ArticleBMC cancer2025
Red cell indices as predictors of cancer risk: findings from a large prospective cohort study.
Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Long-term risk of gynecologic malignancies in postmenopausal women with vaginal bleeding and benign endometrial lesions: a cohort study.Frontiers in oncology · 2026Article
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11 authors.
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Abstract
backgroundRed blood cell disorders have been implicated in tumorigenesis. Nevertheless, the association between red cell indices (RCIs), which reflect the health status of red blood cells, and the risk of cancer has yet to be determined.
methodsThis was a prospective cohort study involving 455,897 participants who were free of cancer at baseline and had measurements of RCIs, namely mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), red cell distribution width (RDW), and hemoglobin (Hb). The associations of RCIs with overall and site-specific cancer risk were examined by using multivariate Cox proportional hazards regression models with RCIs mutually adjusted. The dose-response relationships were investigated via restricted cubic splines.
resultsOver a median follow-up of 10.9 years, 47,177 participants were diagnosed with cancer. MCV (Q5 vs Q1: fully-adjusted HR = 0.83, 95% CI: 0.78-0.88) and MCH (HR = 0.83, 95% CI: 0.79-0.87) exhibited a non-linear and inverse association with the overall cancer risk (both P values for nonlinear < 0.001). Conversely, RDW showed a linear and positive association with the overall cancer risk (HR = 1.19, 95% CI: 1.15-1.23, P for linear < 0.001). For site-specific cancers, MCV and MCH exhibited inverse associations with the risks of lymphoma, leukemia, breast cancer, and kidney cancer, while RDW was positively associated with the risks of these malignancies.
conclusionsOur findings indicate that MCV, MCH, and RDW have clinical significance as potential biomarkers for predicting cancer risk. Further studies are needed to elucidate the underlying mechanisms driving these associations.
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