Leveraging Real-World Data for Clinical Decision Making in Geriatric Oncology

Older adults represent most patients with cancer worldwide, yet they remain substantially underrepresented in randomized clinical trials (RCTs), limiting the evidence available to guide treatment decisions in this growing population. Real-world data (RWD), defined as data routinely collected from clinical practice such as electronic health records, administrative claims, clinical registries, wearable devices, and patient-reported outcomes, offer an opportunity to complement traditional trial evidence. In this narrative review, we aimed to synthesize the potential benefits, limitations, and considerations in leveraging RWD for clinical decision making in geriatric oncology. When analyzed rigorously, RWD can generate real-world evidence (RWE) that reflects the heterogeneity of patients seen in routine care and provides insights into treatment patterns, safety, effectiveness, healthcare utilization, and patient-centered outcomes. In geriatric oncology, these data sources are particularly valuable for capturing multidimensional health profiles that extend beyond chronological age, including comorbidities, functional status, and social determinants of health. RWD can also help characterize healthcare trajectories, identify predictors of treatment tolerance and toxicity, and evaluate outcomes such as quality of life and resource utilization. However, important challenges remain, including issues related to data quality and standardization, confounding and bias inherent to observational analyses, ethical considerations surrounding data sharing, and difficulties integrating RWE into clinical decision making. Advances in artificial intelligence, global data networks, regulatory acceptance of RWE, decentralized clinical trials, and expanded data infrastructure may further enhance the role of RWD in oncology. When used rigorously, RWE can help fill evidence gaps and support more personalized care for older adults with cancer.