‘Smart’ prescribing of antidepressant medications?

The potential of an interactive point-of-care smartphone application to aid in prescribing antidepressant medications was discussed at this APA Online 2022 session, involving earlier use of polypharmacy and shorter medication trials.

Training the prescribers

Professor Philip Muskin (Columbia University, USA) began by explaining that although antidepressant drugs are often prescribed by non-specialists, such as primary care physicians/general practitioners, psychiatry teaching given as part of primary care programs is frequently considered sub-optimal.1 This leaves doctors poorly equipped to make treatment decisions or ask some of the more difficult questions around prescribing such as those regarding sexual dysfunction or suicidal ideation.2 Education and training may need to be a rolling programme, rather than a one-off event, to show benefit.3

Education and training may need to be a rolling programme

Health technologies offer the potential to help solve health-related problems and improve quality of life, but it is important they are complemented by good staff training and effective organization of the associated health services.4 The mental health-related software market is rapidly expanding, but applications often have no mental health care professional involvement in their development.5

 

Challenging prescribing assumptions

Dr John Mann (Columbia University, USA) discussed the use of sequenced 6-week antidepressant medication trials in the pivotal STAR*D study. The cumulative remission rate was 33% for the 1st step and then 57%, 63% and 67% after the 2nd, 3rd and 4th steps respectively.6 The response rate dropped markedly after the 2nd medication trial, and he suggested that for those patients either their depression became harder to treat over time or that their disease was always going to be harder to treat. If the first option is correct then treating patients effectively as soon as possible is crucial, especially as early responders also had lower relapse rates.6

Treating patients effectively as soon as possible is crucial

He suggested that the STAR*D study has led to the assumptions that a sequence of 6-week long medication trials and use of monotherapy are optimal. This is in contrast with the approach used in hypertension, involving multiple agents and specific blood pressure targets as effectiveness measures.

 

Polypharmacy and shorter medication trials

Dr Mann proposed that antidepressant treatment should move towards polypharmacy and shorter medication trials. Combinations of antidepressant medications can have a higher response rate than single agents,7 as the effects of different classes are potentially additive, and adverse events appear not to be significantly greater. There is also the option of augmenting with a non-antidepressant such as an anti-psychotic.

Move towards polypharmacy and shorter medication trials

He also challenged the assumption that a 6-week trial of an antidepressant medication is required before considering other options. This is based on the statistical separation of active drug response from placebo. If instead ‘responders’ are compared to ‘non-responders’ then benefit starts to be seen within two weeks. In a meta-analysis of over 6,500 patients, receiving different classes of antidepressants, only 4% of patients who didn’t improve within the first two weeks remitted at week 4.8

 

Partnering technology and evidence-based care

Dr Ravi Shah (Columbia University, USA) presented the ‘Accelerated Sequential Antidepressant Protocol’ (ASAP) that has been developed using these principles of polypharmacy and shorter medication trials. After the first step the protocol proceeds to medications that target more than one neurotransmitter system or two combinations of medications with different treatment targets, with 3-week long sequenced treatment steps.

Aim is to aid decision-making at the point of care

Psychiatrists from Columbia University partnered with a technology start-up company to build an interactive point-of-care smartphone application to disseminate the ASAP protocol.9 It provides evidence-based treatment algorithms for psychiatric outpatient management of depression including built-in calculators for clinical rating scales. The aim is to aid decision-making at the point of care, especially targeting primary care physicians and early career trainees. The next steps include analysing outcome data from protocol use, integration into electronic medical records and building modules for other psychiatric conditions.

Our correspondent’s highlights from the symposium are meant as a fair representation of the scientific content presented. The views and opinions expressed on this page do not necessarily reflect those of Lundbeck.

References

  1. Leigh H, Mallios R, Stewart D. Teaching psychiatry in primary care residencies: do training directors of primary care and psychiatry see eye to eye? Acad Psychiatry 2008;32(6):504-9.
  2. Epstein SA, Hooper LM, Weinfurt KP, DePuy V, Cooper LA, Harless WG, Tracy CM. Primary care physicians' evaluation and treatment of depression: Results of an experimental study using video vignettes. Med Care Res Rev 2008;65(6):674-95.
  3. Mann JJ, Michel CA, Auerbach RP. Improving Suicide Prevention Through Evidence-Based Strategies: A Systematic Review. Am J Psychiatry 2021;178(7):611-24.
  4. https://www.who.int/europe/news-room/fact-sheets/item/health-technologies
  5. Sucala M, Cuijpers P, Muench F, et al. Anxiety: There is an app for that. A systematic review of anxiety apps. Depress Anxiety 2017;34(6):518-25.
  6. Gaynes BN, Rush AJ, Trivedi MH, et al. The STAR*D study: treating depression in the real world. Cleve Clin J Med 2008;75(1):57-66.
  7. Henssler J, Alexander D, Schwarzer G, et al. Combining Antidepressants vs Antidepressant Monotherapy for Treatment of Patients With Acute Depression: A Systematic Review and Meta-analysis. JAMA Psychiatry 2022;79(4):300-12.
  8. Szegedi A, Jansen WT, van Willigenburg APP, et al. Early improvement in the first 2 weeks as a predictor of treatment outcome in patients with major depressive disorder: a meta-analysis including 6562 patients. J Clin Psychiatry 2009;70(3):344-53.
  9. https://www.avomd.io/columbiapsychpathways