Eric L Eisenstein1, Meredith N Zozus2, Sharon F Terry3, Linda Davidson-Ray4, Kevin J Anstrom4. 1. Duke Clinical Research Institute, 31 Innisfree Dr., Durham, NC, 27707, USA. eric.eisenstein@duke.edu. 2. University of Texas Health Science Center at San Antonio, San Antonio, TX, USA. 3. Genetic Alliance, Washington, DC, USA. 4. Duke Clinical Research Institute, 31 Innisfree Dr., Durham, NC, 27707, USA.
Abstract
BACKGROUND: The 21st Century Cures Act allows the US Food and Drug Administration (FDA) to utilize real-world data (RWD) to create real-world evidence (RWE) for new indications or post approval study requirements. We compared central adjudication with two insurance claims data sources to understand how endpoint accuracy differences impact RWE results. METHODS: We developed a decision analytic model to compare differences in efficacy (all-cause death, stroke and myocardial infarction) and safety (bleeding requiring transfusion) results for a simulated acute coronary syndrome antiplatelet therapy clinical trial. Endpoint accuracy metrics were derived from previous studies that compared centrally-adjudicated and insurance claims-based clinical trial endpoints. RESULTS: Efficacy endpoint results per 100 patients were similar for the central adjudication model (intervention event rate, 11.3; control, 13.7; difference, 2.4) and the prospective claims data collection model (intervention event rate, 11.2; control 13.6; difference, 2.3). However, the retrospective claims linking model's efficacy results were larger (intervention event rate, 14.6; control, 18.0; difference, 3.4). True positive event rate results (intervention, control and difference) for both insurance claims-based models were less than the central adjudication model due to false negative events. Differences in false positive event rates were responsible for differences in efficacy results for the two insurance claims-based models. CONCLUSION: Efficacy endpoint results differed by data source. Investigators need guidance to determine which data sources produce regulatory-grade RWE.
BACKGROUND: The 21st Century Cures Act allows the US Food and Drug Administration (FDA) to utilize real-world data (RWD) to create real-world evidence (RWE) for new indications or post approval study requirements. We compared central adjudication with two insurance claims data sources to understand how endpoint accuracy differences impact RWE results. METHODS: We developed a decision analytic model to compare differences in efficacy (all-cause death, stroke and myocardial infarction) and safety (bleeding requiring transfusion) results for a simulated acute coronary syndrome antiplatelet therapy clinical trial. Endpoint accuracy metrics were derived from previous studies that compared centrally-adjudicated and insurance claims-based clinical trial endpoints. RESULTS: Efficacy endpoint results per 100 patients were similar for the central adjudication model (intervention event rate, 11.3; control, 13.7; difference, 2.4) and the prospective claims data collection model (intervention event rate, 11.2; control 13.6; difference, 2.3). However, the retrospective claims linking model's efficacy results were larger (intervention event rate, 14.6; control, 18.0; difference, 3.4). True positive event rate results (intervention, control and difference) for both insurance claims-based models were less than the central adjudication model due to false negative events. Differences in false positive event rates were responsible for differences in efficacy results for the two insurance claims-based models. CONCLUSION: Efficacy endpoint results differed by data source. Investigators need guidance to determine which data sources produce regulatory-grade RWE.
Entities:
Keywords:
Administrative claims; Data collection; Data quality; Measurement accuracy; Real world data; Real world evidence
Authors: Eric L Eisenstein; Kristi Prather; Stephen J Greene; Tina Harding; Amanda Harrington; Davera Gabriel; Ingrid Jones; Robert J Mentz; Eric J Velazquez; Kevin J Anstrom Journal: Stud Health Technol Inform Date: 2019
Authors: Christoph B Olivier; Deepak L Bhatt; Sergio Leonardi; Gregg W Stone; C Michael Gibson; Ph Gabriel Steg; Christian W Hamm; Matthew D Wilson; Stacey Mangum; Matthew J Price; Jayne Prats; Harvey D White; Renato D Lopes; Robert A Harrington; Kenneth W Mahaffey Journal: Circ Cardiovasc Interv Date: 2019-07-12 Impact factor: 6.546
Authors: Arun Krishnamoorthy; Eric D Peterson; J David Knight; Kevin J Anstrom; Mark B Effron; Marjorie E Zettler; Linda Davidson-Ray; Brian A Baker; Patrick L McCollam; Daniel B Mark; Tracy Y Wang Journal: J Am Heart Assoc Date: 2016-01-25 Impact factor: 5.501