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Figure.
Percentage of Antidepressant Prescriptions for Depression by Pharmaceutical Class, 2006-2015
Percentage of Antidepressant Prescriptions for Depression by Pharmaceutical Class, 2006-2015

SNRI indicates serotonin-norepinephrine reuptake inhibitor; SSRI, selective serotonin reuptake inhibitor; TCA, tricyclic antidepressant.

The plots show the unadjusted percentage of antidepressant prescriptions written for depression in each calendar year by pharmacological class. The error bars represent 95% CIs that were calculated based on standard errors corrected for multilevel clustering of prescriptions using an alternating logistic regression algorithm.6 Five-year risk difference estimates in the percentage of antidepressant prescriptions for depression were obtained from a generalized linear risk difference model (with an identity link) that included a linear effect of calendar time and dummy variables for individual pharmaceutical classes, along with their interactions with calendar time. All risk-difference estimates were adjusted for patient age and sex and used an alternating logistic regression algorithm6 to account for multilevel clustering of prescriptions. As there were no missing data on patient age or sex, all prescriptions were included in the regression model.

Table.  
Treatment Indications and Off-Label Prescribing for Antidepressant Prescriptions in Quebec, Canada, 2006-2015
Treatment Indications and Off-Label Prescribing for Antidepressant Prescriptions in Quebec, Canada, 2006-2015
1.
National Center for Health Statistics. Health, United States, 2010 with special feature on death and dying. http://www.cdc.gov/nchs/data/hus/hus10.pdf. Accessed July 23, 2015.
2.
Gardarsdottir  H, Heerdink  ER, van Dijk  L, Egberts  ACG.  Indications for antidepressant drug prescribing in general practice in the Netherlands. J Affect Disord. 2007;98(1-2):109-115.
PubMedArticle
3.
Tamblyn  R, Huang  A, Kawasumi  Y,  et al.  The development and evaluation of an integrated electronic prescribing and drug management system for primary care. J Am Med Inform Assoc. 2006;13(2):148-159.
PubMedArticle
4.
Bartlett  G, Tamblyn  R, Kawasumi  Y, Poissant  L, Taylor  L.  Nonparticipation bias in health services research using data from an integrated electronic prescribing project: the role of informed consent. Acta Bioeth. 2005;11(2):145-159. http://www.scielo.cl/pdf/abioeth/v11n2/art05.pdf.Article
5.
Eguale  T, Winslade  N, Hanley  JA, Buckeridge  DL, Tamblyn  R.  Enhancing pharmacosurveillance with systematic collection of treatment indication in electronic prescribing: a validation study in Canada. Drug Saf. 2010;33(7):559-567.
PubMedArticle
6.
Carey  V, Zeger  SL, Diggle  P.  Modelling multivariate binary data with alternating logistic regressions. Biometrika. 1993;80(3):517-526. doi:10.2307/2337173.Article
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Research Letter
May 24/31, 2016

Treatment Indications for Antidepressants Prescribed in Primary Care in Quebec, Canada, 2006-2015

Author Affiliations
  • 1Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Canada
  • 2School of Pharmacy, Massachusetts College of Pharmacy and Health Sciences, Boston
JAMA. 2016;315(20):2230-2232. doi:10.1001/jama.2016.3445

Antidepressant use in the United States has increased over the last 2 decades.1 A suspected reason for this trend is that primary care physicians are increasingly prescribing antidepressants for nondepressive indications, including unapproved (off-label) indications that have not been evaluated by regulatory agencies.2 However, the frequency with which physicians prescribe antidepressants for nondepressive indications is unknown because treatment indications are rarely documented. We analyzed the prevalence of treatment indications for antidepressants and assessed temporal trends in antidepressant prescribing for depression.

Methods

This study used data from the Medical Office of the 21st Century (MOXXI) research platform.3 MOXXI is an electronic medical record (EMR) and prescribing system that has been used by primary care physicians in community-based, fee-for-service practices around 2 major urban centers in Quebec, Canada. During the study period, approximately 185 physicians (25% of eligible) and 100 000 patients (30% of all who visited a MOXXI physician) gave informed consent to use the EMR and have their information used for research purposes. Compared with nonconsenters, MOXXI physicians were younger and MOXXI patients were older with more health complexities.4

This study included all prescriptions written for adults between January 1, 2006, and September 30, 2015, for all antidepressants except monoamine oxidase inhibitors. Physicians had to document at least 1 treatment indication per prescription using a drop-down menu containing a list of indications or by typing the indication(s). In a validation study, these indications had excellent sensitivity (98.5%) and high positive predictive value (97.0%).5 Prescriptions were classified as on-label or off-label depending on whether the drug was approved for the indication by Health Canada or the US Food and Drug Administration by September 2015. Temporal trends in antidepressant prescribing for depression were measured using generalized linear risk difference models for binary outcomes, with an identity link. A linear effect of calendar time (in years) was modeled on the probability of antidepressant prescribing for depression, adjusted for patient age and sex and accounting for multilevel clustering of prescriptions using an alternating logistic regression algorithm.6 All statistical analyses were conducted using SAS (SAS Institute) software, version 9.4. This study was approved by the McGill institutional review board.

Results

During the study period, 101 759 antidepressant prescriptions (5.9% of all prescriptions) were written by 158 physicians for 19 734 patients. Only 55.2% of antidepressant prescriptions were indicated for depression. Physicians also prescribed antidepressants for anxiety disorders (18.5%), insomnia (10.2%), pain (6.1%) and panic disorders (4.1%) (Table). For these indications, respectively, the most frequently prescribed antidepressants were citalopram (29.5% of prescriptions for the indication), trazodone (76.6%), amitriptyline (65.1%), and paroxetine (35.9%).

For 29.4% of all antidepressant prescriptions (65.6% of prescriptions not for depression), physicians prescribed a drug for an off-label indication, especially insomnia and pain. Physicians also prescribed antidepressants for several indications that were off-label for all antidepressants, including migraine, vasomotor symptoms of menopause, attention-deficit/hyperactivity disorder, and digestive system disorders (Table).

Between 2006 and 2015, the percentage of antidepressants prescribed for depression decreased significantly, with an adjusted 5-year risk difference of −9.73% (95% CI, −11.86% to −7.61%) for serotonin-norepinephrine reuptake inhibitors, −3.96% (95% CI, −5.33% to −2.59%) for selective serotonin reuptake inhibitors, and −2.99% (95% CI, −4.90% to −1.08%) for tricyclic antidepressants (Figure). However, the percentage of other antidepressants (especially mirtazapine) prescribed for depression increased significantly, with an adjusted 5-year risk difference of 2.36% (95% CI, 0.32% to 4.40%).

Discussion

Between 2006 and 2015, primary care physicians in Quebec commonly and increasingly prescribed antidepressants for nondepressive indications. When physicians prescribed antidepressants for insomnia and pain, they often prescribed antidepressants off-label.

The study was limited by a selective patient population and a small number of prescribers from 1 Canadian province. However, this is the first study to our knowledge to describe the prevalence of treatment indications for antidepressants using validated, physician-documented treatment indications recorded at the point of prescribing. The findings indicate that the mere presence of an antidepressant prescription is a poor proxy for depression treatment, and they highlight the need to evaluate the evidence supporting off-label antidepressant use.

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Article Information
Section Editor: Jody W. Zylke, MD, Deputy Editor.

Corresponding Author: Jenna Wong, MSc, Faculty of Medicine, Clinical and Health Informatics Research Group, Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, 1140 Pine Ave W, Montreal, Quebec, H3A 1A3 (jenna.wong@mail.mcgill.ca).

Author Contributions: Dr Tamblyn and Ms Wong had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Wong, Motulsky, Tamblyn.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Wong.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Wong, Abrahamowicz.

Obtained funding: Wong, Tamblyn.

Administrative, technical, or material support: Tamblyn.

Study supervision: Tamblyn.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.

Role of the Funder/Sponsor: The funding agencies had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript, and decision to submit the manuscript for publication.

References
1.
National Center for Health Statistics. Health, United States, 2010 with special feature on death and dying. http://www.cdc.gov/nchs/data/hus/hus10.pdf. Accessed July 23, 2015.
2.
Gardarsdottir  H, Heerdink  ER, van Dijk  L, Egberts  ACG.  Indications for antidepressant drug prescribing in general practice in the Netherlands. J Affect Disord. 2007;98(1-2):109-115.
PubMedArticle
3.
Tamblyn  R, Huang  A, Kawasumi  Y,  et al.  The development and evaluation of an integrated electronic prescribing and drug management system for primary care. J Am Med Inform Assoc. 2006;13(2):148-159.
PubMedArticle
4.
Bartlett  G, Tamblyn  R, Kawasumi  Y, Poissant  L, Taylor  L.  Nonparticipation bias in health services research using data from an integrated electronic prescribing project: the role of informed consent. Acta Bioeth. 2005;11(2):145-159. http://www.scielo.cl/pdf/abioeth/v11n2/art05.pdf.Article
5.
Eguale  T, Winslade  N, Hanley  JA, Buckeridge  DL, Tamblyn  R.  Enhancing pharmacosurveillance with systematic collection of treatment indication in electronic prescribing: a validation study in Canada. Drug Saf. 2010;33(7):559-567.
PubMedArticle
6.
Carey  V, Zeger  SL, Diggle  P.  Modelling multivariate binary data with alternating logistic regressions. Biometrika. 1993;80(3):517-526. doi:10.2307/2337173.Article
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