Supplementary figures: Mapping the EORTC QLQ-C30 onto the EQ-5D-5L index for patients with paroxysmal nocturnal hemoglobinuria in France

These are peer-reviewed supplementary materials for the article 'Mapping the EORTC QLQ-C30 onto the EQ-5D-5L index for patients with paroxysmal nocturnal hemoglobinuria in France' published in the Journal of Comparative Effectiveness Research.Supplementary Figure 1: Markov model diagram.Supplementary Figure 2:. Histogram of EORTC QLQ-C30 subscale scores.Supplementary Figure 3: Histogram of EQ-5D-5L domain scores.Supplementary Figure 4: Model performance.Supplementary Figure 5: Estimated utilities by visit and treatment.Supplementary Table 1: Types of regression models.Supplementary Table 2: Tobit model results.Supplementary Table 3: Health-state utilities by modelAim: To map patient-level data collected on the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC) QLQ-C30 to EQ-5D-5L data for estimating health-state utilities in patients with paroxysmal nocturnal hemoglobinuria (PNH). Materials & methods: European cross-sectional PNH patient survey data populated regression models mapping EORTC QLQ-C30 domains (covariates: sex and baseline age) to utilities calculated with the EQ-5D-5L French value set. A genetic algorithm allowed selection of the best-fitting between a set of models with and without interaction terms. We validated the selected algorithm using EQ-5D-5L utilities converted from EORTC QLQ-C30 data collected in the PEGASUS phase III, randomized controlled trial of pegcetacoplan versus eculizumab in adults with PNH. Results: Selected through the genetic algorithm, the ordinary least squares model without interactions provided highly stable results across study visits (mean [±SD] utilities 0.58 [±0.42] to 0.89 [±0.10]), and showed the best predictive validity. Conclusion: The new PNH EQ-5D-5L direct mapping developed using a genetic algorithm enabled calculation of reliable health-state utility data required for cost–utility analysis in health technology assessments supporting treatments of PNH.本数据集为发表于《比较效果研究杂志》（Journal of Comparative Effectiveness Research）的论文《将法国阵发性睡眠性血红蛋白尿症（paroxysmal nocturnal hemoglobinuria, PNH）患者的EORTC QLQ-C30量表映射至EQ-5D-5L指数》的同行评议补充材料。 补充图1：马尔可夫模型示意图 补充图2：EORTC QLQ-C30子量表得分直方图 补充图3：EQ-5D-5L领域得分直方图 补充图4：模型性能 补充图5：各访视及治疗组的估算效用值 补充表1：回归模型类型 补充表2：托比特模型结果 补充表3：基于不同模型的健康状态效用值 研究目的：将通过欧洲癌症研究与治疗组织生活质量问卷C30（EORTC QLQ-C30）收集的患者层面数据映射至EQ-5D-5L数据，以估算阵发性睡眠性血红蛋白尿症（PNH）患者的健康状态效用值。 材料与方法：采用欧洲横断面PNH患者调查数据构建回归模型，将EORTC QLQ-C30维度（协变量：性别与基线年龄）映射至基于法国权重集计算的EQ-5D-5L效用值。通过遗传算法在包含与不包含交互项的多组模型中筛选最优拟合模型。本研究采用来自PEGASUS Ⅲ期随机对照试验的EORTC QLQ-C30数据转换得到的EQ-5D-5L效用值对筛选得到的最优模型进行验证，该试验对比了pegcetacoplan与eculizumab治疗成人PNH患者的疗效。 结果：经遗传算法筛选得到的无交互项普通最小二乘模型在各研究访视中均表现出极高的稳定性（效用值均值[±标准差]：0.58[±0.42]至0.89[±0.10]），且具备最优的预测效度。 结论：本研究通过遗传算法开发的新型PNH患者EQ-5D-5L直接映射模型，可计算得到可靠的健康状态效用值数据，该数据可为支持PNH治疗的卫生技术评估中的成本效用分析提供必要支撑。