Key result
Higher heartbeat complexity, characterized by a lower recurrence rate (≤ 33.30%), was independently associated with improved overall survival in advanced non-small cell lung cancer patients (HR 0.415).
Why the study?
The predictive value of traditional linear heart rate variability for survival in advanced NSCLC remains controversial, prompting evaluation of nonlinear heartbeat complexity methods.
Does heartbeat complexity predict overall survival in patients with advanced non-small cell lung cancer?
Cohort (n=78)
No
Does heartbeat complexity predict overall survival in patients with advanced non-small cell lung cancer?
Nonlinear heart rate variability parameters, specifically recurrence quantification analysis indexes, provide independent prognostic value for survival in patients with advanced non-small cell lung cancer.
Answers are grounded in this paper and cite their sources.
Hypothesis-generating for nonlinear HRV complexity in advanced NSCLC survival; prospective validation needed before clinical use.
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.
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Wu et al. (2023) conducted a cohort in Advanced non-small cell lung cancer (NSCLC) (n=78). Heartbeat complexity (recurrence rate ≤ 33.30%) vs. Low heartbeat complexity (recurrence rate > 33.30%) was evaluated on Overall survival (HR 0.415, 95% CI 0.192-0.896, p=0.025). Higher heartbeat complexity, characterized by a lower recurrence rate (≤ 33.30%), was independently associated with improved overall survival in advanced non-small cell lung cancer patients (HR 0.415).
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