This is the first study to evaluate the association between cardiovascular autonomic functions and TTD in patients with terminal hepatocellular carcinoma. The inclusion of HRV measurement in prognostic models may improve accuracy in TTD prediction and, hence, facilitate medical decision making in hospice care.

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BackgroundA simple and accurate survival prediction tool can facilitate decision making processes for hospice patients with advanced cancers. The objectives of this study were to explore the association of cardiac autonomic functions and survival in patients with advanced cancer and to evaluate the prognostic value of heart rate variability (HRV) in 7-day survival prediction.MethodsA prospective study was conducted on 138 patients with advanced cancer recruited from the hospice ward of a regional hospital in southern Taiwan. Information on functional status and symptom burden of the patients was recorded. Frequency-domain HRV was obtained for the evaluation of cardiac autonomic functions at admission. The end point of the study was defined as the survival status at day 7 after admission to the hospice ward. Multivariate logistic regression analyses were performed to evaluate the independent associations between HRV indices and survival of 7 days or less.ResultsThe median survival time of the patients was 20 days (95% CI, 17–28 days). Results from the multivariate logistic regression analysis indicated that the natural logarithm-transformed high-frequency power (lnHFP) of a value less than 2 (OR = 3.8, p = 0.008) and ECOG performance status of 3 or 4 (OR = 3.4, p = 0.023) were significantly associated with a higher risk of survival of 7 days or less. Receiver operating characteristic (ROC) curve analysis revealed that the area under the curve was 0.71 (95% CI, 0.61–0.81).ConclusionsIn hospice patients with non-lung cancers, an lnHPF value below 2 at hospice admission was significantly associated with survival of 7 days or less. HRV might be used as a non-invasive and objective tool to facilitate medical decision making by improving the accuracy in survival prediction.