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Cost-effective treatments are needed to reduce the burden of depression. One way to improve the cost-effectiveness of psychotherapy might be to increase session frequency, but keep the total number of sessions constant.
To evaluate the cost-effectiveness of twice-weekly compared with once-weekly psychotherapy sessions after 12 months, from a societal perspective.
An economic evaluation was conducted alongside a randomised controlled trial comparing twice-weekly versus once-weekly sessions of psychotherapy (cognitive–behavioural therapy or interpersonal psychotherapy) for depression. Missing data were handled by multiple imputation. Statistical uncertainty was estimated with bootstrapping and presented with cost-effectiveness acceptability curves.
Differences between the two groups in depressive symptoms, physical and social functioning, and quality-adjusted life-years (QALY) at 12-month follow-up were small and not statistically significant. Total societal costs in the twice-weekly session group were higher, albeit not statistically significantly so, than in the once-weekly session group (mean difference €2065, 95% CI −686 to 5146). The probability that twice-weekly sessions are cost-effective compared with once-weekly sessions was 0.40 at a ceiling ratio of €1000 per point improvement in Beck Depression Inventory-II score, 0.32 at a ceiling ratio of €50 000 per QALY gained, 0.23 at a ceiling ratio of €1000 per point improvement in physical functioning score and 0.62 at a ceiling ratio of €1000 per point improvement in social functioning score.
Based on the current results, twice-weekly sessions of psychotherapy for depression are not cost-effective over the long term compared with once-weekly sessions.
For the analysis of clinical effects, multiple imputation (MI) of missing data was shown to be unnecessary when using longitudinal linear mixed-models (LLM). It remains unclear whether this also applies to cost estimates from trial-based economic evaluations, that are generally right-skewed. Therefore, this study aimed to assess whether MI is required prior to LLM when analyzing longitudinal cost-effectiveness data.
Two-thousand complete datasets were simulated containing five time points. Incomplete datasets were generated with 10 percent, 25 percent, and 50 percent missing data in costs and effects, assuming a Missing At Random (MAR) mechanism. Statistical performance of six different methodological strategies was compared in terms of empirical bias (EB), root-mean-squared error (RMSE), and coverage rate (CR). Six strategies were compared: (i) LLM (LLM), (ii) MI prior to LLM (MI-LLM), (iii) mean imputation prior to LLM (M-LLM), (iv) complete-case analysis prior to seemingly unrelated regression (CCA-SUR), (v) MI prior to SUR (MI-SUR), and (vi) mean imputation prior to SUR (M-SUR). To evaluate the impact on the probability of cost-effectiveness at different willingness-to-pay [WTPs] thresholds, cost-effectiveness analyses were performed by applying the six strategies to two empirical datasets with 9% and 50% of missing data, respectively.
For costs and effects, LLM, MI-LLM, and MI-SUR performed better than M-LLM, CCA-SUR, and M-SUR, as indicated by smaller EBs and RMSEs, as well as CRs closer to the nominal levels of 0.95. However, even though LLM, MI-LLM, and MI-SUR performed equally well for effects, MI-LLM and MI-SUR were found to perform better than LLM for costs at 10 percent and 25 percent missing data. At 50 percent missing data, all strategies resulted in relatively high EBs and RMSEs for costs. In both empirical datasets, LLM, MI-LLM, and MI-SUR all resulted in similar probabilities of cost-effectiveness at different WTPs.
When opting for using LLM for analyzing trial-based economic evaluation data, researchers are advised to multiply impute missing values first. Otherwise, MI-SUR may also be used.
Patients’ EQ-5D health states are preferably valued using country-specific value sets. If value sets are not available, crosswalks may be used to estimate utility values. However, up until now the impact of using crosswalks instead of value sets on cost-utility outcomes remains unclear.
Trial-based cost-utility data were simulated for four conditions (depression, low back pain, osteoarthritis, and cancer), three levels of disease severity (mild, moderate, and severe), and three treatment effect sizes (small, medium, and large), resulting in 36 scenarios. For all scenarios, utility values were estimated using four scoring methods (EQ-5D-3L value set, EQ-5D-5L value set, 3L-to-5L crosswalk, and 5L-to-3L crosswalk) for three countries (the Netherlands, the United States, and Japan). Mean utility values, quality-adjusted life years (QALYs), incremental QALYs, and cost-utility outcomes (incremental cost-effectiveness ratios [ICER], probabilities of cost-effectiveness at willingness-to-pay [WTP] thresholds) were compared between value sets and crosswalks.
Differences between value sets and crosswalks ranged from -0.33 to 0.13 for mean utility values, from -0.18 to 0.13 for QALYs, and from -0.01 to 0.08 for incremental QALYs. Because of the small differences in incremental QALYs, ICERs between scoring methods were considerably different. For small effect sizes, at a WTP of EUR 20,000/QALY gained, the largest difference in the probability of cost-effectiveness was found for moderate cancer between the 5L value set and 3L-to-5L crosswalk (difference 0.63) using Japanese valuations. For medium effect sizes, the largest difference was found for mild cancer between the 3L value set and the 5L-to-3L crosswalk (difference 0.06) using Japanese valuations. For large effect sizes, the largest difference was found for mild osteoarthritis between the 3L value set and 5L-to-3L crosswalk (difference 0.08) using Japanese valuations.
Our findings indicate that reimbursement decisions may change depending on the use of crosswalks. Crosswalks are justifiable in absence of country-specific value sets but should not be considered a sustainable alternative for value sets.
It is unclear what session frequency is most effective in cognitive–behavioural therapy (CBT) and interpersonal psychotherapy (IPT) for depression.
Compare the effects of once weekly and twice weekly sessions of CBT and IPT for depression.
We conducted a multicentre randomised trial from November 2014 through December 2017. We recruited 200 adults with depression across nine specialised mental health centres in the Netherlands. This study used a 2 × 2 factorial design, randomising patients to once or twice weekly sessions of CBT or IPT over 16–24 weeks, up to a maximum of 20 sessions. Main outcome measures were depression severity, measured with the Beck Depression Inventory-II at baseline, before session 1, and 2 weeks, 1, 2, 3, 4, 5 and 6 months after start of the intervention. Intention-to-treat analyses were conducted.
Compared with patients who received weekly sessions, patients who received twice weekly sessions showed a statistically significant decrease in depressive symptoms (estimated mean difference between weekly and twice weekly sessions at month 6: 3.85 points, difference in effect size d = 0.55), lower attrition rates (n = 16 compared with n = 32) and an increased rate of response (hazard ratio 1.48, 95% CI 1.00–2.18).
In clinical practice settings, delivery of twice weekly sessions of CBT and IPT for depression is a way to improve depression treatment outcomes.
Objectives: Major depression is common in elderly patients. Interpersonal psychotherapy (IPT) is a potentially effective treatment for depressed elderly patients. The objective of this study was to evaluate the cost-effectiveness of IPT delivered by mental health workers in primary care practices, for depressed patients 55 years of age and older identified by screening, in comparison with care as usual (CAU).
Methods: We conducted a full economic evaluation alongside a randomized controlled trial comparing IPT with CAU. Outcome measures were depressive symptoms, presence of major depression, and quality of life. Resource use was measured from a societal perspective over a 12-month period by cost diaries. Multiple imputation and bootstrapping were used to analyze the data.
Results: At 6 and 12 months, the differences in clinical outcomes between IPT and CAU were small and nonsignificant. Total costs at 12 months were €5,753 in the IPT group and €4,984 in the CAU group (mean difference, €769; 95 percent confidence interval, −2,459 – 3,433). Cost-effectiveness planes indicated that there was much uncertainty around the cost-effectiveness ratios.
Conclusions: Based on these results, provision of IPT in primary care to elderly depressed patients was not cost-effective in comparison to CAU. Future research should focus on improvement of patient selection and treatments that have more robust effects in the acute and maintenance phase of treatment.
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