Intended for healthcare professionals

CCBYNC Open access
Research

Off-label indications for antidepressants in primary care: descriptive study of prescriptions from an indication based electronic prescribing system

BMJ 2017; 356 doi: https://doi.org/10.1136/bmj.j603 (Published 21 February 2017) Cite this as: BMJ 2017;356:j603
  1. Jenna Wong, PhD candidate1,
  2. Aude Motulsky, researcher1 2,
  3. Michal Abrahamowicz, James McGill professor1,
  4. Tewodros Eguale, associate professor3,
  5. David L Buckeridge, associate professor1,
  6. Robyn Tamblyn, professor1
  1. 1Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montréal, Canada
  2. 2Centre de recherche du Centre hospitalier de l’Université de Montréal, School of Public Health, University of Montréal, Montréal, Canada
  3. 3Massachusetts College of Pharmacy and Health Sciences University, Boston, MA, USA
  1. Correspondence to: J Wong jenna.wong{at}mail.mcgill.ca
  • Accepted 18 January 2017

Abstract

Objective To examine off-label indications for antidepressants in primary care and determine the level of scientific support for off-label prescribing.

Design Descriptive study of antidepressant prescriptions written by primary care physicians using an indication based electronic prescribing system.

Setting Primary care practices in and around two major urban centres in Quebec, Canada.

Participants Patients aged 18 years or older who visited a study physician between 1 January 2003 and 30 September 2015 and were prescribed an antidepressant through the electronic prescribing system.

Main outcome measures Prevalence of off-label indications for antidepressant prescriptions by class and by individual drug. Among off-label antidepressant prescriptions, the proportion of prescriptions in each of the following categories was measured: strong evidence supporting use of the prescribed drug for the respective indication; no strong evidence for the prescribed drug but strong evidence supporting use of another drug in the same class for the indication; or no strong evidence supporting use of the prescribed drug and all other drugs in the same class for the indication.

Results 106 850 antidepressant prescriptions were written by 174 physicians for 20 920 adults. By class, tricyclic antidepressants had the highest prevalence of off-label indications (81.4%, 95% confidence interval, 77.3% to 85.5%), largely due to a high off-label prescribing rate for amitriptyline (93%, 89.6% to 95.7%). Trazodone use for insomnia was the most common off-label use for antidepressants, accounting for 26.2% (21.9% to 30.4%) of all off-label prescriptions. For only 15.9% (13.0% to 19.3%) of all off-label prescriptions, the prescribed drug had strong scientific evidence for the respective indication. For 39.6% (35.7% to 43.2%) of off-label prescriptions, the prescribed drug did not have strong evidence but another antidepressant in the same class had strong evidence for the respective indication. For the remaining 44.6% (40.2% to 49.0%) of off-label prescriptions, neither the prescribed drug nor any other drugs in the class had strong evidence for the indication.

Conclusions When primary care physicians prescribed antidepressants for off-label indications, these indications were usually not supported by strong scientific evidence, yet often another antidepressant in the same class existed that had strong evidence for the respective indication. There is an important need to generate and provide physicians with evidence on off-label antidepressant use to optimise prescribing decisions.

Footnotes

  • We thank Claude Dagenais (academic adviser, Faculty of Pharmacy, University of Montréal) for reviewing the manuscript and providing substantive comments.

  • Contributors: JW extracted and had full access to all of the study data and takes responsibility for the integrity of the data and the accuracy of the data analysis. JW contributed to the study design; analysis and interpretation of the data; drafting of the manuscript; and critical revision of the manuscript for important intellectual content. AM and RT contributed to the study design; analysis and interpretation of the data; and critical revision of the manuscript for important intellectual content. MA and TE contributed to the analysis and interpretation of the data; and critical revision of the manuscript for important intellectual content. DB contributed to the interpretation of the data and critical revision of the manuscript for important intellectual content. All authors read and approved the final manuscript. JW is the guarantor.

  • Funding: This study was funded by the Canadian Institutes of Health Research (CIHR; grant IOP-112675). JW is supported by the Vanier Canada Graduate Scholarship (CIHR) and the Max E Binz Fellowship (Faculty of Medicine, McGill University). MA is a James McGill professor of biostatistics at McGill University. The funders had no role in the study design; collection, analysis, interpretation of the data; writing of the manuscript; or in the decision to submit the manuscript for publication.

  • Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: support from the Canadian Institutes of Health Research for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.

  • Ethical approval: This study was approved by the McGill institutional review board.

  • Data sharing: No additional data available.

  • The lead author affirms that the manuscript is an honest, accurate, and transparent account of the study being reported, and that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

View Full Text