Faculty of Social Sciences, Hellenic Open University, Patras, Greece.
Eur J Health Econ. 2013 Apr;14(2):307-14. doi: 10.1007/s10198-012-0376-9. Epub 2012 Jan 18.
The purpose of this methodological study was to to provide insight into the under-addressed issue of the longitudinal predictive ability of mapping models. Post-intervention predicted and reported utilities were compared, and the effect of disease severity on the observed differences was examined.
A cohort of 120 rheumatoid arthritis (RA) patients (60.0% female, mean age 59.0) embarking on therapy with biological agents completed the Modified Health Assessment Questionnaire (MHAQ) and the EQ-5D at baseline, and at 3, 6 and 12 months post-intervention. OLS regression produced a mapping equation to estimate post-intervention EQ-5D utilities from baseline MHAQ data. Predicted and reported utilities were compared with t test, and the prediction error was modeled, using fixed effects, in terms of covariates such as age, gender, time, disease duration, treatment, RF, DAS28 score, predicted and reported EQ-5D.
The OLS model (RMSE = 0.207, R(2) = 45.2%) consistently underestimated future utilities, with a mean prediction error of 6.5%. Mean absolute differences between reported and predicted EQ-5D utilities at 3, 6 and 12 months exceeded the typically reported MID of the EQ-5D (0.03). According to the fixed-effects model, time, lower predicted EQ-5D and higher DAS28 scores had a significant impact on prediction errors, which appeared increasingly negative for lower reported EQ-5D scores, i.e., predicted utilities tended to be lower than reported ones in more severe health states.
This study builds upon existing research having demonstrated the potential usefulness of mapping disease-specific instruments onto utility measures. The specific issue of longitudinal validity is addressed, as mapping models derived from baseline patients need to be validated on post-therapy samples. The underestimation of post-treatment utilities in the present study, at least in more severe patients, warrants further research before it is prudent to conduct cost-utility analyses in the context of RA by means of the MHAQ alone.
本方法学研究旨在深入探讨映射模型纵向预测能力这一尚未得到充分关注的问题。对比干预后预测的和报告的效用值,并考察疾病严重程度对观察到的差异的影响。
对 120 名开始接受生物制剂治疗的类风湿关节炎(RA)患者(60.0%为女性,平均年龄 59.0 岁)进行了一项队列研究,这些患者在基线时和干预后 3、6 和 12 个月时完成了健康评估问卷(MHAQ)和 EQ-5D 量表的评估。采用最小二乘法(OLS)回归方程,基于基线 MHAQ 数据来估算干预后的 EQ-5D 效用值。采用 t 检验比较预测值和报告值,采用固定效应模型,根据年龄、性别、时间、疾病持续时间、治疗、RF、DAS28 评分、预测和报告的 EQ-5D 等协变量,对预测误差进行建模。
OLS 模型(RMSE = 0.207,R² = 45.2%)始终低估了未来的效用值,平均预测误差为 6.5%。在 3、6 和 12 个月时,报告和预测的 EQ-5D 效用值之间的平均绝对差异超过了 EQ-5D 的典型报告的 MID(0.03)。根据固定效应模型,时间、较低的预测 EQ-5D 和较高的 DAS28 评分对预测误差有显著影响,对于报告的 EQ-5D 评分较低的情况,预测误差的负值越来越大,即在健康状况较差的情况下,预测效用值往往低于报告的效用值。
本研究进一步证实了将疾病特异性工具映射到效用测量上的潜在有用性,该研究还解决了纵向有效性的具体问题,因为基于基线患者得出的映射模型需要在治疗后的样本上进行验证。在本研究中,至少在病情较重的患者中,治疗后效用值被低估,因此在 RA 背景下,单独使用 MHAQ 进行成本效用分析之前,还需要进一步研究。