152750-156

Precision medicine to improve survival without increasing costs in advanced cancer patients.

Category: 
Health Services Research and Quality of Care
Session Type and Session Title: 
This abstract will not be presented at the 2015 ASCO Annual Meeting but has been published in conjunction with the meeting.
Abstract Number: 

e17641

Citation: 
J Clin Oncol 33, 2015 (suppl; abstr e17641)
Author(s): 
Lincoln Nadauld, S. Burke Van Norman, Gail Fulde, Justin G. McDermott, David Newman, Allison M. Butler, Brian P. Tudor, Heather Gilbert, Karen Yin Lin, Gary Stone, James M. Ford, Derrick S. Haslem; Intermountain Healthcare, St George, UT; Duke University School of Medicine, Durham, NC; Intermountain Healthcare, St. George, UT; Statistical Data Center, LDS Hospital, Intermountain Healthcare, Salt Lake City, UT; Stanford University School of Medicine, Stanford, CA

Abstract Disclosures

Abstract: 

Background: The advent of Next-Generation Sequencing (NGS), and other diagnostic technologies, has enabled the use of genomic information to guide targeted treatment in cancer patients. The outcomes and costs associated with the implementation of precision cancer medicine have been difficult to generate. Leveraging the advantages of an integrated healthcare system, we have implemented a clinical cancer genomics program to personalize targeted treatment for advanced cancer patients in a community setting. We report a retrospective analysis of the clinical outcomes associated with precision cancer medicine. Methods: We conducted a matched cohort study of 72 patients from July 2013 to December 2014, with metastatic cancer of diverse subtypes. The outcomes of 36 patients treated with precision cancer medicine were compared to 36 historical control patients who received standard chemotherapy. Study and control patients were matched according to age, gender, histological diagnosis, and number of previous treatment lines. PFS was compared between the two groups using a Cox Proportional Hazard model for survival and accounting for potential confounders. Costs includes ED visits, hospitalizations, NGS costs and costs for targeted or standard therapy. Results: Progression free survival was 22.9 weeks for the treatment group and 12.0 weeks for the historical control group (p = 0.002). Patients receiving precision cancer medicine compared to conventional treatment patients had a hazard ratio of 0.47 (95% confidence interval of 0.29-0.75) when adjusting for age, gender, histological diagnosis and previous treatment lines. Costs per week were $3204 in the targeted group and $3501 in the control cohort (p = 0.385). Conclusions: Precision cancer medicine appears to significantly improve survival for patients with advanced cancer when compared to control patients who received conventional chemotherapy. The additional survival is not associated with increased costs. While the results of this study warrant further investigation in the setting of a prospective randomized control trial, this genomics-based approach appears to be a viable, and perhaps superior, option for patients with advanced or metastatic cancer.