Evidence map›Paper›PMID 40055624›Full record

ArticleBMC cancer2025

Assessing the performance of QLQ-C30 in predicting all-cause mortality in community cancer patients.

Jin Zhao, Yanmin Wang, Weidong Huang, Richard H Xu, Xiaoming Yang, Pei Wang

Abstract read
In one paragraph

Article in BMC cancer, 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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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Jin Zhao *School of Public Health, Fudan University, 130 Dong An Road, Shanghai, 200032, China.
Yanmin Wang *Jing'an District Center for Disease Control and Prevention, 195 Yong He Road, Shanghai, 200072, China.
Weidong HuangSchool of Health Management, Harbin Medical University, 157 Xue Fu Road, 150081, Harbin, China.
Richard H XuDepartment of Rehabilitation Sciences, Faculty of Health and Social Sciences, Hong Kong Polytechnic University, 11 Yau Tsai Road, Kowloon, 999077, Hong Kong, China.
Xiaoming YangJing'an District Center for Disease Control and Prevention, 195 Yong He Road, Shanghai, 200072, China. yangxiaoming@jingancdc.net.
Pei WangSchool of Public Health, Fudan University, 130 Dong An Road, Shanghai, 200032, China. wang_p@fudan.edu.cn.

Funding

National Natural Science Foundation of China 72274037
6 · The paper itself

Abstract

backgroundTo evaluate the ability of QLQ-C30 in predicting mortality in community-based cancer patients in China.

methodsA whole-cluster sampling method was adopted to enroll cancer patients in four communities in Shanghai from 2018 to 2019. The patients were surveyed using a questionnaire enquiring demographic information, cancer types, and QLQ-C30 scale. Death information of participants was collected and updated from community health care centers. Cox regression models were used to assess the relationship between various QLQ-C30 scores (i.e., total score, five dimension scores, and utility score) and all-cause mortality.

resultsA total of 3,304 participants were enrolled with a mean age of 63.9 years. Among them, 2,710 patients survived while 594 died by 2023. The mean total QLQ-C30 score in living patients was statistically significantly higher than that in deceased patients ( 92.96 vs. 85.21, p < 0.001); and the mean values of the five dimension scores and utility score were also significantly higher for the living patients. Cox regression models with the adjustment of covariates also confirmed that higher QLQ-C30 scores were associated with lower risk of death, with the hazard ratio value being 0.81 for the total score, 0.83-0.89 for the dimension scores, and 0.83 for the utility score, respectively (p < 0.001 for all).

conclusionsQLQ-C30 could accurately predict all-cause mortality in Chinese community cancer patients.

Indexed as

NeoplasmsQuality of LifeAdultAgedAged, 80 and overCause of DeathChinaFemaleHumansMaleMiddle AgedPrognosisProportional Hazards ModelsSurveys and QuestionnairesCommunity cancer patientsHealth-related quality of lifeMortalityPredictionQLQ-C30

Identifiers

PMID40055624
PMCPMC11889892

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.