Association Of Short-Term Heart Rate Variability With TNM Staging Of Breast Cancer

Background and purpose:Breast cancer is the most common cancer among worldwide and is the fifth leading cause of cancer deaths worldwide.The autonomic nervous system activity,assessed by heart rate variability（HRV）,is related to the occurrence and development of tumors.Reductions in HRV are clinically predictive of cardiovascular morbidity and mortality,which elevates risk of death from all causes,including cancer.HRV may be identified as the prognostic marker in breast cancer patients.Further studies are needed to elucidate the potential role of HRV parameters in the prognosis of breast cancer patients.This study aimed to explore the association between short-term HRV with TNM staging in breast cancer patients.Materials and methods:The study included 133 patients（average age 49.2 years）with breast cancer or benign breast tumors.According to TNM staging,breast cancer patients were divided into early-stage breast cancer（50 patients）and advanced-stage breast cancer（40patients）,and patients with benign breast tumors（43 patients）were enrolled as controls.Five-minute resting electrocardiogram was collected for the analysis of linear and nonlinear HRV parameters,i.e.,the standard deviation of the normal-normal intervals（SDNN）,root mean square of successive interval differences（RMSSD）,total powers（TP）,low frequency powers（LF）,high frequency powers（HF）,the ratio of LF to HF（LF/HF）,and nonlinear measures,i.e.,Poincare plot:SD1,SD2,and the ratio of SD2 to SD1（SD2/SD1）,approximate entropy（Ap En）,sample entropy（Samp En）,detrended fluctuation analysis:short-term fluctuationsα₁and long-term fluctuationsα₂,and correlation dimension（CD）.Finally,multiple logistic regression models were performed to test the correlation between HRV and breast tumor stage.Results:According to the chi-square test,the results of the pathological type of breast cancer and molecular typing revealed no significant differences between the groups.In TNM staging,the early-stage group comprised patients with stages T1–3,N0–1,and M0 cancers,while the advanced-stage group comprised patients with stages T1–4,N1–3,and M0–1 cancers.Among patients with stages I–IV,the early-stage group comprised stages Ia,IIa,and IIb;however,the advanced-stage group comprised stage IIIa,IIIb,IIIc,and IV.The one-way ANOVA and Kruskal-Wallis test showed patients with advanced-stage breast cancer had lower SDNN（P<0.001）,RMSSD（P=0.006）,LF（P<0.001）,HF（P=0.005）,TP（P<0.001）,SD1（P=0.007）,SD2（P<0.001）,and CD（P<0.001）than those with benign tumors and early-stage breast cancer.However,differences in HRV indices between the benign and early-stage groups were not significantly different.In logistic regression analysis,after adjusting for age,body mass index,mean heart rate,and respiratory rate,SD2（odds ratio[OR]=0.307,95%confidence interval[CI]=0.155–0.606,P=0.001）,SDNN（OR=0.357,95%CI=0.183–0.694,P=0.002）,TP（OR=0.467,95%CI=0.239–0.910,P=0.025）,and LF（OR=0.341,95%CI=0.130–0.898,P=0.029）were significantly associated with tumor stage.Conclusion:1.This study found that the linear and nonlinear HRV were related to breast cancer staging.The results of our study showed that patients with advanced-stage breast cancer had lower HRV,had autonomic dysfunction,and might have a poor prognosis,2.Nonlinear HRV parameters might predict TNM staging in patients with breast tumors.Nonlinear approaches are of great significance in coping well with the nonstationary and nonlinear nature of heartbeat fluctuations.It is suggested that the combined measurement of traditional linear and nonlinear HRV parameters may benefit future investigations.3.In addition to evaluating tumor stage,linear methods and nonlinear indicators should be considered to estimate the prognosis of a breast cancer patient,and clinicians could ascertain patients at risk for disease progression through the long-term monitoring of HRV.