Research Article
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Published Online: 13 October 2006

Use of Palliative Performance Scale in End-of-Life Prognostication

Publication: Journal of Palliative Medicine
Volume 9, Issue Number 5


Background: Current literature suggests clinicians are not accurate in prognostication when estimating survival times of palliative care patients. There are reported studies in which the Palliative Performance Scale (PPS) is used as a prognostic tool to predict survival of these patients. Yet, their findings are different in terms of the presence of distinct PPS survival profiles and significant covariates.
Objective: This study investigates the use of PPS as a prognostication tool for estimating survival times of patients with life-limiting illness in a palliative care unit. These findings are compared to those from earlier studies in terms of PPS survival profiles and covariates. Methods: This is a retrospective cohort study in which the admission PPS scores of 733 palliative care patients admitted between March 3, 2000 and August 9, 2002 were examined for survival patterns. Other predictors for survival included were age, gender, and diagnosis.
Results: Study findings revealed that admission PPS score was a strong predictor of survival in patients already identified as palliative, along with gender and age, but diagnosis was not significantly related to survival. We also found that scores of PPS 10% through PPS 50% led to distinct survival curves, and male patients had consistently lower survival rates than females regardless of PPS score.
Conclusion: Our findings differ somewhat from earlier studies that suggested the presence of three distinct PPS survival profiles or bands, with diagnosis and noncancer as significant covariates. Such differences are likely attributed to the size and characteristics of the patient populations involved and further analysis with larger patient samples may help clarify PPS use in prognosis.

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cover image Journal of Palliative Medicine
Journal of Palliative Medicine
Volume 9Issue Number 5October 2006
Pages: 1066 - 1075
PubMed: 17040144


Published online: 13 October 2006
Published in print: October 2006


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Francis Lau, Ph.D.
Health Information Science, University of Victoria, Victoria, British Columbia, Canada.
G. Michael Downing, M.D.
Victoria Hospice Society, Victoria, British Columbia, Canada.
Mary Lesperance, Ph.D.
Department of Mathematics and Statistics, University of Victoria, Victoria, British Columbia, Canada.
Jack Shaw, B.Sc.
Health Information Science, University of Victoria, Victoria, British Columbia, Canada.
Craig Kuziemsky, B.Com.
Health Information Science, University of Victoria, Victoria, British Columbia, Canada.

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