• Helen Chow, Martin J Edelman, Giuiseppe Giaccone, Suresh S Ramalingam, Timothy A Quill, Andrew D Bowser, Jim Mortimer, Wilma Guerra, Laurel A Beckett, Howard L West, Primo N Lara, and David R Gandara.
• *Department of Hematology and Oncology, UC Davis Comprehensive Cancer Center, Sacramento, CA; †Department of Internal Medicine, University of Maryland, College Park, MD; ‡Department of Oncology, Lombardi Comprehensive Cancer Center of the Georgetown University, Washington, DC; §Department of Biostatistics, University of California, Davis, CA; ‖Division of Medical Oncology, Swedish Cancer Institute, Seattle, WA; ¶Department of Internal Medicine, Swedish Cancer Institute, Seattle, WA; #Department of Internal Medicine, Comprehensive Cancer Center, University of California, Davis, CA.
• J Thorac Oncol. 2015 Oct 1; 10 (10): 1421-9.

BackgroundTreatment guidelines provide recommendations but cannot account for the wide variability in patient-tumor characteristics in individual patients. We developed an on-line interactive decision tool to provide expert recommendations for specific patient scenarios in the first-line and maintenance settings for advanced non-small-cell lung cancer. We sought to determine how providing expert feedback would influence clinical decision-making.MethodFive lung cancer experts selected treatment for 96 different patient cases based on patient and/or tumor-specific features. These data were used to develop an on-line decision tool. Participant physicians entered variables for their patient scenario with treatment choices, and then received expert treatment recommendations for that scenario. To determine the impact on decision-making, users were asked whether the expert feedback impacted their original plan.ResultsA total of 442 individual physicians, of which 88% were from outside the United States, entered 653 cases, with report on impact in 389 cases. Expert feedback affected treatment choice in 73% of cases (23% changed and 50% confirmed decisions). For cases with epidermal growth factor receptor (EGFR) mutation or anaplastic lymphoma kinase (ALK) fusion, all experts selected targeted therapy whereas 51% and 58% of participants did not. Greater variability was seen between experts and participants for cases involving EGFR or ALK wild-type tumors. Participants were 2.5-fold more likely to change to expert recommended therapy for ALK fusions than for EGFR mutations (p = 0.017).ConclusionThis online tool for treatment decision-making resulted in a positive influence on clinician's decisions. This approach offers opportunities for improving quality of care and meets an educational need in application of new therapeutic paradigms.

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