Differences in heart rate variability and body composition in breast cancer survivors and women without cancer

Association between body composition and subsequent cardiovascular diseases among 5-year breast cancer survivors

BACKGROUND AND AIMS

Cardiovascular disease (CVD) remain one of the leading causes of mortality in breast cancer survivors. This study aimed to investigate the association between body composition and subsequent CVD in breast cancer survivors.

METHODS AND RESULTS

A retrospective cohort study of more than 70 thousand 5-year breast cancer survivors aged 40 years or older was conducted using data from the National Health Insurance Service of South Korea. Based on the percentage of predicted lean body mass (pLBMP), appendicular skeletal muscle mass (pASMP), and body fat mass (pBFMP), which were calculated using prediction equations with anthropometric data and health habits, groups were equally divided into quartiles. The risk of CVD was evaluated using multivariate Cox proportional hazards regression. Compared to those with the lowest pLBMP and pASMP, those with the highest pLBMP and pASMP had a 38% and 42% lower risk of CVD, respectively. In contrast, those with the highest pBFMP had a 57% higher risk of CVD compared to those with the lowest pBFMP. Each 1 % increase in pLBMP and pASMP was associated with a decreased risk of CVD [pLBMP, adjusted hazard ratio (aHR): 0.96, 95% CI 0.94-0.98, p < 0.05; pASMP, aHR: 0.91, 95% CI 0.87-0.95, p < 0.05] while each 1 % increase in pBFMP was associated with the increased risk of CVD (aHR: 1.05, 95% CI 1.03-1.07, p < 0.01).

CONCLUSION

In this cohort study, a high pLBMP, a high pASMP, and a low pBFMP were associated with a lower risk of CVD.

Tracking Cancer: Exploring Heart Rate Variability Patterns by Cancer Location and Progression

Reduced heart rate variability (HRV) is an autonomic nervous system (ANS) response that may indicate dysfunction in the human body. Consistent evidence shows cancer patients elicit lower HRV; however, only select cancer locations were previously evaluated. Thus, the aim of the current study was to explore HRV patterns in patients diagnosed with and in varying stages of the most prevalent cancers. At a single tertiary academic medical center, 798 patients were recruited. HRV was measured via an armband monitor (Warfighter MonitorTM, Tiger Tech Solutions, Inc., Miami, FL, USA) equipped with electrocardiographic capabilities and was recorded for 5 to 7 min with patients seated in an upright position. Three time-domain metrics were calculated: SDNN (standard deviation of the NN interval), rMSSD (the root mean square of successive differences of NN intervals), and the percentage of time in which the change in successive NN intervals exceeds 50ms within a measurement (pNN50). Of the 798 patients, 399 were diagnosed with cancer. Cancer diagnoses were obtained via medical records one week following the measurement. Analysis of variance models were performed comparing the HRV patterns between different cancers, cancer stages (I-IV), and demographic strata. A total of 85% of the cancer patients had breast, gastrointestinal, genitourinary, or respiratory cancer. The cancer patients were compared to a control non-cancer patient population with similar patient size and distributions for sex, age, body mass index, and co-morbidities. For all HRV metrics, non-cancer patients exhibited significantly higher rMSSDs (11.1 to 13.9 ms, p < 0.0001), SDNNs (22.8 to 27.7 ms, p < 0.0001), and pNN50s (6.2 to 8.1%, p < 0.0001) compared to stage I or II cancer patients. This significant trend was consistently observed across each cancer location. Similarly, compared to patients with stage III or IV cancer, non-cancer patients possessed lower HRs (-11.8 to -14.0 bpm, p < 0.0001) and higher rMSSDs (+31.7 to +32.8 ms, p < 0.0001), SDNNs (+45.2 to +45.8 ms), p < 0.0001, and pNN50s (19.2 to 21.6%, p < 0.0001). The HR and HRV patterns observed did not significantly differ between cancer locations (p = 0.96 to 1.00). The depressed HRVs observed uniformly across the most prevalent cancer locations and stages appeared to occur independent of patients' co-morbidities. This finding highlights the potentially effective use of HRV as a non-invasive tool for determining common cancer locations and their respective stages. More studies are needed to delineate the HRV patterns across different ages, between sexes and race/ethnic groups.

Association of heartbeat complexity with survival in advanced non-small cell lung cancer patients

Background

Previous studies have shown that the predictive value of traditional linear (time domain and frequency domain) heart rate variability (HRV) for the survival of patients with advanced non-small cell lung cancer (NSCLC) is controversial. Nonlinear methods, based on the concept of complexity, have been used to evaluate HRV, providing a new means to reveal the physiological and pathological changes in HRV. This study aimed to assess the association between heartbeat complexity and overall survival in patients with advanced NSCLC.

Methods

This study included 78 patients with advanced NSCLC (mean age: 62.0 ± 9.3 years). A 5-min resting electrocardiogram of advanced NSCLC patients was collected to analyze the following HRV parameters: time domain indicators, i.e., standard deviation of the normal-normal intervals (SDNN) and root mean square of successive interval differences (RMSSD); frequency domain indicators, i.e., total power (TP), low frequency power (LF), high frequency power (HF), and the ratio of LF to HF (LF/HF); nonlinear HRV indicators characterizing heartbeat complexity, i.e., approximate entropy (ApEn), sample entropy (SampEn), and recurrence quantification analysis (RQA) indexes: mean diagonal line length (Lmean), maximal diagonal line length (Lmax), recurrence rate (REC), determinism (DET), and shannon entropy (ShanEn).

Results

Univariate analysis revealed that the linear frequency domain parameter HF and nonlinear RQA parameters Lmax, REC, and DET were significantly correlated with the survival of advanced NSCLC patients (all p < 0.05). After adjusting for confounders in the multivariate analysis, HF, REC, and DET were found to be independent prognostic factors for the survival of patients with advanced NSCLC (all p < 0.05).

Conclusion

There was an independent association between heartbeat complexity and survival in advanced NSCLC patients. The nonlinear analysis method based on RQA may provide valuable additional information for the prognostic stratification of patients with advanced NSCLC and may supplement the traditional time domain and frequency domain analysis methods.

Cardiovascular Dysautonomia in Patients with Breast Cancer

Breast cancer is the most frequent malignant disease among women, being responsible for a considerable percentage of fatalities and comorbidities every year. Despite advances in early detection and therapy, evidence shows that breast cancer survivors are at increased risk of developing other chronic conditions, such as cardiovascular diseases.

Autonomic dysfunction is an emerging, but poorly understood topic that has been suggested as a risk factor for cardiovascular disease in breast cancer patients. It clinically manifests through persistently elevated heart rates and abnormal heart rate variability, even before any signs of cardiovascular dysfunction appear. Since changes in the left ventricular ejection fraction only manifest when myocardial injury has already occurred, it has been hypothesized that autonomic dysfunction can constitute an early biomarker of cardiovascular impairment in breast cancer patients.

This review focuses on the direct and indirect effects of cancer and its treatment on the autonomic nervous system in breast cancer patients. We highlight the mechanisms potentially involved in cancer and antineoplastic therapy-related autonomic imbalance and review the potential strategies to prevent and/or attenuate autonomic dysfunction.

There are gaps in the current knowledge; more research in this area is needed to identify the relevance of autonomic dysfunction and define beneficial interventions to prevent cardiovascular disease in breast cancer patients.