Mapping the Peds QLTM 4.0 onto CHU-9D: a cross-sectional study in functional dyspepsia population from China

Frontiers in Public Health

Public Health

Yuankai Huang¹  Maozhen Li¹  Qiqi Wang¹  Chuchuan Wan¹  Xiaoyu Xi² 

[1] The Research Center of National Drug Policy & Ecosystem, China Pharmaceutical University, Nanjing, China;null;

关键词: mapping;    CHU-9D;    Peds QL 4.0;    health utility value;    functional dyspepsia;   

DOI  :  10.3389/fpubh.2023.1166760

 received in 2023-02-15, accepted in 2023-03-30,  发布年份 2023

来源: Frontiers

【 摘 要 】

ObjectiveThe 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.MethodsA sample of 2,152 patients with FD completed both the CHU-9D and Peds QL 4.0 instruments. A total of 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, and 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), was used to assess the predictive ability of the models.ResultsThe Tobit model with selected Peds QL 4.0 item scores, gender and age as the independent variable predicted the most accurate. The best-performing models for other possible combinations of variables were also shown.ConclusionThe mapping algorithm helps 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.

【 授权许可】

Unknown   
Copyright © 2023 Wang, Wan, Li, Huang and Xi.