Antidepressant maintenance versus active monitoring after depression remission: a decision analysis and framework linking recurrence probability and patient preferences.

Authors

William U Meyerson, Tianxi Cai, Jordan W Smoller

Published in

Psychological medicine. Volume 56. Pages e318. Oct 06, 2026. Epub Oct 06, 2026.

Abstract

When deciding on antidepressant maintenance with clinicians, remitted patients must weigh the burdens of continued use against the benefit of less time depressed. This benefit is often inferred qualitatively from relapse-frequency data, even though expected time depressed also depends on episode duration, antidepressant re-initiation, and how evidence from highly recurrent populations applies to patients with fewer prior episodes.
We developed a health-state transition model to combine evidence on recurrence, episode duration, re-initiation, and treatment effects into expected time depressed and time taking antidepressants under maintenance versus active monitoring. Adults in remission were simulated for 5 years across groups based on depression history. We summarized the trade-off as additional antidepressant use required to avert 1 month of depression. The decision framework links this estimate to patient preferences by comparing required with acceptable use, allowing patients who expect greater consequences of relapse or experience fewer treatment burdens to consider more antidepressant use acceptable.
Maintenance efficiency varied substantially with recurrence history. Each month of depression averted required 1.5 additional years of antidepressant use among patients with 4-5 prior episodes; 2.8 years with 2-3 prior episodes, 5.1 years after one moderate-to-severe episode, and 11.8 years after one mild episode. When these trade-offs are acceptable, patients are modeled to prefer maintenance.
The model expresses the maintenance trade-off as a ratio of benefits and burdens. Preferences and clinical judgment determine for whom the ratio is acceptable. Empirical work can determine whether this improves maintenance decisions in practice.

PMID:
42834741
Bibliographic data and abstract were imported from PubMed on 06 Oct 2026.

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