Jordan B Strom1, Hector Tamez1, Yuansong Zhao2, Linda R Valsdottir2, Jeptha Curtis3, J Matthew Brennan4, Changyu Shen1, Jeffrey J Popma5, Laura Mauri6, Robert W Yeh7. 1. Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology; Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA; Harvard Medical School, Boston, MA. 2. Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology; Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA. 3. Center for Outcomes Research and Evaluation, Yale University School of Medicine, New Haven, CT. 4. Duke Clinical Research Institute, Durham, NC. 5. Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA; Harvard Medical School, Boston, MA; Baim Institute for Clinical Research, Boston, MA. 6. Medtronic Inc. 7. Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology; Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA; Harvard Medical School, Boston, MA; Baim Institute for Clinical Research, Boston, MA. Electronic address: ryeh@bidmc.harvard.edu.
Abstract
BACKGROUND: Randomized controlled trials are the "gold standard" for comparing the safety and efficacy of therapies but may be limited due to high costs, lack of feasibility, and difficulty enrolling "real-world" patient populations. The Extending Trial-Based Evaluations of Medical Therapies Using Novel Sources of Data (EXTEND) Study seeks to evaluate whether data collected within procedural registries and claims databases can reproduce trial results by substituting surrogate non-trial-based variables for exposures and outcomes. METHODS AND RESULTS: Patient-level data from 2 clinical trial programs-the Dual Antiplatelet Therapy Study and the United States CoreValve Studies-will be linked to a combination of national registry, administrative claims, and health system data. The concordance between baseline and outcomes data collected within nontrial data sets and trial information, including adjudicated end point events, will be assessed. We will compare the study results obtained using these alternative data sources to those derived using trial-ascertained variables and end points using trial-adjudicated end points and covariates. CONCLUSIONS: Linkage of trials to registries and claims data represents an opportunity to use alternative data sources in place of and as adjuncts to randomized clinical trial data but requires further validation. The results of this research will help determine how these data sources can be used to improve our present and future understanding of new medical treatments.
BACKGROUND: Randomized controlled trials are the "gold standard" for comparing the safety and efficacy of therapies but may be limited due to high costs, lack of feasibility, and difficulty enrolling "real-world" patient populations. The Extending Trial-Based Evaluations of Medical Therapies Using Novel Sources of Data (EXTEND) Study seeks to evaluate whether data collected within procedural registries and claims databases can reproduce trial results by substituting surrogate non-trial-based variables for exposures and outcomes. METHODS AND RESULTS: Patient-level data from 2 clinical trial programs-the Dual Antiplatelet Therapy Study and the United States CoreValve Studies-will be linked to a combination of national registry, administrative claims, and health system data. The concordance between baseline and outcomes data collected within nontrial data sets and trial information, including adjudicated end point events, will be assessed. We will compare the study results obtained using these alternative data sources to those derived using trial-ascertained variables and end points using trial-adjudicated end points and covariates. CONCLUSIONS: Linkage of trials to registries and claims data represents an opportunity to use alternative data sources in place of and as adjuncts to randomized clinical trial data but requires further validation. The results of this research will help determine how these data sources can be used to improve our present and future understanding of new medical treatments.
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