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.
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.
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.
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.