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A systematic review of physicians' survival predictions in terminally ill cancer patients

Journal

BRITISH MEDICAL JOURNAL
Volume 327, Issue 7408, Pages 195-198

Publisher

BRITISH MED JOURNAL PUBL GROUP
DOI: 10.1136/bmj.327.7408.195

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Objective To systematically review the accuracy of physicians clinical predictions of survival in terminally ill cancer patients. Data sources Cochrane Library, Medline (1996-2000), Embase, Current Contents, and Cancerlit databases as well as hand searching. Study selection Studies were included if a physician's temporal clinical prediction of survival (CPS) and the actual survival (AS) for terminally ill cancer patients were available for statistical analysis. Study quality was assessed by using a critical appraisal tool produced by the local health authority. Data synthesis Raw data were pooled and analysed with regression and other multivariate techniques. Results 17 published Studies were identified; 12 met the inclusion criteria, and 8 were evaluable, providing 1563 individual prediction-survival dyads. CPS was generally overoptimistic (median CPS 42 days, median AS 29 days); it was correct to within one week in 25% of cases and overestimated survival by at least four weeks in 27%. The longer the CPS the greater the variability in AS. Although agreement between CPS and AS was poor (weighted K 0.36), the two were highly significantly associated after log transformation (Spearman rank correlation 0.60, P < 0.001). Consideration of performance status, symptoms, and use of steroids improved the accuracy of the CPS, although the additional value was small. Heterogeneity of the studies results precluded a comprehensive meta-analysis. Conclusions Although clinicians consistently overestimate survival, their predictions are highly correlated with actual Survival; die predictions have discriminatory ability even if they are miscalibrated. Clinicians caring for patients with terminal cancer 0 need to be aware of their tendency to overestimate survival. as it may affect patients prospects for achieving, a good death. Accurate prognostication 0 0 models incorporating clinical prediction of survival are needed.

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