Association between the Weight-to-Waist Ratio and All-Cause Mortality in Cancer Patients A Cox Proportional-Hazards Regression Analysis of Cohort Data

Objective This study aimed to investigate the association between weight-to-waist ratio (WWR) and all-cause mortality risk in cancer patients, clarify whether it is an independent prognostic factor for cancer patients, and analyze its potential interaction effects. Methods A cohort study design was adopted. We screened data from 18,469 baseline participants and finally included 834 cancer patients with complete baseline data (331 deceased cases and 503 surviving cases). The Wilcoxon rank-sum test and Pearson chi-square test were used to compare baseline characteristics between the deceased and surviving groups. A Cox proportional-hazards regression model was employed to analyze the association between WWR and mortality risk, and a multifactorial-adjusted model was constructed to control for confounders. The dose-response relationship was analyzed by quartile grouping, heterogeneity was evaluated through subgroup analysis, and a non-linear relationship was tested using restricted cubic spline (RCS) analysis. Results The median WWR in the deceased group was 0.79 (IQR: 0.72–0.87), which was significantly lower than that in the surviving group (0.84, IQR: 0.77–0.90) (P < 0.001). After adjusting for demographic characteristics, lifestyle factors, and comorbidities (Model 3), WWR was significantly inversely associated with all-cause mortality risk (HR = 0.06, 95% CI: 0.02–0.24, P < 0.001). Multivariate-adjusted dose-response analysis showed that mortality risk decreased stepwise with increasing WWR quartiles, reaching a plateau in the highest quartile (Q4) (Q2 vs. Q1: HR = 0.70, P = 0.023; Q3 vs. Q1: HR = 0.57, P = 0.001; Q4 vs. Q1: HR = 0.57, P = 0.003). This indicates that a higher WWR is a protective factor against all-cause mortality in cancer patients, with a dose-response relationship. Subgroup analysis suggested potential interaction effects between WWR and urbanization level (p for interaction = 0.014) and history of heart disease (p for interaction = 0.084). RCS analysis indicated a linear association between WWR and mortality risk (p for overall association < 0.001, p for non-linearity = 0.077). Conclusion WWR is an independent protective factor for all-cause mortality in cancer patients, showing a dose-response relationship. Improving WWR by optimizing the balance between body weight and waist circumference may provide a novel intervention strategy for improving cancer prognosis.