High‐Throughput Screening Using the Self‐Controlled Tree‐Based Scan Statistic to Identify Medications Associated With Hospitalization for Severe Acute Liver Injury
Year: 2025
Type: article
Language: en
Topic: Drug-Induced Hepatotoxicity and Protection
Authors and affiliations:
raw_author_name: Vincent Lo Re
raw_affiliation_strings: Center for Clinical Epidemiology and Biostatistics, Center for Real‐World Effectiveness and Safety of Therapeutics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine University of Pennsylvania  Philadelphia Pennsylvania USA
Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine University of Pennsylvania  Philadelphia Pennsylvania USA
Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
raw_author_name: Craig W. Newcomb
raw_affiliation_strings: Center for Clinical Epidemiology and Biostatistics, Center for Real‐World Effectiveness and Safety of Therapeutics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine University of Pennsylvania  Philadelphia Pennsylvania USA
Center for Clinical Epidemiology and Biostatistics, Center for Real-World Effectiveness and Safety of Therapeutics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
raw_author_name: Dean M. Carbonari
raw_affiliation_strings: Center for Clinical Epidemiology and Biostatistics, Center for Real‐World Effectiveness and Safety of Therapeutics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine University of Pennsylvania  Philadelphia Pennsylvania USA
Center for Clinical Epidemiology and Biostatistics, Center for Real-World Effectiveness and Safety of Therapeutics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
raw_author_name: Charles E. Leonard
raw_affiliation_strings: Center for Clinical Epidemiology and Biostatistics, Center for Real‐World Effectiveness and Safety of Therapeutics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine University of Pennsylvania  Philadelphia Pennsylvania USA
Leonard Davis Institute of Health Economics University of Pennsylvania  Philadelphia Pennsylvania USA
Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
raw_author_name: Christopher T. Rentsch
raw_affiliation_strings: Department of Medicine, Yale School of Medicine  New Haven Connecticut USA
Department of Non‐communicable Disease Epidemiology London School of Hygiene &amp; Tropical Medicine  London UK
VA Connecticut Healthcare System, US Department of Veterans Affairs  West Haven Connecticut USA
Department of Medicine, Yale School of Medicine, New Haven, Connecticut, USA
Department of Non‐communicable Disease Epidemiology London School of Hygiene &amp; Tropical Medicine London UK
VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA
raw_author_name: Judith C. Maro
raw_affiliation_strings: Department of Population Medicine Harvard Medical School and Harvard Pilgrim Healthcare Institute  Boston Massachusetts USA
Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Healthcare Institute, Boston, Massachusetts, USA