Introduction More accurate methods of prognostication are likely to lead to improvements in the quality of care of patients approaching the ends of their lives. The Prognosis in Palliative care Scales (PiPS) predict survival in terms of ‘days’, ‘weeks’ or ‘months’ and have been shown to perform as well as, or better than Clinician Estimates of Survival (CES).1
Aims a) To validate PiPS in a new cohort of patients and b) to evaluate the accuracy of other prognostic tools.2,3
Methods This is a national, multi-centre, prospective, observational cohort study, aiming to recruit 1780 patients via palliative care services (PCS). Eligible patients have advanced, incurable cancer who have recently been referred to PCS. Patients with or without capacity are included in the study.
The primary outcome is the accuracy of PiPS predictions and the difference in accuracy between these predictions and the CES. The secondary outcomes include the accuracy of predictions by the Palliative Prognostic Score, Palliative Prognostic Index, Palliative Performance Scale, and the Feliu Prognostic Nomogram compared with actual patient survival and CES.
Results Within 10 months of recruitment, 5699 patients were screened across 27 recruiting sites. Of those, 1608 were approached to participate in the study and 940 were recruited (812 patients with and 128 patients without capacity). Updated recruitment figures and a breakdown of the reasons for ineligibility, inability to approach patients and refusal to consent will be presented.
Conclusion This study demonstrates the feasibility of recruiting large numbers of participants to a prospective palliative care study.
. Gwilliam B, Keeley V, Todd C, Roberts C, Gittins M, Kelly L, Barclay S, Stone P. Prognosticating in patients with advanced cancer-observational study comparing the accuracy of clinicians’ and patients‘ estimates of survival. Ann Oncol2013;24(2):482–488available from: PM:23028038.
. Kim ES, Lee JK, Kim MH, Noh HM, Jin YH.Validation of the prognosis in palliative care study predictor models in terminal cancer patients. Korean J Fam Med2014;35(6):283–294available from: PM:25426276
. Stone PC, Lund S. Predicting prognosis in patients with advanced cancer. AnnOncol2007;18(6):971–976available from: PM:17043092
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