BACKGROUND A utility value is a health-related quality of life metric (HRQoL) metric used in a cost-effectiveness analysis. While utilities as outcomes in the treatment of advanced Parkinson's disease (PD) with deep brain stimulation (DBS) are available, they do not currently exist for PD with early motor complications. The objectives of this study were to predict utilities from observed disease-specific HRQoL data using two mapping algorithms, and investigate their performance in terms of longitudinal changes within and between treatment groups, and distribution by PD severity. METHODS This is a post hoc analysis of data from the EARLYSTIM trial of DBS compared with best medical therapy (BMT) in PD patients with early motor complications We used two published algorithms comprising ordinal and multinomial regression models to map EQ-5D-3L utilities from observed PD-specific 39 item Questionnaire (PDQ-39) scores in EARLYSTIM. Utilities were calculated using the predicted functioning levels of EQ-5D-3L dimensions and the established EQ-5D-3L UK tariffs. Statistical analyses (analysis of variance, two-tailed Student's t-test) were used to test the change from baseline within groups and difference in change from baseline between groups in utilities. Boxplots were developed to investigate the distribution of predicted utilities by PD severity, measured using the Hoehn and Yahr scale. RESULTS The change from baseline in predicted mean utilities was statistically significant at all visits up to 24 months for the DBS group (p < 0.001) with both algorithms, and statistically significant at 12 months only (p = 0.04) for the BMT group with one algorithm. With both algorithms, the between-groups difference in change from baseline in predicted mean utilities favored DBS at all follow-up visits (p < 0.001). Based on the Hoehn and Yahr scale, predicted utilities deteriorated with increasing disease severity. CONCLUSIONS Among PD patients with early motor complications, utilities predicted by both mapping algorithms using PDQ-39 data demonstrated a statistically and clinically meaningful improvement with DBS compared with BMT. It was not possible to conclude if one algorithm was more responsive than other. In the absence of utilities collected directly from patients, mapping is an acceptable option permitting economic evaluations to be undertaken.

中文翻译：

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帕金森氏病伴早期运动并发症：根据EARLYSTIM试验中PDQ-39数据预测EQ-5D-3L效用。

背景技术效用值是在成本效益分析中使用的健康相关生活质量度量（HRQoL）度量。虽然可以使用可通过深部脑刺激（DBS）治疗晚期帕金森氏病（PD）的效用，但目前尚不适用于早期运动并发症的PD。这项研究的目的是使用两种作图算法从观察到的特定疾病的HRQoL数据预测效用，并根据治疗组内和治疗组之间的纵向变化以及PD严重性的分布来研究其性能。方法这是一项针对DBS的EARLYSTIM试验与早期运动并发症的PD患者的最佳药物治疗（BMT）进行对比的事后分析。我们使用了两种已公布的算法，包括序数和多项式回归模型，以绘制来自EQ-5D-3L的效用。在EARLYSTIM中观察到的PD特定的39项问卷（PDQ-39）得分。使用EQ-5D-3L尺寸的预测功能水平和既定的EQ-5D-3L英国关税来计算公用事业。统计分析（方差分析，两尾学生t检验）用于检验公用事业中各组与基线之间的变化以及各组之间与基线之间的变化差异。开发了箱形图，以研究使用Hoehn和Yahr量表通过PD严重性预测的效用分布。结果两种算法在DBS组直至24个月的所有就诊时，预测平均效用的基线变化均具有统计学意义（p <0.001），而对于BMT组只有一种，在12个月时才具有统计学意义（p = 0.04）。算法。使用这两种算法，在所有后续随访中，预测平均效用的基线之间的组间变化差异均支持DBS（p <0.001）。根据Hoehn和Yahr量表，预测的效用随着疾病严重程度的增加而恶化。结论在患有早期运动并发症的PD患者中，两种映射算法使用PDQ-39数据预测的效用均表明，与BMT相比，DBS具有统计学和临床​​意义的改善。无法断定一种算法是否比另一种更具响应性。