Depressive disorders: treatment failures and poor prognosis over the last 50 years
Open accessAbstract
Depression like many diseases is pleiotropic but unlike cancer and Alzheimer's disease for example, is still largely stigmatized and falls into the dark shadows of human illness. The failure of depression to be in the spotlight for successful treatment options is inherent in the complexity of the disease(s), flawed clinical diagnosis, overgeneralization of the illness, inadequate and biased clinical trial design, restrictive and biased inclusion/exclusion criteria, lack of approved/robust biomarkers, expensive imaging technology along with few advances in neurobiological hypotheses in decades. Clinical trial studies summitted to the regulatory agencies ( FDA / EMA ) for approval, have continually failed to show significant differences between active and placebo. For decades, we have acknowledged this failure, despite vigorous debated by all stakeholders to provide adequate answers to this escalating problem, with only a few new antidepressants approved in the last 20 years with equivocal efficacy, little improvement in side effects or onset of efficacy. It is also clear that funding and initiatives for mental illness lags far behind other life‐treating diseases. Thus, it is no surprise we have not achieved much success in the last 50 years in treating depression, but we are accountable for the many failures and suboptimal treatment. This review will therefore critically address where we have failed and how future advances in medical science offers a glimmer of light for the patient and aid our future understanding of the neurobiology and pathophysiology of the disease, enabling transformative therapies for the treatment of depressive disorders.
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A recent systematic review and meta-analysis indicates reduced risk of relapse and recurrence in patients remitted from a depressive episode when psychotherapy is sequentially integrated with antidepressant medication.
“The results of a recent systematic review and meta-analysis indicate reduced risk of relapse and recurrence in patients remitted from a depressive episode when psychotherapy is sequentially integrated with antidepressant medication. 554”
From Time for united action on depression: a Lancet–World Psychiatric Association Commission (2022) · cites this paper as [554]
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- Authors
- Blackburn, T. P.
- Affiliations
- TPBioVentures Hoboken New Jersey USA
- Corresponding author
- Blackburn, Thomas P.
- ORCID
- Blackburn, Thomas P.
- Venue
- Pharmacology Research & Perspectives
- Publisher
- Wiley
- Published
- 2019-05-03
- Volume
- 7
- Issue
- 3
- Pages
- e00472-e00472
- ISSN
- 2052-1707 (ISSN-L)
- PMC
- PMC6498411
- OpenAlex
- W2943320709
- Cited by
- 136
- References
- 116
- Citations by year
- 2026: 15 · 2025: 22 · 2024: 22 · 2023: 29 · 2022: 17 · 2021: 18 · 2020: 10 · 2019: 3
- FWCI
- 1.53
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Pharmacology Research & Perspectives (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Social Sciences › Psychology › Clinical Psychology › Psychological Treatments and Disorders
- Social Sciences › Psychology › Social Psychology › Mental Health Treatment and Access
- Keywords
- depressive disorders, antidepressant treatment failure, antidepressant efficacy, placebo response, biomarkers, neurobiology of depression, depression pathophysiology
- MeSH terms
- Antidepressive Agents, Clinical Trials as Topic, Depressive Disorder, Humans, Prognosis, Treatment Failure, Molecular Targeted Therapy
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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