Mapping the Peds QLTM 4.0 onto CHU-9D: a cross-sectional study in functional dyspepsia population from China - Wang, Qiqi; Wan, Chuchuan; Li, Maozhen; Huang, Yuankai; Xi, Xiaoyu (Frontiers in Public Health, 2023)
Objective: The study aims to develop a mapping algorithm from the Pediatric Quality of Life Inventory™ 4.0 (Peds QL 4.0) onto Child Health Utility 9D (CHU-9D) based on the cross-sectional data of functional dyspepsia (FD) children and adolescents in China. Methods: A sample of 2152 patients with FD completed both the CHU-9D and Peds QL 4.0 instruments. Six regression models were used to develop the mapping algorithm, including ordinary least squares regression (OLS), the generalized linear regression model (GLM), MM-estimator model (MM), Tobit regression (Tobit) and Beta regression (Beta) for direct mapping, multinomial logistic regression (MLOGIT) for response mapping. Peds QL 4.0 total score, Peds QL 4.0 dimension scores, Peds QL 4.0 item scores, gender and age were used as independent variables according to the Spearman correlation coefficient. The ranking of indicators, including the mean absolute error (MAE), root mean squared error (RMSE), adjusted R2 and consistent correlation coefficient (CCC), were used to assess the predictive ability of the models. Results: Tobit model with Peds QL 4.0 item scores, gender and age as the independent variable predicted the most accurate. The best performing models for other possible variables combinations of variables were also shown. Conclusion: The mapping algorithm help to transform Peds QL 4.0 data into health utility value. It is valuable for conducting health technology evaluations within clinical studies that have only collected Peds QL 4.0 data.