Background Currently, the landscape of cancer treatment has undergone significant transformations, with numerous cancer patients now surviving in a chronic disease paradigm over extended periods. Research indicates that a substantial number of cancer survivors succumb to non-tumor factors, with cardiovascular disease (CVD) being a prominent cause among them. Nevertheless, the potential CVD risks associated with cancer treatment are frequently overlooked, resulting in inadequate early intervention and protective measures.The estimated pulse wave velocity (ePWV) can reflect the degree of arterial stiffness and is an independent predictor of cardiovascular events. The simple calculation method provides feasibility for cardiovascular risk stratification in cancer patients.
Objective To assess the influencing factors of ePWV on all-cause mortality and CVD mortality in a cohort of cancer patients.
Methods A retrospective cohort design was used. The cohort included 4 632 cancer patients who attended the National Health and Nutrition Examination Survey (NHANES) database from 1999 to 2018. Baseline data were collected, including age, gender, race, BMI, chest circumference, baseline heart rate (BHR), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), diastolic blood pressure (DBP), diabetes status, history of CVD, smoking and drinking status. Follow-up to July 2023. With ePWV as the variable, the quartile method was used for grouping. All the subjects were divided into 4 groups, which were recorded as Q1, Q2, Q3 and Q4 groups. The baseline levels of the 4 groups were compared, and the Kaplan-Meier survival curves related to all-cause mortality and CVD mortality of the patients were plotted. Cox proportional hazard regression model were used to explore the relationship of ePWV and mortality in cancer patients. The receiver operating characteristic (ROC) curve of the predictive value of ePWV for death in cancer patients was drawn, and the area under the ROC curve (AUC) was calculated.
Results A total of 4 632 patients, with an average age of (60.7±1.0) years, were enrolled, comprising 2 426 females (52.37%) and 2 206 males (47.63%). There were 1 158 cases in Q1-Q4 groups. Significant differences were observed among the four groups in terms of age, gender, race, BMI, chest circumference, BHR, TC, HDL-C, SBP, DBP, diabetes history, CVD history, smoking status, and alcohol consumption status (P<0.05). During the follow-up period, 830 (17.92%) of 4 632 cancer patients died of all-cause and 376 (8.12%) died of CVD. There were significant differences in all-cause mortality and CVD mortality among the four groups (P<0.001). Kaplan-Meier survival analysis revealed statistically significant differences in the survival curves related to all-cause mortality and CVD mortality among 4 groups (χ2=587.11, P<0.001; χ2=322.97, P<0.001). The results of multivariate Cox regression analysis indicated that, compared with patients in Q1, those in Q2, Q3, and Q4 had an increased risk of all-cause mortality (Q2: HR=1.30, 95%CI=1.23-1.38, P=0.045; Q3: HR=1.46, 95%CI=1.01-2.13, P=0.047; Q4: HR=1.24, 95%CI=1.04-1.49, P=0.017). Additionally, patients in Q3 and Q4 exhibited an elevated risk of CVD mortality (Q3: HR=1.28, 95%CI=1.05-1.56, P=0.013; Q4: HR=2.73, 95%CI=1.67-4.48, P=0.026); ROC curve showed that the AUC values of Q1, Q2, Q3 and Q4 groups were 0.514, 0.624, 0.598 and 0.772, respectively.
Conclusion It was verified that elevated ePWV was positively correlated with the risk of all-cause and CVD mortality in cancer patients. ePWV may be a predictor of the risk of death in this population.
