Dose-effect meta-analysis for psychopharmacological interventions using randomised data.

Hamza, Tasnim; Furukawa, Toshi A; Orsini, Nicola; Cipriani, Andrea; Salanti, Georgia (2022). Dose-effect meta-analysis for psychopharmacological interventions using randomised data. Evidence-Based Mental Health, 25(1), pp. 1-6. BMJ Publishing Group 10.1136/ebmental-2021-300278

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OBJECTIVE

The current practice in meta-analysis of the effects of psychopharmacological interventions ignors the administered dose or restricts the analysis in a dose range. This may introduce unnecessary uncertainty and heterogeneity. Methods have been developed to integrate the dose-effect models in meta-analysis.

METHODS

We describe the two-stage and the one-stage models to conduct a dose-effect meta-analysis using common or random effects methods. We illustrate the methods on a dataset of selective serotonin reuptake inhibitor antidepressants. The dataset comprises 60 randomised controlled trials. The dose-effect is measured on an odds ratio scale and is modelled using restricted cubic splines to detect departure from linearity.

RESULTS

The estimated summary curve indicates that the probability of response increases up to 30 mg/day of fluoxetine-equivalent which results in reaching 50% probability to respond. Beyond 40 mg/day, no further increase in the response is observed. The one-stage model includes all studies, resulting in slightly less uncertainty than the two-stage model where only part of the data is analysed.

CONCLUSIONS

The dose-effect meta-analysis enables clinicians to understand how the effect of a drug changes as a function of its dose. Such analysis should be conducted in practice using the one-stage model that incorporates evidence from all available studies.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Social and Preventive Medicine (ISPM)

Graduate School:

Graduate School for Health Sciences (GHS)

UniBE Contributor:

Hamza, Tasnim A. A., Salanti, Georgia

Subjects:

600 Technology > 610 Medicine & health
300 Social sciences, sociology & anthropology > 360 Social problems & social services

ISSN:

1362-0347

Publisher:

BMJ Publishing Group

Language:

English

Submitter:

Andrea Flükiger-Flückiger

Date Deposited:

28 Jan 2022 11:57

Last Modified:

05 Dec 2022 16:05

Publisher DOI:

10.1136/ebmental-2021-300278

PubMed ID:

35042697

BORIS DOI:

10.48350/164859

URI:

https://boris.unibe.ch/id/eprint/164859

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