In an article, published in Frontiers in Neuroscience, researchers sought to uncover associations between heart rate variability (HRV) and overall survival (OS) in patients with lung cancer with brain metastases (LCBM). The study’s co-lead authors, Shuang Wu and Guangqiao Li, reported that decreased root mean square of successive differences (RMSSD)—one of the time parameters of HRV assessed in the study—was independently associated with shorter survival time in patients with LCBM.
The prospective study enrolled 56 patients with LCBM from one center who had received first-time radiotherapy between 2019 and 2021. In addition to RMSSD, HRV was analyzed with the standard deviation of all normal-normal intervals (SDNN) parameter. The survival time was defined as “date of HRV testing to the date of death or the last follow-up.” Multivariate analysis was used to validate any factors that demonstrated associations with survival in patients with LCBM.
According to the study’s collaborators, univariate analysis identified that HRV parameters of SDNN ≤13 ms (p = 0.003) and RMSSD ≤4.8 ms (p = 0.014) were significant predictors of poor survival. In the multivariate analysis, RMSSD ≤4.8 ms (hazard ratio = 3.457; 95% confidence interval [CI], 1.303–9.171; p = 0.013) was additionally confirmed as “an independent negative prognostic factor after adjusting for mean heart rate, Karnofsky performance status, and number of brain metastases in LCBM patients.”
The authors did acknowledge that the study was limited by heterogeneity in radiotherapy method and dose among the patients, as well as only 24 (42.9%) of study participants surviving until the end of the investigation. They called for further studies with larger sample sizes and longer follow-up periods to validate their prospective findings.
In closing, the study’s authors suggested that HRV parameters may be an effective prognostic tool for predicting survival in patients with LCBM. If their findings were validated, “it may be possible to tailor personalized treatment strategies and perform prognostic evaluations based on patient vagal activity,” the researchers concluded.