Development of mapping algorithms for gastric cancer: translating EORTC QLQ-C30 and QLQ-STO22 to EQ-5D-5L health utilities.

ABSTRACT:

Purpose

This study aims to develop a mapping model from the EORTC QLQ-C30 and QLQ-STO22 to the EQ-5D-5L.

Methods

Data were collected from 1059 gastric cancer patients in mainland China. The conceptual overlap between the EORTC QLQ-C30/QLQ-STO22 and EQ-5D-5L was assessed using the Pearson correlation coefficient. Four regression models were applied to estimate the algorithm: ordinary least squares (OLS), Tobit regression (Tobit), ordered probit regression (Oprobit), and beta mixture regression (Betamix). The independent variables in the models comprised the scale dimension scores of the EORTC QLQ-C30 and QLQ-STO22, squared terms of relevant dimension scores, age, and gender. The generalizability of the models was assessed using random sample validation and five-fold cross-val

SUBMITTER: Zhou H 

PROVIDER: S-EPMC12689832 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature