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    • "It is well documented that clinicians are overly optimistic in estimating survival prognosis [1], [2]. A systematic review concluded that an accurate survival prediction within one week occurred in only 25% of cases [3]. Survival prediction scales for advanced cancer patients are typically composed of a combination of clinical symptoms and signs, laboratory data, and physicians' estimation. "
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    ABSTRACT: A 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. A 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. The 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). In 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.
    PLoS ONE 07/2013; 8(7):e69482. DOI:10.1371/journal.pone.0069482 · 3.23 Impact Factor
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    • "In hospice palliative care, an important issue is the ability to accurately predict the probability of survival of terminal cancer patients with short-term survival. Patients, family members, and providers may desire this information for their plans and decisions about "pain and distress;" clinicians may want to improve their prognostic skills [1,2]. When death is near, goals and plans of management often shift and a clinical pathway has been developed to guide care [3]. "
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    ABSTRACT: The ability to identify patients for hospice care results in better end-of-life care. To develop a validated prognostic scale for 7-day survival prediction, a prospective observational cohort study was made of patients with terminal cancer. Patient data gathered within 24 hours of hospital admission included demographics, clinical signs and symptoms and their severity, laboratory test results, and subsequent survival data. Of 727 patients enrolled, data from 374 (training group) was used to develop a prognostic tool, with the other 353 serving as the validation group. Five predictors identified by multivariate logistic regression analysis included patient's cognitive status, edema, ECOG performance status, BUN and respiratory rate. A formula of the predictor model based on those five predictors was constructed. When probability was >0.2, death within 7 days was predicted in the training group and validation group, with sensitivity of 80.9% and 71.0%, specificity of 65.9% and 57.7%, positive predictive value of 42.6% and 26.8%, and negative predictive value (NPV) of 91.7% and 90.1%, respectively. This predictor model showed a relatively high sensitivity and NPV for predicting 7-day survival among terminal cancer patients, and could increase patient satisfaction by improving end-of-life care.
    BMC Public Health 09/2009; 9(1):365. DOI:10.1186/1471-2458-9-365 · 2.26 Impact Factor
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    ABSTRACT: The appropriate role of antitumour therapies in far advanced cancer patients is a complex issue and the switch to best supportive care alone is often a difficult choice as there are no international guidelines on the minimum amount of benefit needed to justify the use of palliative chemotherapy. New chemotherapeutic drugs with well-tolerated toxic profiles are increasingly available and patients’ expectations often influence physicians to continue chemotherapy in the absence of a clear appropriateness principle, even when death is approaching. Recruitment in phase I studies is an opportunity to offer a potential, albeit rare, benefit when no other therapeutic options are available. Although communication and understanding between the physician, patient and family is pivotal to avoid futile care in cancer, modern clinicians often find themselves in difficulty when having to inform patients about a poor prognosis, mainly because they are all too aware of the poor accuracy of predictions about life-expectancy. Several tools on prognosis prediction are now available to help physicians discriminate between patients who could benefit from palliative chemotherapy and those for whom supportive and palliative approaches would be more suitable. It has also been seen that the management of patients with far advanced cancers is improved by close collaboration between palliative care experts and oncologists. KeywordsPalliative care-Appropriateness of therapy-Prognosis
    12/2010; 8(3):112-120. DOI:10.1007/s12682-010-0062-6
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