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Multivariate Bayesian Arm-Based Network Meta-Analysis of Pharmacological Interventions for the Treatment of Acute Bipolar Mania in Adults

Malo, PK and Bhaskarapillai, B and Kesavan, M (2022) Multivariate Bayesian Arm-Based Network Meta-Analysis of Pharmacological Interventions for the Treatment of Acute Bipolar Mania in Adults. In: Indian Journal of Psychological Medicine .

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Official URL: https://doi.org/10.1177/02537176221114392


Background: In a network meta-analysis (NMA), multiple treatments can be compared simultaneously by aggregating pieces of evidence from direct as well as indirect treatment comparisons in different randomized controlled trials (RCTs). Conventional NMA are performed using a normal approximation approach and can be applied for arm-level binary outcome data as well. This study aimed to estimate the treatment effects within a Bayesian framework using a binomial likelihood for a multivariate NMA model. Methods: The dataset consists of 57 RCTs comparing the effect of ten pharmacological drugs and a placebo for acute bipolar mania in adults. The binary outcomes of interest were treatment response and all-cause dropouts measured three weeks from the baseline. Binomial distribution was adopted for the number of events and the probability of event occurrence modeled on the logit scale. Jeffrey�s Beta prior was considered for the heterogeneity and inconsistency of standard deviation (SD) parameters. Cholesky and spherical decomposition strategies were adopted for the between-study variance�covariance matrix. Deviance information criterion (DIC) indices were computed to determine the model fit. All results pertaining to Markov chain Monte Carlo simulations and all analyses were carried out in WinBUGS software. Results: The estimated common heterogeneity SDs were similar, and the DIC values did not provide any evidence for superiority between the two decomposition strategies. The correlation (95 credible interval) between the outcomes was estimated as �0.31 (�0.71, �0.02) and �0.37 (�0.73, �0.03) for the Cholesky and spherical decompositions, respectively. Gelman�Rubin convergence statistics were stable, and Monte Carlo errors for all the parameters were around 0.005. Overall, olanzapine, paliperidone, and quetiapine were both significantly more effective and acceptable than a placebo when both the study outcomes were considered simultaneously. Conclusions: The findings favoring olanzapine, paliperidone, and quetiapine possess an excellent concordance with the one adopted in clinical practice, and the Canadian Network for Mood and Anxiety Treatments and Royal Australian and New Zealand College of Psychiatrists guidelines recommend these as first-line drugs for treating bipolar disorder. © 2022 Indian Psychiatric Society - South Zonal Branch.

Item Type: Journal Article
Publication: Indian Journal of Psychological Medicine
Publisher: SAGE Publications Ltd
Additional Information: The copyright for this article belongs to Authors.
Department/Centre: Autonomous Societies / Centres > Centre for Brain Research
Date Deposited: 29 Sep 2022 11:55
Last Modified: 29 Sep 2022 11:55
URI: https://eprints.iisc.ac.in/id/eprint/76848

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