A Strategy to Characterize Chemotherapy Diffusion with Population-Based Data
Glenn Heller, Memorial Sloan Kettering Cancer Center  Katherine Panageas, Sloan Kettering Cancer Center  Deborah Schrag, Memorial Sloan Kettering Cancer Center  *Cami Sima, Memorial Sloan Kettering Cancer Center 

Keywords: chemotherapy diffusion, population-based data, patient-level data, time to event anaysis

To inform assessments of the quality of cancer care, we investigate trends of chemotherapy drug diffusion subsequent to FDA approval. We propose a method that is relevant to patient-level population-based data and employs time-to-event techniques to describe the probability of utilization of a drug within a specified timeframe subsequent to the diagnosis of cancer. By mapping the relationship between this probability and calendar time of a patient’s diagnosis, we can assess trends in diffusion post FDA approval. Our approach accounts for the dependent censoring for death, as well as for the clustering of patients within physicians. The method proposed is illustrated using SEER-Medicare data applied to two case studies: gemcitabine, approved for stage III/IV pancreas cancer, and irinotecan, approved as a second line therapy for stage IV colorectal cancer.

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