Longitudinal Temporal and Probabilistic Prediction of Survival in a Cohort of Patients With Advanced Cancer

Context. Survival prognostication is important during the end of life. The accuracy of clinician prediction of survival (CPS) over time has not been well characterized. Objectives. The aims of the study were to examine changes in prognostication accuracy during the last 14 days of life in a cohort of patients with advanced cancer admitted to two acute palliative care units and to compare the accuracy between the temporal and probabilistic approaches. Methods. Physicians and nurses prognosticated survival daily for cancer patients in two hospitals until death/discharge using two prognostic approaches: temporal and probabilistic. We assessed accuracy for each method daily during the last 14 days of life comparing accuracy at Day - 14 (baseline) with accuracy at each time point using a test of proportions. Results. A total of 6718 temporal and 6621 probabilistic estimations were provided by physicians and nurses for 311 patients, respectively. Median (interquartile range) survival was 8 days (4-20 days). Temporal CPS had low accuracy (10%-40%) and did not change over time. In contrast, probabilistic CPS was significantly more accurate (P < .05 at each time point) but decreased close to death. Conclusion. Probabilistic CPS was consistently more accurate than temporal CPS over the last 14 days of life; however, its accuracy decreased as patients approached death. Our findings suggest that better tools to predict impending death are necessary. (C) 2014 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.