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Prognostic and Diagnostic Utility of Heart Rate Variability to Predict and Understand Change in Cancer and Chemotherapy Related Fatigue, Pain, and Neuropathic Symptoms: A Systematic Review

Bolanos, J. L.; Hneiny, L.; Gonzalez, J. P.; O'Malley, M. E.; Wong, M. L.

2025-01-08 oncology
10.1101/2025.01.08.25320191 medRxiv
Show abstract

Advances in early cancer detection and treatment have significantly improved survival rates, resulting in over 18.1 million cancer survivors in the United States. Many of these survivors experience chronic pain, fatigue, and neuropathic symptoms related to cancer or its treatments. Emerging evidence suggests that autonomic nervous system dysfunction plays a crucial role in these symptoms. Heart rate variability (HRV), a measure of autonomic function, has shown potential in predicting the onset of somatic symptoms in cancer patients. This systematic review aimed to assess the association of HRV with pain, fatigue, and neuropathy in cancer patients and survivors. A comprehensive search was conducted across multiple databases, yielding 19 studies that met inclusion criteria. These studies varied in cancer types, stages, and HRV measurement methods. Most studies focused on breast cancer and reported a predominant female population. Fatigue was the most studied symptom, followed by pain. HRV measures included both time and frequency domain variables, with significant variability in measurement duration and control for confounding factors. Findings suggest that decreased HRV is associated with increased fatigue and pain, providing potential support for a bidirectional relationship between autonomic dysfunction and these symptoms. However, the heterogeneity in HRV measurement methods and the high risk of bias in many studies highlight the need for standardized HRV protocols in cancer research. Further large-scale studies with low risk of bias are necessary to validate HRV as a reliable tool for phenotyping and managing cancer-related symptoms.

Published in Supportive Care in Cancer · not in our set (fewer than 10 published preprints to learn from) · training set

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