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    Analysis of a real-world progression variable and related endpoints for patients with five different cancer types

    Summary of: Griffith SD, Tucker MG, Bowser B, Calkins G, Chang C, Guardino E, Khozin S, Kraut J, You P, Schrag D, Miksad RA. Generating real-world tumor burden endpoints from electronic health record data: Comparison of RECIST, radiology-anchored, and clinician-anchored approaches for abstracting real-world progression in non-small cell lung cancer. Adv Ther. 2019;36(8):2122-2136.

    Our summary

    The identification of cancer progression events (i.e., disease worsening) is important for assessing therapeutic benefit. Measuring cancer progression using real-world data requires methodology that is different from a clinical trial setting.

    The authors previously developed a novel method to reliably ascertain real-world cancer progression (rwP) in a cohort of patients with advanced non-small cell lung cancer, using data from a deidentified electronic health record (EHR)-derived database. This study aimed to determine whether the same method could identify cancer progression in five additional solid tumor types with a range of disease characteristics: metastatic breast cancer, advanced melanoma, small cell lung cancer, metastatic renal cell carcinoma and advanced gastric/esophageal cancer.

    Why this matters

    Our prior seminal publications described a feasible and scalable approach to analyze progression-related endpoints from EHR-derived data in solid tumors. That work, however, was focused on a cohort of patients with advanced NSCLC, and left open the issue of applicability to other tumor types. The present article closes that gap, unlocking a path to enable progression-based analyses as part of a wider array of RWE studies, and expanding what observational studies can contribute to oncology research.

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