Progression from unipolar depression to schizophrenia.
Abstract
OBJECTIVE: To examine progression from unipolar depression (UD) to schizophrenia and to identify groups of UD patients at elevated risk for progression. METHOD: Historical prospective cohort study using data from Danish national registers. The sample included 71 932 individuals who received a diagnosis of UD in Denmark between January 1, 1995, and May 31, 2013. Analyses were conducted using Kaplan-Meier estimates and Cox regressions. RESULTS: The 18.5-year cumulative incidence of schizophrenia was 5.5% in women and 8.4% in men. The strongest predictors of progression included younger age (adjusted hazard ratio (AHR) for individuals 18-24 vs. 40+ = 7.42, 95% confidence interval = [6.29, 8.74]), psychotic symptoms at index UD diagnosis (AHR = 3.70 [3.18, 4.31]), previous disorder with psychotic features (AHR = 3.71 [3.31, 4.16]), and previous illicit substance use disorder (AHR = 1.66 [1.40, 1.97]). Groups of UD patients with different combinations of risk factors had elevated risk for progression, with 10-year cumulative incidences ranging from 9% to 62%. To conclude, at the time of UD diagnosis, the strongest risk factors for progression to schizophrenia include male sex, younger age, past/current psychotic symptoms, and illicit substance use disorders. These clinical predictors may aid in targeting monitoring for schizophrenia among patients with UD.
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Many patients who eventually receive a diagnosis of schizophrenia or bipolar disorder have previously received treatment for other and less severe mental disorders.
“In fact, many patients who eventually receive a diagnosis of schizophrenia or bipolar disorder have previously received treatment for other and less severe mental disorders.”
From Predicting Diagnostic Progression to Schizophrenia or Bipolar Disorder via Machine Learning (2025) · cites this paper as [9]
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Musliner, K. L., Mortensen, P. B., McGrath, J. J., Suppli, N. P., Hougaard, D. M., Bybjerg-Grauholm, J., Bækvad-Hansen, M., Andreassen, O., Pedersen, C. B., Pedersen, M. G., et al. (2019) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2018.4166 · Cited by 108 · see citing works
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Predicting Diagnostic Progression to Schizophrenia or Bipolar Disorder via Machine Learning
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- Authors
- Musliner, K. L., Munk‐Olsen, T., Mors, O., & Østergaard, S. D.
- Affiliations
- Aarhus University (DK)
- Aarhus University Hospital (DK)
- Corresponding author
- Musliner, Katherine L.
- Venue
- Acta Psychiatrica Scandinavica
- Publisher
- Wiley
- Published
- 2016-11-04
- Volume
- 135
- Issue
- 1
- Pages
- 42-50
- ISSN
- 0001-690X (ISSN-L)
- 1600-0447
- OpenAlex
- W2546610740
- Cited by
- 21
- References
- 32
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 2 · 2023: 1 · 2022: 2 · 2021: 4 · 2020: 4 · 2019: 2 · 2018: 3
- FWCI
- 1.48
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Acta Psychiatrica Scandinavica (publishedVersion)
- PubMed (publishedVersion)
- Scopus (Elsevier) (submittedVersion)
- Funders
- Lundbeckfonden
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Health Sciences › Medicine › Psychiatry and Mental health › Bipolar Disorder and Treatment
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Keywords
- major depressive disorder, schizophrenia, risk factors, psychotic symptoms, age, sex differences, cumulative incidence, depression monitoring
- MeSH terms
- Adolescent, Adult, Aged, Denmark, Major Depressive Disorder, Depressive Disorder, Major, Female, Humans, Male, Middle Aged, Prospective Studies, Registries, Risk Factors, Schizophrenia, Incidence, Proportional Hazards Models, Disease Progression, Kaplan-Meier Estimate, Young Adult
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