Blood cell indices and inflammation-related markers with kidney cancer risk: a large-population prospective analysis in UK Biobank
作者全名：He, Qingliu; Wei, Chengcheng; Cao, Li; Zhang, Pu; Zhuang, Wei; Cai, Fangzhen
作者地址：[He, Qingliu; Zhuang, Wei; Cai, Fangzhen] Fujian Med Univ, Affiliated Hosp 2, Dept Urol, Quanzhou, Peoples R China; [He, Qingliu; Wei, Chengcheng] Huazhong Univ Sci & Technol, Union Hosp, Tongji Med Coll, Dept Urol, Wuhan, Hubei, Peoples R China; [Wei, Chengcheng] Chongqing Med Univ, Affiliated Hosp 1, Dept Urol, Chongqing, Peoples R China; [Cao, Li] Huazhong Univ Sci & Technol, Union Hosp, Tongji Med Coll, Dept Orthopaed, Wuhan, Hubei, Peoples R China; [Zhang, Pu] Univ Elect Sci & Technol China, Sichuan Prov Peoples Hosp, Sch Med, Dept Urol, Chengdu, Peoples R China
通信作者：Zhuang, W; Cai, FZ (通讯作者)，Fujian Med Univ, Affiliated Hosp 2, Dept Urol, Quanzhou, Peoples R China.; Zhang, P (通讯作者)，Univ Elect Sci & Technol China, Sichuan Prov Peoples Hosp, Sch Med, Dept Urol, Chengdu, Peoples R China.
来源：FRONTIERS IN ONCOLOGY
ESI学科分类：CLINICAL MEDICINE
WOS号：WOS:001241799700001
JCR分区：Q2
影响因子：3.5
年份：2024
卷号：14
期号：
开始页：
结束页：
文献类型：Article
关键词：kidney cancer; blood cell indices; inflammation-related markers; UK Biobank; prospective analysis
摘要：Background Kidney cancer is a prevalent malignancy with an increasing incidence worldwide. Blood cell indices and inflammation-related markers have shown huge potential as biomarkers for predicting cancer incidences, but that is not clear in kidney cancer. Our study aims to investigate the correlations of blood cell indices and inflammation-related markers with kidney cancer risk.Methods We performed a population-based cohort prospective analysis using data from the UK Biobank. A total of 466,994 participants, free of kidney cancer at baseline, were included in the analysis. The hazard ratios (HRs) and 95% confidence intervals (CIs) for kidney cancer risk were calculated using Cox proportional hazards regression models. Restricted cubic spline models were used to investigate nonlinear longitudinal associations. Stratified analyses were used to identify high-risk populations. The results were validated through sensitivity analyses.Results During a mean follow-up of 12.4 years, 1,710 of 466,994 participants developed kidney cancer. The Cox regression models showed that 13 blood cell indices and four inflammation-related markers were associated with kidney cancer incidence. The restricted cubic spline models showed non-linear relationships with kidney cancer. Finally, combined with stratified and sensitivity analyses, we found that the mean corpuscular hemoglobin concentration (MCHC), red blood cell distribution width (RDW), platelet distribution width (PDW), systemic immune-inflammation index (SII), and product of platelet count and neutrophil count (PPN) were related to enhanced kidney cancer risk with stable results.Conclusion Our findings identified that three blood cell indices (MCHC, RDW, and PDW) and two inflammation-related markers (SII and PPN) were independent risk factors for the incidence of kidney cancer. These indexes may serve as potential predictors for kidney cancer and aid in the development of targeted screening strategies for at-risk individuals.
基金机构：Natural Science Foundation of Fujian Province [2020J01204, 2021J01276, 2022J01273]; Joint funds for the innovation of science and technology, Fujian province [2023Y9228, 2023Y9243]; Quanzhou City Science & Technology Program of China [2023C008YR]
基金资助正文：The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was funded by the Natural Science Foundation of Fujian Province (No.2020J01204, No.2021J01276 and No.2022J01273); The joint funds for the innovation of science and technology, Fujian province (No.2023Y9228 and No.2023Y9243); The Quanzhou City Science & Technology Program of China, No.2023C008YR.
