Evidence map›Paper›PMID 41310487›Full record

ArticleBMC cancer2025

Association of estimated glucose disposal rate with all-cause and breast cancer-specific mortality in US breast cancer survivors: a population-based study.

Jinhao Li, Jiasheng Liu, Bingliang Cai, Chuansheng Yang

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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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5 · Who and what money

Authors and funding

4 authors.

Jinhao LiDepartment of Breast, Thyroid and Head-Neck Surgery, Yuebei People's Hospital, Shantou University Medical College, Shaoguan, Guangdong, 512026, China.
Jiasheng LiuDepartment of Urology, Yuebei People's Hospital, Shantou University Medical College, Shaoguan, Guangdong, 512026, China.
Bingliang CaiDepartment of Breast, Thyroid and Head-Neck Surgery, Yuebei People's Hospital, Shantou University Medical College, Shaoguan, Guangdong, 512026, China.
Chuansheng YangDepartment of Breast, Thyroid and Head-Neck Surgery, Yuebei People's Hospital, Shantou University Medical College, Shaoguan, Guangdong, 512026, China. yangchuansh@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInsulin resistance (IR) is increasingly linked with poor cancer prognosis, but its impact on mortality among breast cancer patients—particularly regarding different causes of death—remains incompletely understood. The estimated glucose disposal rate (eGDR) is a surrogate index of insulin sensitivity. This study intended to investigate the links of eGDR with all-cause mortality (ACM) and breast cancer-specific mortality (BCSM) in US breast cancer survivors.

methodsData were sourced from the 2007–2016 National Health and Nutrition Examination Survey(NHANES). A cross-sectional design was used to assess the link between eGDR and breast cancer prevalence, while a cohort design was adopted for mortality follow-up. Additionally, weighted logistic regression was leveraged to estimate the link between eGDR and breast cancer prevalence. Cox models were employed to evaluate the relationship between eGDR and ACM. Restricted cubic splines were utilized to model nonlinear links, and competing risk models were adopted to analyze BCSM.

resultsAmong 323 women with breast cancer, 73 deaths occurred during follow-up (median 6.2 years). After multiple confounders were controlled, a binary analysis using optimal cutoff values confirmed that higher eGDR was independently linked with lower ACM risk (HR: 0.40; 95% CI: 0.18–0.89; P = 0.025). This association was nonlinear, and the protective effect remained across multiple subgroups. In competing risk analysis, a potential association was observed between higher eGDR and lower BCSM risk (HR: 0.13; 95% CI: 0.02–0.99; P = 0.048), with no marked association observed for cardiovascular mortality.

conclusionIn US breast cancer survivors, higher eGDR was independently linked with lower ACM risk. This association may be partly driven by a reduction in BCSM, but this specific finding requires validation in larger studies due to considerable statistical uncertainty.

Indexed as

Blood GlucoseBreast NeoplasmsCancer SurvivorsGlucoseInsulin ResistanceAdultAgedCause of DeathCross-Sectional StudiesFemaleHumansMiddle AgedNutrition SurveysRisk FactorsUnited StatesBlood GlucoseGlucoseBreast cancerCompeting riskseGDRInsulin resistanceMortalityNHANES

Identifiers

PMID41310487
PMCPMC12771819

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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.