Authors: Rocque GB, Kandhare PG, Williams CP, Nakhmani A, Azuero A, Burkard ME, Forero A, Bhatia S, Kenzik KM
Title: Visualization of Sequential Treatments in Metastatic Breast Cancer.
Journal: JCO Clin Cancer Inform 3:1-8
Date: 2019 Mar
PubMed ID: 30840488
Abstract: PURPOSE: Treatment sequencing of metastatic breast cancer (MBC) is heterogeneous. The primary objective of this study was to develop a visualization technique to understand population-level treatment sequencing for MBC. Secondary outcomes were to describe the heterogeneity of MBC treatment sequencing, as measured by the proportion of patients with a rare sequence, and to generate hypotheses about the impact of sequencing on overall survival. METHODS: This retrospective review evaluated treatment sequencing for patients with MBC in the SEER-Medicare database. Patients with either de novo MBC or International Classification of Diseases, Ninth Revision, diagnosis codes for secondary metastasis (197.XX-198.XX) on two separate dates, excluding breast (198.81, 198.82, 198.2) and lymph nodes (196.XX), were included. Complete Medicare Parts A, B, and D coverage was required. A treatment sequence that fewer than 11 patients received was considered rare. A graphic was created with each nonrare treatment-sequence grouping on the y-axis and time on the x-axis. Bars representing time on hormonal therapy, chemotherapy, human epidermal growth factor receptor 2-targeted therapy, and other targeted therapies were color coded. Kaplan-Meier-like curves were overlaid on treatment maps, using estimated median survival for each sequence. RESULTS: Of 6,639 patients with MBC, 56% received a treatment sequence that fewer than 11 other patients received, with 2,985 other unique, rare sequences were identified. Sequence visualization demonstrated differential survival, with longer median survival for those initially receiving hormonal therapy. The median time receiving initial treatment was similar for patients receiving first-line chemotherapy. CONCLUSION: Treatment-sequence visualization can enhance the capacity to effectively conceptualize treatment patterns and patient outcomes.