Predicting survival in patients with advanced cancer in the last weeks of life: How accurate are prognostic models compared to clinicians’ estimates?

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Abstract

Background:

It is unclear if validated prognostic scores such as the Palliative Performance Scale, Palliative Prognostic Index, and Palliative Prognostic Score are more accurate than clinician prediction of survival in patients admitted to an acute palliative care unit with only days of survival.

Aim:

We compared the prognostic accuracy of Palliative Performance Scale, Palliative Prognostic Index, Palliative Prognostic Score, and clinician prediction of survival in this setting.

Design:

This is a pre-planned secondary analysis of a prospective study.

Setting/participants:

We assessed Palliative Performance Scale, Palliative Prognostic Index, Palliative Prognostic Score, and clinician prediction of survival at baseline. We computed their prognostic accuracy using the Concordance index and area under the receiver operating characteristics curve for 7-, 14-, and 30-day survival.

Results:

A total of 204 patients were included with a median overall survival of 10 days (95% confidence interval: 8–11 days). The Concordance index for Palliative Performance Scale, Palliative Prognostic Index, Palliative Prognostic Score, and clinician prediction of survival were 0.74, 0.71, 0.70, and 0.75, respectively. The areas under the curve for these approaches were 0.82–0.87 for 30-day survival, 0.75–0.80 for 14-day survival, and 0.74–0.81 for 7-day survival. The four prognostic approaches had similar accuracies, with the exception of 7-day survival in which clinician prediction of survival was significantly more accurate than Palliative Prognostic Score (difference: 7%) and Palliative Prognostic Index (difference: 8%).

Conclusion:

In patients with advanced cancer with days of survival, clinician prediction of survival and Palliative Performance Scale alone were as accurate as Palliative Prognostic Score and Palliative Prognostic Index. These four approaches may be useful for prognostication in acute palliative care units. Our findings highlight how patient population may impact the accuracy of prognostic scores.

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Most cited references 35

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The Palliative Prognostic Index: a scoring system for survival prediction of terminally ill cancer patients.

S. Inoue, S Chihara, J Tsunoda … (1999)

Although accurate prediction of survival is essential for palliative care, few clinical methods of determining how long a patient is likely to live have been established. To develop a validated scoring system for survival prediction, a retrospective cohort study was performed with a training-testing procedure on two independent series of terminally ill cancer patients. Performance status (PS) and clinical symptoms were assessed prospectively. In the training set (355 assessments on 150 patients) the Palliative Prognostic Index (PPI) was defined by PS, oral intake, edema, dyspnea at rest, and delirium. In the testing sample (233 assessments on 95 patients) the predictive values of this scoring system were examined. In the testing set, patients were classified into three groups: group A (PPI 4.0). Group B survived significantly longer than group C, and group A survived significantly longer than either of the others. Also, when a PPI of more than 6 was adopted as a cut-off point, 3 weeks' survival was predicted with a sensitivity of 80% and a specificity of 85%. When a PPI of more than 4 was used as a cutoff point, 6 weeks' survival was predicted with a sensitivity of 80% and a specificity of 77%. In conclusion, whether patients live longer than 3 or 6 weeks can be acceptably predicted by PPI.

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Identifying Potential Indicators of the Quality of End-of-Life Cancer Care From Administrative Data

Bonnie Lai, Jane Weeks, John Ayanian … (2003)

To explore potential indicators of the quality of end-of-life services for cancer patients that could be monitored using existing administrative data.