Abstract
Arterial stiffness is measured by pulse wave velocity (PWV), which has a well-established correlation with a number of health consequences. Nevertheless, it is still unknown how estimated pulse wave velocity (ePWV) and the risk and mortality of gynecological cancer (GC) are related. This study examined the association between ePWV and GC risk and mortality using data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2003 and 2016. We initially performed a cross-sectional study in which we separated participants into 3 groups based on their ePWV tertiles in order to assess the relationship between ePWV and GC risk. A survival analysis was conducted to examine the relationship between ePWV and mortality risk in patients with GC. Multivariable logistic regression, Cox proportional hazards models and restricted cubic splines (RCS) were performed for analysis. A total of 19,590 participants were included in the study, with 464 diagnosed with GC (238 cervical cancer, 88 ovarian cancer, and 157 uterine cancer). Compared to the lowest ePWV group, the highest ePWV group had a 70% increased risk of GC (odds ratio (OR): 1.70, 95% confidence interval (CI): 1.10-2.62). RCS analysis revealed a nonlinear positive association between ePWV and GC risk (P for nonlinear = .044). The predictive value of ePWV for GC risk was 59.1% (area under the curve (AUC): 0.591, 95% CI: 0.567-0.616). Among GC patients, the highest ePWV group had a 6.45-fold increased risk of death compared to the lowest ePWV group (hazard ratio (HR): 6.45, 95% CI: 1.32-31.53). RCS analysis further showed a linear positive association between ePWV and mortality in GC patients (P for nonlinear = .131). The predictive value of ePWV for mortality risk in GC patients was 80.6% (AUC: 0.806, 95% CI: 0.756-0.855). Higher levels of ePWV are associated with an increased risk of GC and higher mortality in GC patients, although ePWV exhibits relatively poor discriminatory ability for GC risk. ePWV may serve as a useful predictor of both cancer risk and prognosis, highlighting its potential as a clinical marker for identifying at-risk individuals and improving patient management.