Recognizing Biases in Real-World mCSPC Data

Panelists discuss how recognizing and addressing potential biases in real-world evidence (RWE) is essential for accurately interpreting outcomes and applying them to clinical care in metastatic castration-sensitive prostate cancer (mCSPC). They explain that retrospective analyses using electronic health records and claims data provide valuable insights into everyday practice but can be affected by methodological pitfalls such as channeling bias—where sicker or healthier patients are preferentially prescribed a certain therapy—and immortal time bias, which can incorrectly favor one treatment by including survival time before therapy initiation.

Panelists discuss how data scientists and clinicians can minimize these limitations by using robust statistical approaches, including active-comparator designs, propensity score adjustments, and sensitivity analyses. Careful cohort selection, clearly defined index dates, and transparent reporting of missing data help improve the credibility of RWE studies. These practices ensure that findings are not merely artifacts of data structure but reflect meaningful clinical differences observed in real-world settings.

Panelists discuss how understanding these biases empowers clinicians to apply RWE appropriately during patient discussions. When providers acknowledge study limitations and interpret findings within the broader context of clinical trials and patient individuality, they strengthen both accuracy and trust. Ultimately, a balanced understanding of RWE and its biases helps clinicians deliver data-driven yet personalized care, ensuring that real-world data enhances decision-making rather than misleading it.