ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2025
Development of mapping algorithms for gastric cancer: translating EORTC QLQ-C30 and QLQ-STO22 to EQ-5D-5L health utilities.
Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Mapping EORTC-QLQ-C30 scores to EQ-5D-5L utility values for gynecological cancer survivors in follow-up care.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026Article
- Factors affecting health-related quality of life in cervical cancer survivors: a multicenter cross-sectional study in Korea.BMC women's health · 2026Observational
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7 authors.
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Abstract
purposeThis study aims to develop a mapping model from the EORTC QLQ-C30 and QLQ-STO22 to the EQ-5D-5L.
methodsData 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-validation. Model performance was evaluated using four primary metrics: root mean squared error (RMSE), mean absolute error (MAE), intraclass correlation coefficient (ICC), and absolute error (AE).
resultsThe mean health utility value of the EQ-5D-5L was 0.853 (SD = 0.240). The Oprobit3 demonstrated the best performance among all evaluated models, with RMSE = 0.197, MAE = 0.111, AE > 0.05 (%) = 56.84, AE > 0.1 (%) = 28.61, and ICC = 0.703. The predictors included all dimensions of the EORTC QLQ-C30 and QLQ-STO22 questionnaires, as well as age and gender.
conclusionsThe developed algorithm enables researchers to estimate EQ-5D-5L health utilities based on EORTC QLQ-C30 and QLQ-STO22 scores. This approach facilitates cost-utility analyses in gastric cancer patients when EQ-5D-5L data are unavailable.
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