Journal article : Review
Women and psychosis: a guide to evidence-based, hormone-informed care
- Abstract:
- Psychosis is associated with sex differences that are rarely considered in routine care. Oestrogen exerts protective effects, with symptom exacerbation and increased relapse risk occurring during low-oestrogen states, such as perimenstruation, postpartum, and menopause transition. Antipsychotic pharmacokinetics and response vary by sex and hormonal status, with premenopausal women requiring lower doses, and postmenopausal women showing reduced treatment efficacy. Antipsychotic-induced hyperprolactinaemia can suppress endogenous oestrogen, compounding both mental and physical health risks. Despite this, treatment guidelines remain largely sex neutral. This Review outlines the role of ovarian hormones in psychosis and offers practical considerations to support the first steps towards implementing hormone-informed care, providing a conceptual framework to guide clinical decision making with the aim of improving outcomes for women with psychosis across the lifespan. Key recommendations include thorough assessment of hormonal status, sex-specific prescribing, and the judicious use of oestrogen-based interventions such as hormonal contraception, hormone therapy, and oestrogen receptor modulators.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
-
-
(Preview, Accepted manuscript, pdf, 718.0KB, Terms of use)
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- Publisher copy:
- 10.1016/s2215-0366(26)00016-7
Authors
+ Medical Research Council
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- Funder identifier:
- https://ror.org/03x94j517
- Grant:
- MR/W015943/2
- Publisher:
- Elsevier
- Journal:
- Lancet Psychiatry More from this journal
- Publication date:
- 2026-03-24
- Acceptance date:
- 2026-01-13
- DOI:
- EISSN:
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2215-0374
- ISSN:
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2215-0366
- Language:
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English
- Subtype:
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Review
- Pubs id:
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2394915
- Local pid:
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pubs:2394915
- Deposit date:
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2026-03-25
- ARK identifier:
Terms of use
- Copyright holder:
- Elsevier Ltd
- Copyright date:
- 2026
- Rights statement:
- © 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
- Notes:
- The author accepted manuscript (AAM) of this paper has been made available under the University of Oxford's Open Access Publications Policy, and a CC BY public copyright licence has been applied.
- Licence:
- CC Attribution (CC BY)
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