Abstract P2-15-05: Visualization of the relationship between survival and sequential treatments in metastatic breast cancer
Authors: Gabrielle Rocque, Aidan Gilbert, Courtney P Williams, Arie Nakhmani, Pravinkumar G Kandhare, Andres Azuero, Smita Bhatia, Kelly M Kenzik, Mark E Burkard
Journal: Cancer Research (2020)

Abstract Background: Sequential therapeutic options in metastatic breast cancer (MBC) are disparate. However, clinical trial data on treatments received pre- or post-trial are limited to number of prior therapies and not the prior sequence or duration of treatment. The lack of contextual data on prior treatment history in clinical trials may contribute to challenges evaluating efficacy. This study sought to understand the relationship between sequential order of treatments, prior treatment time, and survival using a novel visualization technique and conventional statistics. Methods: This retrospective cohort study utilized the nationwide, de-identified electronic health record (EHR)-derived Flatiron Health database to identify women with estrogen receptor (ER) positive, human epidermal growth factor receptor 2 (HER2) -negative MBC diagnosed in 2014 who subsequently received paclitaxel. Visualizations were created with individual patients represented on the Y-axis and time on the X-axis to qualitatively evaluate treatment patterns and survival. Time 0 was defined as initiation of paclitaxel in the metastatic setting. Specific treatments were represented by a color-coded treatment bar, with post-metastatic paclitaxel in black, hormonal therapy in shades of red, chemotherapy in shades of blue, HER2-targeted therapy in shades of green, and other targeted therapies in shades of orange. Treatment gaps were represented by white space. A Kaplan-Meier curve was generated as a function of time from paclitaxel to death or censoring and was superimposed on the visualization. Separate visualizations assessed progression-free and overall survival (PFS, OS). Hazard ratios (HR) and 95% confidence intervals (CI) from Cox proportional hazard models evaluated the association between prior treatment time and post-paclitaxel OS. Results: Of 877 ER+/HER2- MBC patients diagnosed in 2014, 234 received paclitaxel. Qualitatively, the visualization graphic sorted by OS demonstrated that patients who received treatments for longer durations prior to paclitaxel had worse survival compared to those who received paclitaxel earlier in their treatment course (i.e., shorter time on treatment prior to receiving paclitaxel). Quantitatively, median survival from paclitaxel initiation was 20 months (IQR 8-53). When dividing the sample into quartiles based on overall survival after paclitaxel, median time on treatment prior to paclitaxel was 2 months (IQR 0.3-7), 8 months (1-31 IQR), 10 (1-28) months (IQR), and 11 months (IQR 3-32; Table 2). In adjusted models, every year increase on treatment prior to paclitaxel initiation was associated with a 16% increased yearly hazard of death (HR 1.16, 95% CI 1.05-1.29). Conclusion: Visualizing paclitaxel in the context of disease course demonstrates an association between length of time on prior therapy and remaining OS, highlighting the potential for an overall OS benefit to be observed merely based on early vs. late receipt of treatment. This approach to graphically visualizing treatment sequences can aid in better understanding treatment patterns and their impact on survival outcomes through the power of patient-level data. This study should promote future evaluation of treatment sequencing and duration of prior therapies when studying the impact of new treatments, which will be perpetually important as new FDA-approved medications are incorporated into existing MBC treatment paradigms. Citation Format: Gabrielle Rocque, Aidan Gilbert, Courtney P Williams, Arie Nakhmani, Pravinkumar G Kandhare, Andres Azuero, Smita Bhatia, Kelly M Kenzik, Mark E Burkard. Visualization of the relationship between survival and sequential treatments in metastatic breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-15-05.