Evidence map›Paper›PMID 40722091›Full record

ArticleHealth and quality of life outcomes2025

Socio-demographic characteristics associated with SF-6D v2 utility scores in patients undergoing dialysis in China: contributions of the quantile regression.

Ye Zhang, Li Yang, Zeyuan Chen

Abstract readMulticenter Study
In one paragraph

Article in Health and quality of life outcomes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

3 authors.

Ye ZhangPopulation Development Studies Center, Renmin University of China, Beijing, 100872, People's Republic of China.
Li YangSchool of Public Health, Peking University, Beijing, 100191, People's Republic of China.
Zeyuan ChenDepartment of Informatics and Media, Uppsala University, Uppsala, SE-751 05, Sweden. zychen@mail.bnu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGeneric preference-based instruments, such as the Short Form 6-Dimensions (SF-6D) and EuroQol 5-Dimensions (EQ-5D), can generate utility scores that facilitate the estimation of health-related quality of life (HRQoL) which is commonly used in cost-utility analysis. This study investigated the associations between utility scores and potential socio-demographic factors in Chinese patients with dialysis using quantile regression.

methodsPatients were recruited in a multicenter survey conducted between November 2023 and January 2024 for dialysis patients in China. Patient responses to the SF-6D version 2 (SF-6Dv2) instruments were used to calculate utility scores. The relationships between utility scores and potential socio-demographic factors were examined using both ordinary least squares (OLS) and quantile regression models. The Wald test was employed to test the differences in coefficients across quantiles in quantile regression. Model performance was assessed using 5-fold cross-validation.

resultsA total of 378 patients were included. Age, education level, having a loan due to illness, currently working, monthly income > 8000 RMB and number of comorbidities were associated with utility scores. The quantile regression coefficients and Wald test suggested that the size of the associations between the utility scores and factors varied along with the utility score distribution. Quantile regression yielded more accurate fitted and predicted values compared to OLS regression.

conclusionQuantile regression offers a valuable complement in analyzing factors associated with utility scores among Chinese dialysis patients. For policymakers, differentiated nonclinical strategies may be needed to improve HRQoL across varying health states within this population.

Indexed as

Quality of LifeRenal DialysisAdultAgedChinaFemaleHumansKidney Failure, ChronicMaleMiddle AgedRegression AnalysisSocioeconomic FactorsSurveys and QuestionnairesDialysisHealth-related quality of lifeQuantile regressionSF-6Dv2Utility scores

Identifiers

PMID40722091
PMCPMC12305961

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