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

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posted on 2024-04-12, 15:08 authored by Piotr Wojciechowski, Marlena Wdowiak, Zalmai Hakimi, Koo Wilson, Jesse Fishman, Jameel Nazir, Mondher Toumi

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 model

Aim: 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.

Funding

This study was funded by Apellis Pharmaceuticals, Inc. and Swedish Orphan Biovitrum (SOBI) AB, Stockholm, Sweden.

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