Survival Prediction in Terminally Ill Cancer Patients by Clinical Estimates, Laboratory Tests, and Self-Rated Anxiety and Depression

Gripp, Stephan; Moeller, S.; Bölke, Edwin; Schmitt, G; Matuschek, Christiane; Asgari, Sonja; Asgharzadeh, Farzin; Roth, Stephan; Budach, Wilfried; Franz, Matthias; Willers, R.

doi:10.1200/jco.2006.10.5411

Cited by 256 publications

(205 citation statements)

References 45 publications

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“…Christakis et al (2000) reported than only 20% of predictions were accurate and 63% were over-optimistic by a factor of 5.3. Gripp et al (2007) reported similarly that 71-96% of estimates of survival of patients who died within one month were over-optimistic. One head-to-head direct comparison of CPS and prognostic scores in terminally ill patients by Stiel et al (2010) reported lower correlation with actual survival for CPS than for either PPI or PaP.…”

Section: Discussionmentioning

confidence: 97%

Validation of a Palliative Prognostic Index to Predict Life Expectancy for Terminally Ill Cancer Patients in a Hospice Consultation Setting in Taiwan

Cheng¹,

Kao²,

Hung³

et al. 2012

Asian Pacific Journal of Cancer Prevention

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Background: The aim of our study was to assess the practical utility of the palliative prognostic index (PPI) as a prognostic tool used by nurse specialists in a hospice consultation setting in Taiwan The sensitivity and specificity for the poor prognosis group was 66% and 71%; the positive predictive value and negative predictive value were 81% and 52%, respectively, to predict patient death within 21 days (area under the curve of the receiver operating characteristic was 0.68). Conclusions: Assessment by PPI can accurately predict survival of terminal cancer patients receiving hospice consultation care. PPI is a simple tool and can be administered by nurse members of hospice consultation teams.

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Section: Discussionmentioning

confidence: 97%

Validation of a Palliative Prognostic Index to Predict Life Expectancy for Terminally Ill Cancer Patients in a Hospice Consultation Setting in Taiwan

Cheng¹,

Kao²,

Hung³

et al. 2012

Asian Pacific Journal of Cancer Prevention

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“…The main indicators of this final phase are poor performance status; weight loss; symptoms such as appetite loss, breathlessness, or confusion; and abnormalities on some laboratory parameters, including high white cell count, lymphopenia, hypoalbuminemia, and elevated lactate dehydrogenase or C-reactive protein. 4,5,13 Recently, a two-week survival prognostic model that incorporated both biochemical markers and the presence of appetite loss, dyspnea, and edema 14 was used in a palliative care unit.…”

Section: Discussionmentioning

confidence: 99%

Prognostic Factors of Survival in Patients With Advanced Cancer Admitted to Home Care

Mercadante

Valle²,

Porzio

et al. 2013

Journal of Pain and Symptom Management

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Context. Data regarding prognostication of life expectancy in patients with advanced cancer are of paramount importance to patients, families, and clinicians. However, data regarding patients followed at home are lacking.Objectives. The aim of this study was to evaluate the correlation between various factors recorded at the beginning of home care assistance and survival.Methods. A sample of consecutive patients admitted to two home care programs was surveyed. A preliminary consensus was achieved as to the possible variables easy to be recorded at home. These included age at the time of home care admission, gender, residence, marital status, primary cancer diagnosis, Karnofsky Performance Status (KPS) score, measures of systolic blood pressure and heart rate, cyanosis, use of oxygen, and body temperature. The Edmonton Symptom Assessment System was used to record the intensity of each symptom. Patients were divided into two groups: patients with a survival of less than 10 days (short survival) and patients with a survival of 10 days or more (medium-long survival).Results. Three hundred seventy-four consecutive patients admitted to home care programs were surveyed, of which 187 were male. The mean AE SD age was 72.1 AE 12.7 years. The mean survival was 56.2 AE 65 days. Mean survival was 71.5 AE 67 days (287 patients) and 5.6 AE 2.7 days (87 patients) in the short and medium-long survival groups, respectively. No association between type of tumor and survival was observed (P ¼ 0.162). Univariate logistic regression analysis revealed that male gender (P ¼ 0.020), older age (P ¼ 0.012), lower KPS scores (P < 0.0005), systolic blood pressure less than 100 mm Hg (P ¼ 0.003), heart rate greater than 100 beats per minute (P ¼ 0.0006), delirium (P ¼ 0.004), the use of oxygen (P ¼ 0.002), intensity of fatigue (P ¼ 0.006), drowsiness (P < 0.0005), anorexia (P < 0.0005), dyspnea (P < 0.0005), poor sense of well-being (P < 0.0005), and distress score (P < 0.0005) were associated with a survival of less than 10 days. Marital status, residence, cognitive function, fever, pain, depression, and anxiety were not found to be significantly correlated with survival. In a multiple logistic regression model, low systolic blood pressure and high heart rate, gender, delirium, use of oxygen, KPS score, drowsiness, anorexia, and dyspnea were significantly correlated with a shorter survival. Conclusion. Low systolic blood pressure and high heart rate, male gender, poor KPS score, anorexia, and dyspnea were correlated with a shorter survival. Moreover, patients with low systolic blood pressure and high heart rate, male gender, poor KPS score, and greater intensity of anorexia and dyspnea are more likely to die within one week. The combination of physical symptoms from the Edmonton Symptom Assessment System and other parameters included in this study, which are simple to assess and are repeatable at home, should be further explored in future studies to provide a simple tool for use with patients with advanced cancer admitted to a home...

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“…Furthermore, stressors may be responsible for cognitive complaints, especially in the domain of memory, which could have a role in diminishing treatment compliance 107 . However, at a mechanistic level, mounting evidence indicates that chronic stress confer increased vulnerability to chronic diseases amplifying pro-inflammatory signals via an increased production of cytokines and other immune mediators, as well as via a decreased sensitivity to hormonal inhibitory control by the HPA axis, as well altered autonomic responses 108,109 .…”

Section: Stress As a Modulator Of Immune Response In Depression And Cmentioning

confidence: 99%

Depression in cancer: The many biobehavioral pathways driving tumor progression

Bortolato

Hyphantis

Valpione

et al. 2017

Cancer Treatment Reviews

248

179

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Major Depressive Disorder (MDD) is common among cancer patients, with prevalence rates up to four-times higher than the general population. Depression confers worse outcomes, including non-adherence to treatment and increased mortality in the oncology setting. Advances in the understanding of neurobiological underpinnings of depression have revealed shared biobehavioral mechanisms may contribute to cancer progression. Moreover, psychosocial stressors in cancer promote:(1) inflammation and oxidative/nitrosative stress; (2) a decreased immunosurveillance; and (3) a dysfunctional activation of the autonomic nervous system and of the hypothalamic-pituitary-adrenal axis. Consequently, the prompt recognition of depression among patients with cancer who may benefit of treatment strategies targeting depressive symptoms, cognitive dysfunction, fatigue and sleep disturbances, is a public health priority. Moreover, behavioral strategies aiming at reducing psychological distress and depressive symptoms, including addressing unhealthy diet and life-style choices, as well as physical inactivity and sleep dysfunction, may represent important strategies not only to treat depression, but also to improve wider cancer-related outcomes. Herein, we provide a comprehensive review of the intertwined biobehavioural pathways linking depression to cancer progression. In addition, the clinical implications of these findings are critically reviewed.

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Survival Prediction in Terminally Ill Cancer Patients by Clinical Estimates, Laboratory Tests, and Self-Rated Anxiety and Depression

Abstract: This study revealed that physicians' survival estimates were unreliable, especially in the case of patients near death. Self-reported emotional distress and objective PFs may improve the accuracy of survival estimates.

Cited by 256 publications

References 45 publications

Validation of a Palliative Prognostic Index to Predict Life Expectancy for Terminally Ill Cancer Patients in a Hospice Consultation Setting in Taiwan

Validation of a Palliative Prognostic Index to Predict Life Expectancy for Terminally Ill Cancer Patients in a Hospice Consultation Setting in Taiwan

Prognostic Factors of Survival in Patients With Advanced Cancer Admitted to Home Care

Depression in cancer: The many biobehavioral pathways driving tumor progression

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