Multiple outcomes in clinical research lead to logical and statistical challenges. For any area of physical or psychological health, a single study might include multiple related outcomes analyzed in multiple ways, leading to multiple numerical results. Using examples from the Multiple Data Sources (MUDS) study, Dr. Evan Mayo-Wilson discussed the consequences of “multiplicity” for clinical investigators, systematic reviews and guideline developers, and clinical decision-makers. He highlighted some potential solutions to these challenges, including prospective registration and core outcome sets.
Dr. Mayo-Wilson is an Assistant Scientist in the Department of Epidemiology at the Johns Hopkins Bloomberg School of Public Health. His research centers on evaluations of health and social interventions, particularly methods for conducting, reporting, and synthesizing clinical trials. He is a core faculty member in the Center for Clinical Trials and Evidence Synthesis, the Center for Drug Safety and Effectiveness, and the Center of Excellence in Regulatory Science and Innovation.
Dr. Mayo-Wilson has contributed to multiple guidelines for reporting research, including the Consolidated Standards of Reporting Trials Extension for Social and Psychological Interventions (CONSORT-SPI) and the American Psychological Association Journal Article Reporting Standards (JARS). He is an author of National Institute for Health and Care Excellence (NICE, UK) guidelines for the identification and management of social anxiety disorder, bipolar disorder, and psychosis.