Department of Health Sciences, Faculty of Earth and Life Sciences, Amsterdam Public Health Research Institute, VU University Amsterdam, Amsterdam, The Netherlands.
Department of Clinical, Neuro and Developmental Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Depress Anxiety. 2018 Mar;35(3):209-219. doi: 10.1002/da.22714. Epub 2018 Jan 12.
There is limited evidence on the cost effectiveness of Internet-based treatments for depression. The aim was to evaluate the cost effectiveness of guided Internet-based interventions for depression compared to controls.
Individual-participant data from five randomized controlled trials (RCT), including 1,426 participants, were combined. Cost-effectiveness analyses were conducted at 8 weeks, 6 months, and 12 months follow-up.
The guided Internet-based interventions were more costly than the controls, but not statistically significant (12 months mean difference = €406, 95% CI: - 611 to 1,444). The mean differences in clinical effects were not statistically significant (12 months mean difference = 1.75, 95% CI: - .09 to 3.60 in Center for Epidemiologic Studies Depression Scale [CES-D] score, .06, 95% CI: - .02 to .13 in response rate, and .00, 95% CI: - .03 to .03 in quality-adjusted life-years [QALYs]). Cost-effectiveness acceptability curves indicated that high investments are needed to reach an acceptable probability that the intervention is cost effective compared to control for CES-D and response to treatment (e.g., at 12-month follow-up the probability of being cost effective was .95 at a ceiling ratio of 2,000 €/point of improvement in CES-D score). For QALYs, the intervention's probability of being cost effective compared to control was low at the commonly accepted willingness-to-pay threshold (e.g., at 12-month follow-up the probability was .29 and. 31 at a ceiling ratio of 24,000 and 35,000 €/QALY, respectively).
Based on the present findings, guided Internet-based interventions for depression are not considered cost effective compared to controls. However, only a minority of RCTs investigating the clinical effectiveness of guided Internet-based interventions also assessed cost effectiveness and were included in this individual-participant data meta-analysis.
目前针对基于互联网的抑郁症治疗方法的成本效益的证据有限。本研究旨在评估与对照组相比,基于互联网的有指导干预治疗抑郁症的成本效益。
对 5 项随机对照试验(RCT)的个体参与者数据(共 1426 名参与者)进行了合并。在 8 周、6 个月和 12 个月的随访时进行成本效益分析。
与对照组相比,基于互联网的有指导干预治疗方法的费用更高,但无统计学意义(12 个月时的平均差值为 406 欧元,95%CI:-611 至 1444)。在临床效果方面,两组之间的差异也无统计学意义(12 个月时的平均差值为 1.75,95%CI:在抑郁症状中心量表 [CES-D] 评分中为 -0.09 至 3.60;在应答率方面为 0.06,95%CI:-0.02 至 0.13;在质量调整生命年 [QALYs] 方面为 0.00,95%CI:-0.03 至 0.03)。成本效益接受性曲线表明,与对照组相比,要达到干预措施具有成本效益的可接受概率,需要进行大量投资,特别是在 CES-D 和治疗应答方面(例如,在 12 个月的随访时,在 CES-D 评分提高 2000 欧元/点的情况下,干预措施具有成本效益的概率为 0.95)。对于 QALYs,与对照组相比,干预措施具有成本效益的概率在通常可接受的支付意愿阈值下较低(例如,在 12 个月的随访时,在成本效益比分别为 24000 欧元和 35000 欧元/QALY 时,其概率分别为 0.29 和 0.31)。
根据目前的研究结果,与对照组相比,基于互联网的抑郁症有指导干预治疗方法不被认为具有成本效益。然而,只有少数 RCT 研究了基于互联网的有指导干预措施的临床疗效,也评估了成本效益,并纳入了本次个体参与者数据荟萃分析。