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Year : 2018  |  Volume : 7  |  Issue : 3  |  Page : 125-126

Heart rate variability in male breast cancer

Department of Bio-Engineering, Birla Institute of Technology, Ranchi, Jharkhand, India

Date of Web Publication6-Dec-2018

Correspondence Address:
Ms. Reema Shyamsunder Shukla
Department of Bio.Engineering, Birla Institute of Technology, Mesra, Ranchi - 835 215, Jharkhand
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ccij.ccij_12_18

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How to cite this article:
Shukla RS, Aggarwal Y. Heart rate variability in male breast cancer. Clin Cancer Investig J 2018;7:125-6

How to cite this URL:
Shukla RS, Aggarwal Y. Heart rate variability in male breast cancer. Clin Cancer Investig J [serial online] 2018 [cited 2019 May 22];7:125-6. Available from:

Male breast cancer (BC) constitutes 1% of all the BC cases.[1] BC has known to be the second most common cause of death after lung cancer.[2] Electrocardiogram was recorded from 4 male BC patients and 17 healthy controls using an MP45 bioamplifier (Biopac Systems Inc., USA). The heart rate variability (HRV) time, and spectral and nonlinear domain based parameters were extracted from the tachogram obtained from Acknowledge 4.0 software (Biopac Systems Inc., Goleta, USA) using HRV analysis tool (Kubios HRV 2.0, University of Finland, Finland). The study showed that patients had decreased values of mean RR intervals, standard deviation (SD) of normal RR intervals (SDNN), square root of mean of successive differences of RR intervals (RMSSD), normalized unit (nu) of low frequency (LF), ratio of LF to high frequency (LF/HF), SD perpendicular to the line of identity (LOI) (SD1), SD along LOI (SD2), recurrence plots (Lmean, Lmax, and Shannon entropy [ShanEn]), and correlation dimension (CD). Furthermore, it was found that few HRV parameters had increased values, namely, average of heart rate (mHR), SD of heart rate (SDHR), nu of high frequency (HF), LF/HF, ratio of SD1 to SD2 (SD1/SD2), approximate entropy (ApEn), sample entropy (SampEn), and long-term detrended fluctuation (α2). The decreased values of SDNN and RMSSD indicate sympathetic dominance. The increased values of ApEn and SampEn indicate stress and panic disorder. Higher α2 indicates the diseased state. The decreased values of SD1, SD2, Lmax, ShanEn, and CD indicate the decreased complexity of the signal. Healthy male controls have higher values of HRV measures than patients, which indicates the diseased state of male BC patients.[3],[4],[5],[6] All the values of HRV measures are summarized in [Table 1] in the form of mean ± standard error. To conclude, the decreased values of HRV measures in male BC patients in comparison with healthy male controls prove autonomic dysfunction due to withdrawal of parasympathetic activity.
Table 1: Heart rate variability measures in breast cancer male patients and healthy male controls

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The authors are grateful to Dr. Rajesh Singh (Professor and Head, Indira Gandhi Institute of Medical Sciences, Cancer Centre, Patna, India) and Dr. Seema, Dr. Richa Madhavi, and Dr. Dinesh Sinha (Assistant Professor). Also, the authors express their gratitude to Dr. Shreeniwas Raut, Medical Oncology Consultant, HMRI Paras Hospital, Patna, for permitting for data collection in the hospital. The authors are also thankful to Dr. Rakesh Sinha (Professor, Department of Bio-Engineering, Birla Institute of Technology, Mesra, Ranchi, India) for his technical inputs for the work.

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Conflicts of interest

There are no conflicts of interest.

  References Top

Gómez-Raposo C, Zambrana Tévar F, Sereno Moyano M, López Gómez M, Casado E. Male breast cancer. Cancer Treat Rev 2010;36:451-7.  Back to cited text no. 1
Paulin F, Santhakumaran A. Classification of breast cancer by comparing back propagation training algorithms. Int J Comput Sci Eng 2011;3:327-32.  Back to cited text no. 2
Shukla RS, Aggarwal Y. Spectral analysis to evaluate the effect of treatment on autonomic nervous system in pulmonary metastasis. Int J Eng Technol Sci Res 2017;4:501-6.  Back to cited text no. 3
Shukla RS, Aggarwal Y. Heart rate variability time-domain analysis in pulmonary Metastasis to assess performance status. Indian J Sci Res 2017;14:540-5.  Back to cited text no. 4
Shukla RS, Aggarwal Y. Time-domain heart rate variability-based computer-aided prognosis of lung cancer. Indian J Cancer 2017. [doi: 10.4103/ijc.IJC_395_17]. [In press].  Back to cited text no. 5
Shukla RS, Aggarwal Y. Nonlinear heart rate variability based artificial intelligence in lung cancer. J Appl Biomed 2017. [doi: 10.1016/j.jab. 2017.12.002]. [In press].  Back to cited text no. 6


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