Relapse prevention is critical in long-term schizophrenia management. However, despite its importance, definitions of relapse vary widely across clinical trials, which makes it difficult to compare studies or interpret meta-analyses. To address this issue, a recent publication aimed to establish standardized, operational definitions of relapse to improve consistency in trial design, analysis, and interpretation.

The authors reviewed 26 randomized controlled trials published between 2012 and 2024. Only two pairs of trials used the same relapse definition, and over two-thirds of studies failed to define the required severity of illness prior to relapse. Most trials (85%) allowed relapse to be determined by clinical judgment alone (such as hospitalization or clinician opinion) without using structured symptom assessments. Relative symptom change was a common metric but has unfortunately been shown since to distort findings depending on baseline severity.

The Treatment Response and Resistance in Psychosis working group (TRRIP), comprising over 100 experts from 37 countries, developed a set of minimum and optimal criteria for relapse studies. Importantly, this group includes individuals with lived experience. These span pre-baseline illness, baseline stability, and relapse thresholds. Recommendations include the use of validated symptom scales (e.g., PANSS), absolute increases in symptom severity (not percent change), a minimum 12-week baseline stability period, and a 7-day symptom duration threshold for relapse unless immediate intervention is required. A reporting checklist accompanies the criteria to facilitate transparency and cross-study comparability.

For clinicians and researchers, these consensus criteria offer a structured framework to improve the rigor and reproducibility of relapse prevention studies and, over time, may help refine treatment algorithms, inform regulatory guidance, and improve generalizability of results to clinical practice. .

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Reference: Howes OD et al. Am J Psychiatry. Epub ahead of print. Abstract