Shanil Ebrahim1, Sheena Bance2, Abha Athale3, Cindy Malachowski4, John P A Ioannidis5. 1. Stanford Prevention Research Center, Department of Medicine, Stanford University, 1265 Welch Road, 3rd Floor, Stanford, CA 94305, USA; Meta-Research Innovation Center at Stanford (METRICS), Stanford University, 1265 Welch Road, Stanford, CA 94305, USA; Department of Clinical Epidemiology & Biostatistics, McMaster University, 1200 Main Street West, Room 2C, Hamilton, Ontario L8S 4K1, Canada; Department of Anesthesia, McMaster University, 1200 Main Street West, HSC 2U1, Hamilton, Ontario L8S 4K1, Canada; Department of Anaesthesia and Pain Medicine, Hospital for Sick Children, 555 University Ave, Toronto, Ontario M5G 1X8, Canada. 2. Department of Applied Psychology and Human Development, Ontario Institute for Studies in Education, University of Toronto, 252 Bloor Street West, Toronto, Ontario M5S 1V6, Canada. 3. Department of Rehabilitation Science, University of Toronto, 500 University Ave, Toronto, Ontario M5G 1V7, Canada. 4. Department of Health Research and Policy, Stanford University School of Medicine, Redwood Building T152, 150 Governor's Lane, Stanford, CA 94305, USA. 5. Stanford Prevention Research Center, Department of Medicine, Stanford University, 1265 Welch Road, 3rd Floor, Stanford, CA 94305, USA; Meta-Research Innovation Center at Stanford (METRICS), Stanford University, 1265 Welch Road, Stanford, CA 94305, USA; Department of Health Research and Policy, Stanford University School of Medicine, Redwood Building T152, 150 Governor's Lane, Stanford, CA 94305, USA; Department of Statistics, Stanford University School of Humanities and Sciences, 390 Serra Mall, Stanford, CA 94305, USA. Electronic address: jioannid@stanford.edu.
Abstract
OBJECTIVES: To identify the impact of industry involvement in the publication and interpretation of meta-analyses of antidepressant trials in depression. STUDY DESIGN AND SETTING: Using MEDLINE, we identified all meta-analyses evaluating antidepressants for depression published in January 2007-March 2014. We extracted data pertaining to author affiliations, conflicts of interest, and whether the conclusion of the abstract included negative statements on whether the antidepressant(s) were effective or safe. RESULTS: We identified 185 eligible meta-analyses. Fifty-four meta-analyses (29%) had authors who were employees of the assessed drug manufacturer, and 147 (79%) had some industry link (sponsorship or authors who were industry employees and/or had conflicts of interest). Only 58 meta-analyses (31%) had negative statements in the concluding statement of the abstract. Meta-analyses including an author who were employees of the manufacturer of the assessed drug were 22-fold less likely to have negative statements about the drug than other meta-analyses [1/54 (2%) vs. 57/131 (44%); P < 0.001]. CONCLUSION: There is a massive production of meta-analyses of antidepressants for depression authored by or linked to the industry, and they almost never report any caveats about antidepressants in their abstracts. Our findings add a note of caution for meta-analyses with ties to the manufacturers of the assessed products.
OBJECTIVES: To identify the impact of industry involvement in the publication and interpretation of meta-analyses of antidepressant trials in depression. STUDY DESIGN AND SETTING: Using MEDLINE, we identified all meta-analyses evaluating antidepressants for depression published in January 2007-March 2014. We extracted data pertaining to author affiliations, conflicts of interest, and whether the conclusion of the abstract included negative statements on whether the antidepressant(s) were effective or safe. RESULTS: We identified 185 eligible meta-analyses. Fifty-four meta-analyses (29%) had authors who were employees of the assessed drug manufacturer, and 147 (79%) had some industry link (sponsorship or authors who were industry employees and/or had conflicts of interest). Only 58 meta-analyses (31%) had negative statements in the concluding statement of the abstract. Meta-analyses including an author who were employees of the manufacturer of the assessed drug were 22-fold less likely to have negative statements about the drug than other meta-analyses [1/54 (2%) vs. 57/131 (44%); P < 0.001]. CONCLUSION: There is a massive production of meta-analyses of antidepressants for depression authored by or linked to the industry, and they almost never report any caveats about antidepressants in their abstracts. Our findings add a note of caution for meta-analyses with ties to the manufacturers of the assessed products.
Authors: Susan D Shenkin; Jennifer K Harrison; Tim Wilkinson; Richard M Dodds; John P A Ioannidis Journal: Age Ageing Date: 2017-09-01 Impact factor: 10.668