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Clin Oncol (R Coll Radiol). 2001;13(3):209-18.

How accurate are physicians' clinical predictions of survival and the available prognostic tools in estimating survival times in terminally ill cancer patients? A systematic review.

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  • 1Department of Radiation Oncology, Toronto-Sunnybrook Regional Cancer Centre, University of Toronto, Canada. Edward.Chow@tsrcc.on.ca

Abstract

The purpose of this review was to examine the accuracy of physicians' clinical predictions of survival and the available prognostic tools in estimating survival times in terminally ill cancer patients. A MEDLINE search for English language articles published between 1966 and March 2000 was performed using the following keywords: forecasting/clinical prediction, prognosis/prognostic factors, survival and neoplasm metastasis. Searches in CancerLit, EMBASE, PubMed, the Cochrane Library and reference sections of articles were performed. Studies were included if they concerned adult patients with various cancer histological diagnoses and employed clinical prediction and the readily available clinical parameters. Biochemical and molecular markers were excluded. Grading of the evidence and recommendations was performed. Twelve articles on clinical prediction and 19 on prognostic factors met the inclusion criteria. Clinical prediction tends to be incorrect in the optimistic direction but improves with repeated measurements. Performance status has been found to be most strongly correlated with the duration of survival, followed by the 'terminal syndrome', which includes anorexia, weight loss and dysphagia. Cognitive failure and confusion have also been associated with a shorter life span. Performance status combined with clinical symptoms and the clinician's estimate helps to guide an accurate prediction, as reviewed in an Italian series. There is fair evidence to support using performance status, and clinical and biochemical parameters, in addition to clinicians' judgement to aid survival prediction. However, there is weak evidence to support that clinicians' estimates alone could be specifically employed for survival prediction.

PMID:
11527298
[PubMed - indexed for MEDLINE]
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