Division of Infectious Diseases & Global Public Health, UC San Diego, 9500 Gilman Dr., La Jolla, San Diego, CA, 92093, USA.
School of Health Sciences, University of Dundee, Nethergate, Dundee, DD1 4HN, UK.
Qual Life Res. 2024 Oct;33(10):2783-2796. doi: 10.1007/s11136-024-03729-6. Epub 2024 Aug 8.
We aimed to estimate health state utility values (HSUVs) for the key health states found in opioid use disorder (OUD) cost-effectiveness models in the published literature.
Data obtained from six trials representing 1,777 individuals with OUD. We implemented mapping algorithms to harmonize data from different measures of quality of life (the SF-12 Versions 1 and 2 and the EQ-5D-3 L). We performed a regression analysis to quantify the relationship between HSUVs and the following variables: days of extra-medical opioid use in the past 30 days, injecting behaviors, treatment with medications for OUD, HIV status, and age. A secondary analysis explored the impact of opioid withdrawal symptoms.
There were statistically significant reductions in HSUVs associated with extra-medical opioid use (-0.002 (95% CI [-0.003,-0.0001]) to -0.003 (95% CI [-0.005,-0.002]) per additional day of heroin or other opiate use, respectively), drug injecting compared to not injecting (-0.043 (95% CI [-0.079,-0.006])), HIV-positive diagnosis compared to no diagnosis (-0.074 (95% CI [-0.143,-0.005])), and age (-0.001 per year (95% CI [-0.003,-0.0002])). Parameters associated with medications for OUD treatment were not statistically significant after controlling for extra-medical opioid use (0.0131 (95% CI [-0.0479,0.0769])), in line with prior studies. The secondary analysis revealed that withdrawal symptoms are a fundamental driver of HSUVs, with predictions of 0.817 (95% CI [0.768, 0.858]), 0.705 (95% CI [0.607, 0.786]), and 0.367 (95% CI [0.180, 0.575]) for moderate, severe, and worst level of symptoms, respectively.
We observed HSUVs for OUD that were higher than those from previous studies that had been conducted without input from people living with the condition.
我们旨在评估已发表文献中阿片类药物使用障碍(OUD)成本效益模型中发现的关键健康状态的健康状态效用值(HSUVs)。
我们的数据来自六项代表 1777 名 OUD 个体的试验。我们实施了映射算法,以协调来自不同生活质量衡量标准(SF-12 版本 1 和 2 以及 EQ-5D-3L)的数据。我们进行了回归分析,以量化 HSUVs 与以下变量之间的关系:过去 30 天内额外医疗用阿片类药物使用天数、注射行为、OUD 药物治疗、HIV 状况和年龄。二次分析探讨了阿片类药物戒断症状的影响。
与额外医疗用阿片类药物使用天数增加相关的 HSUVs 存在统计学显著降低(分别为每天增加 0.002(95%CI [0.003,0.0001])至 0.003(95%CI [0.005,0.002]))、与不注射相比的药物注射行为(0.043(95%CI [0.079,0.006]))、HIV 阳性诊断与无诊断(0.074(95%CI [0.143,0.005]))和年龄(每增加 1 岁 0.001(95%CI [0.003,0.0002]))。在控制额外医疗用阿片类药物使用的情况下,与 OUD 治疗药物相关的参数没有统计学意义(0.0131(95%CI [0.0479,0.0769])),与之前的研究一致。二次分析表明,戒断症状是 HSUVs 的一个基本驱动因素,分别预测中度、重度和最严重水平的症状为 0.817(95%CI [0.768,0.858])、0.705(95%CI [0.607,0.786])和 0.367(95%CI [0.180,0.575])。
我们观察到的 OUD 的 HSUVs 高于以前的研究,这些研究是在没有患者参与的情况下进行的。