One step closer to personalised prescribing of antidepressants: using real-world data together with patients and clinicians' preferences
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Antidepressants for many decades have been shown to be an effective treatment for depressive disorder.1 Approximately 80% of people with depressive disorder in the UK will have been prescribed an antidepressant within the first year following diagnosis.2 Indeed, about 71 million prescriptions for antidepressants were issued in the UK in 2018—nearly twice as many as the previous decade.3 However, there remain important questions around the tolerability of antidepressant medication. It is well recognised that the side effects of antidepressants can be extremely debilitating and that unwanted symptoms associated with these medications are one of the main reasons for patients discontinuing treatment.4 There are many different antidepressant drugs available, recommended by guidelines, and thus commonly used in real-world clinical practice in patients with depressive disorder across the world. A large number of different side effects of antidepressant medication from different patient populations have been reported in randomised controlled trails.5 While we now have evidence from randomised trials informing us which specific side effects are experienced by patients taking antidepressants, and the frequency of these specific individual side effects, we have limited evidence from real-world patients as to which …
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Observational studies were excluded to reduce heterogeneity, but they can provide more real-world evidence on antidepressant effectiveness.
“We excluded obser vational studies to decrease the hetero geneity in the network metaanalysis; however, obser vational studies can provide more information about realworld evidence on antidepressant effectiveness in the studied population group.46”
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- Authors
- Kernot, C., Tomlinson, A., Chevance, A., & Cipriani, A.
- Affiliations
- Oxford Health NHS Foundation Trust (GB)
- University of Oxford (GB)
- Sorbonne Paris Cité (FR)
- Corresponding author
- Cipriani, Andrea
- Venue
- Evidence Based Mental Health
- Publisher
- BMJ
- Published
- 2019-07-13
- Volume
- 22
- Issue
- 3
- Pages
- 91-92
- ISSN
- 1362-0347 (ISSN-L)
- 1468-960X
- PMC
- PMC10270394
- OpenAlex
- W2959847229
- Cited by
- 13
- References
- 9
- Citations by year
- 2024: 1 · 2021: 2 · 2020: 10
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Evidence-Based Mental Health (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- HAL (submittedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- NIHR
- Topics
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
- Social Sciences › Psychology › Social Psychology › Mental Health Treatment and Access
- Keywords
- antidepressants, real-world data, patient preferences, clinician preferences, depression treatment
- MeSH terms
- Antidepressive Agents, Depressive Disorder, Humans, Drug Prescriptions, Precision Medicine
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