Data Checks Before Registering Study Protocols for Health Care Database Analyses von Wang, Shirley V, Schneeweiss, Sebastian

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External Controls to Study Treatment Effects in Rare Diseases: Challenges and Future Directions von Weberpals, Janick, Wang, Shirley V.

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Building transparency and reproducibility into the practice of pharmacoepidemiology and outcomes research von Wang, Shirley V, Pottegård, Anton

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Hypothetical Assessments of Trial Emulations von Schneeweiss, Sebastian, Wang, Shirley V

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Machine learning to advance the prediction, prevention and treatment of eating disorders von Wang, Shirley B.

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Strengthening Real‐World Evidence on Question Not Answered by Randomized Trials: A Trial Calibration Approach von Kirchgesner, Julien, Wang, Shirley V., Schneeweiss, Sebastian

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Understanding the Facets of Emulating Randomized Clinical Trials—Reply von Wang, Shirley V, Schneeweiss, Sebastian

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Klotho Deficiency Causes Heart Aging via Impairing the Nrf2-GR Pathway von Chen, Kai, Wang, Shirley, Sun, Qiwei Wilton, Zhang, Bo, Ullah, Mujib, Sun, Zhongjie

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Assessing and Interpreting Real‐World Evidence Studies: Introductory Points for New Reviewers von Wang, Shirley V., Schneeweiss, Sebastian

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The reporting of studies conducted using observational routinely collected health data statement for pharmacoepidemiology (RECORD-PE) von Langan, Sinéad M, Schmidt, Sigrún AJ, Wing, Kevin, Ehrenstein, Vera, Nicholls, Stuart G, Filion, Kristian B, Klungel, Olaf, Petersen, Irene, Sorensen, Henrik T, Dixon, William G, Guttmann, Astrid, Harron, Katie, Hemkens, Lars G, Moher, David, Schneeweiss, Sebastian, Smeeth, Liam, Sturkenboom, Miriam, von Elm, Erik, Wang, Shirley V, Benchimol, Eric I

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The FAIRification of research in real‐world evidence: A practical introduction to reproducible analytic workflows using Git and R von Weberpals, Janick, Wang, Shirley V.

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An open‐source implementation of tree‐based scan statistics von Russo, Massimiliano, Wang, Shirley V.

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Improving Transparency to Build Trust in Real-World Secondary Data Studies for Hypothesis Testing—Why, What, and How: Recommendations and a Road Map from the Real-World Evidence Tr... von Orsini, Lucinda S., Berger, Marc, Crown, William, Daniel, Gregory, Eichler, Hans-Georg, Goettsch, Wim, Graff, Jennifer, Guerino, John, Jonsson, Pall, Lederer, Nirosha Mahendraratnam, Monz, Brigitta, Mullins, C. Daniel, Schneeweiss, Sebastian, Brunt, David Van, Wang, Shirley V., Willke, Richard J.

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Core psychopathology of treatment-seeking patients with binge-eating disorder: a network analysis investigation von Wang, Shirley B., Jones, Payton J., Dreier, Melissa, Elliott, Haley, Grilo, Carlos M.

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Emulation of Randomized Clinical Trials With Nonrandomized Database Analyses: Results of 32 Clinical Trials von Wang, Shirley V, Schneeweiss, Sebastian, Franklin, Jessica M, Desai, Rishi J, Feldman, William, Garry, Elizabeth M, Glynn, Robert J, Lin, Kueiyu Joshua, Paik, Julie, Patorno, Elisabetta, Suissa, Samy, D’Andrea, Elvira, Jawaid, Dureshahwar, Lee, Hemin, Pawar, Ajinkya, Sreedhara, Sushama Kattinakere, Tesfaye, Helen, Bessette, Lily G, Zabotka, Luke, Lee, Su Been, Gautam, Nileesa, York, Cassie, Zakoul, Heidi, Concato, John, Martin, David, Paraoan, Dianne, Quinto, Kenneth

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Transparency in real‐world evidence (RWE) studies to build confidence for decision‐making: Reporting RWE research in diabetes von Patorno, Elisabetta, Schneeweiss, Sebastian, Wang, Shirley V.

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Using Real‐World Data to Extrapolate Evidence From Randomized Controlled Trials von Wang, Shirley V., Schneeweiss, Sebastian, Gagne, Joshua J., Evers, Thomas, Gerlinger, Christoph, Desai, Rishi, Najafzadeh, Mehdi

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Secreted Klotho Attenuates Inflammation-Associated Aortic Valve Fibrosis in Senescence-Accelerated Mice P1 von Chen, Jianglei, Fan, Jun, Wang, Shirley, Sun, Zhongjie

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Development of transdiagnostic clinical risk prediction models for 12‐month onset and course of eating disorders among adolescents in the community von Mitchison, Deborah, Wang, Shirley B., Wade, Tracey, Haynos, Ann F., Bussey, Kay, Trompeter, Nora, Lonergan, Alexandra, Tame, Jack, Hay, Phillipa

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Comparison of Machine Learning Methods With Traditional Models for Use of Administrative Claims With Electronic Medical Records to Predict Heart Failure Outcomes von Desai, Rishi J, Wang, Shirley V, Vaduganathan, Muthiah, Evers, Thomas, Schneeweiss, Sebastian

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