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Cost–utility analysis of adjunctive psychosocial therapies in bipolar disorder

Published online by Cambridge University Press:  21 July 2025

Mary Lou Chatterton*
Affiliation:
School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia Institute for Health Transformation, Deakin University, Geelong, Australia
Yong Yi Lee
Affiliation:
School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia School of Public Health, The University of Queensland, Herston, Australia Queensland Centre for Mental Health Research, Brisbane, Australia
Long Khanh-Dao Le
Affiliation:
School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
Melanie Nichols
Affiliation:
Institute for Health Transformation, Deakin University, Geelong, Australia
Michael Berk
Affiliation:
Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Deakin University, Geelong, Australia
Cathrine Mihalopoulos
Affiliation:
School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia Institute for Health Transformation, Deakin University, Geelong, Australia
*
Correspondence: Mary Lou Chatterton. Email: m.chatterton@monash.edu
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Abstract

Background

There are few economic evaluations of adjunctive psychosocial therapies for bipolar disorder.

Aims

Estimate the cost–utility of in-person psychosocial therapies for adults with bipolar disorder added to treatment as usual (TAU), from an Australian Government perspective.

Method

We developed an economic model, estimating costs in 2021 Australian dollars (A$) and outcomes using quality-adjusted life-years (QALYs) gained and disability-adjusted life-years (DALYs) averted. The model compared psychoeducation, brief psychoeducation, carer psychoeducation, cognitive–behavioural therapy (CBT) and family therapy when added to TAU (i.e. pharmacotherapy) over a year for adults (18–65 years) with bipolar disorder. The relative risk of relapse was sourced from two network meta-analyses and applied to the depressive phase in the base case. Probabilistic sensitivity analysis and one-way sensitivity analyses were conducted, assessing robustness of results.

Results

Carer psychoeducation was preferred in the base case when the willingness-to-pay (WTP) threshold is below A$1000 per QALY gained and A$1500 per DALY averted. Brief psychoeducation was preferred when WTP is between A$1000 and A$300 000 per QALY gained and A$1500 and A$450 000 per DALY averted. Family therapy was only preferred at WTP thresholds above A$300 000 per QALY gained or A$450 000 per DALY averted. In sensitivity analyses, brief psychoeducation was the preferred therapy. Psychoeducation and CBT were dominated (more costly and less effective) in base-case and sensitivity analyses.

Conclusions

Carer and brief psychoeducation were found to be the most cost-effective psychosocial therapies, supporting use as adjunctive treatments for adults with bipolar disorder and their families in Australia.

Information

Type
Paper
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of Royal College of Psychiatrists
Figure 0

Table 1 Intervention descriptions and effect sizes

Figure 1

Table 2 Input parameters and uncertainty ranges

Figure 2

Table 3 Results of base-case analyses for the outcome of quality-adjusted life-years (QALYs) gained

Figure 3

Fig. 1 Cost-effectiveness plane for base-case analyses using quality-adjusted life-years (QALYs) gained as the outcome measure. The cost-effectiveness plane displays simulations across a four-quadrant graph by the difference in cost and the difference in outcomes. Points falling in the upper right quadrant represent a scenario where the intervention is more costly and more effective. Points falling in the lower right quadrant represent the scenario where the intervention is less costly and more effective, also known as dominant. While not shown here, any iterations falling in the lower left quadrant would be indicative of an intervention being less costly and less effective than the comparator. Any points falling in the upper left quadrant would be indicative of the intervention being more costly and less effective than the comparator, also referred to as the intervention being dominated.

Figure 4

Fig. 2 Cost-effectiveness plane for base-case analyses using disability-adjusted life-years (DALYs) averted as the outcome measure. The cost-effectiveness plane displays simulations across a four-quadrant graph by the difference in cost and the difference in outcomes. Points falling in the upper right quadrant represent a scenario where the intervention is more costly and more effective. Points falling in the lower right quadrant represent the scenario where the intervention is less costly and more effective, also known as dominant. While not shown here, any iterations falling in the lower left quadrant would be indicative of an intervention being less costly and less effective than the comparator. Any points falling in the upper left quadrant would be indicative of the intervention being more costly and less effective than the comparator, also referred to as the intervention being dominated.

Figure 5

Fig. 3 Cost-effectiveness acceptability frontier for base case analyses using quality-adjusted life-years (QALYs) gained as the outcome measure. This acceptability frontier presents the percentage of simulations falling below a range of willingness to pay thresholds on a log scale.

Figure 6

Fig. 4 Cost-effectiveness acceptability frontier for base case analyses using diability-adjusted life-years (DALYs) averted as the outcome measure. This acceptability frontier presents the percentage of simulations falling below a range of willingness to pay thresholds on a log scale.

Figure 7

Table 4 Results of base-case analyses for the outcome of disability-adjusted life-years (DALYs) averted

Figure 8

Table 5 Results of sensitivity analyses for the outcome of quality-adjusted life-years (QALYs) gained

Figure 9

Table 6 Results of sensitivity analyses for the outcome of disability-adjusted life-years (DALYs) averted

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