Publication-only abstracts (abstract number preceded by an "e"), published in conjunction with the 2019 ASCO Annual Meeting but not presented at the Meeting, can be found online only.
Precision medicine for lung cancer decision-making: Evaluation of an -omics based FFT approach to personalized medicine.
Metastatic Non-Small Cell Lung Cancer
Lung Cancer—Non-Small Cell Metastatic
2019 ASCO Annual Meeting
J Clin Oncol 37, 2019 (suppl; abstr e20713)
Author(s): Isa Mambetsariev, Benjamin Djulbegovic, Rebecca Pharaon, Blake Hewelt, Erminia Massarelli, Marianna Koczywas, Karen L. Reckamp, Ravi Salgia; City of Hope, Duarte, CA; University of South Florida Health, Tampa, FL; City of Hope National Medical Center, Duarte, CA; The University of Texas MD Anderson Cancer Center, Houston, TX; Department of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA; City of Hope Comprehensive Cancer Center, Duarte, CA; The University of Chicago, Chicago, IL
Background: The prevalence of next-generation sequencing and the availability of a large number of targeted therapies in the clinics, has complicated treatment decision-making in lung cancer. While national guidelines and commercial pathways offer a method to improve the oncologists’ adherence to appropriate testing and treatment modalities available, more effort is required to solidify this as a standard of care model at academic and community sites. A better understanding of the improved durable survival of targeted therapy assignment compared with non-targeted therapy outside of the clinical trial setting is needed to understand the efficacy and accuracy of precision medicine. Methods: We perform an in-depth analysis of a series of lung AD patients (n = 798) with genomic and clinical data in a recently created thoracic patient registry, who were treated at COH between 2009-2018 period. Results: 798 individuals with lung AD were identified in the Thoracic Oncology Registry who were treated or were intended to be treated at COH; 662 (83%) of the patients had genomic testing performed at the request of their treating oncologist and 460 (58%) of whom received a 1st-line targeted therapy decision (including clinical trial assignment based on bio-marker). Oncogenic alterations were detected in 653 (82%) patients with the majority presenting with EGFR (47%), who were mostly treated with erlotinib (78%). 462/653 (70%) patients had an alteration detected with an available FDA approved therapy and 90% (416/462) of the patients were appropriately matched to a targeted therapy based on the oncologist’s decision. Several decision-making algorithms were tested and fast-and-frugal trees (FFTs) proved superior with a positive predictive value (PPV) of 90% and only required two important cues in informing the decision of the type of treatment to give to the patient. Furthermore, a targeted therapy treatment decision showed a significant benefit with a median OS of 38 months as compared to 22 months in the non-targeted therapy decision-making group (p < 0.00001). This was also evident in the PFS analysis where targeted therapy decision-making had a median survival of 9 months as compared with 5 months in the other groups (p < 0.00001). Conclusions: FFTs are a novel tool to test the efficacy of precision medicine in a real-world setting and can provide a more streamlined method for clinical guidance and decision-making. FFTs were able to predict with 90% PPV a precision medicine decision that was correlated with improved PFS (9 vs 5 months) and OS (38 vs 22 months).