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Martin J. Edelman, Daniel P. Raymond, Dwight H. Owen, Michelle B. Leavy, Kari Chansky, Sriram Yennu, Felix G. Fernandez, Carolyn J. Presley, Tithi Biswas, Gwendolyn P. Quinn, Matthew B. Schabath, Seth Sheffler-Collins, Laura Chu, and Richard E. Gliklich

Background: Lung cancer is the leading cause of cancer-related death in the United States and globally, and many questions exist about treatment options. Harmonizing data across registries and other data collection efforts would yield a robust data infrastructure to help address many research questions. The purpose of this project was to develop a minimum set of patient and clinician relevant harmonized outcome measures that can be collected in non–small cell lung cancer (NSCLC) patient registries and clinical practice. Methods: Seventeen lung cancer registries and related efforts were identified and invited to submit outcome measures. Representatives from medical specialty societies, government agencies, health systems, health information technology groups, patient advocacy organizations, and industry formed a stakeholder panel to categorize the measures and harmonize definitions using the Agency for Healthcare Research and Quality’s supported Outcome Measures Framework (OMF). Results: The panel reviewed 66 outcome measures and identified a minimum set of 8 broadly relevant measures in the OMF categories of patient survival, clinical response, events of interest, and resource utilization. The panel harmonized definitions for the 8 measures through in-person and virtual meetings. The panel did not reach consensus on 1 specific validated instrument for capturing patient-reported outcomes. The minimum set of harmonized outcome measures is broadly relevant to clinicians and patients and feasible to capture across NSCLC disease stages and treatment pathways. A pilot test of these measures would be useful to document the burden and value of the measures for research and in clinical practice. Conclusions: By collecting the harmonized measures consistently, registries and other data collection systems could contribute to the development research infrastructure and learning health systems to support new research and improve patient outcomes.