for creating more representative oncology trials.
• Addressing diversity gaps in trials is critical for advancing health equity and personalized medicine.