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.