Development of Prognosis in Palliative care Study (PiPS) predictor models to improve prognostication in advanced cancer: prospective cohort study

Abstract

Objective To develop a novel prognostic indicator for use in patients with advanced cancer that is significantly better than clinicians' estimates of survival.Design Prospective multicentre observational cohort study.Setting 18 palliative care services in the UK (including hospices, hospital support teams, and community teams).Participants 1018 patients with locally advanced or metastatic cancer, no longer being treated for cancer, and recently referred to palliative care services. Main outcome measuresPerformance of a composite model to predict whether patients were likely to survive for "days" (0-13 days), "weeks" (14-55 days), or "months+" (>55 days), compared with actual survival and clinicians' predictions.Results On multivariate analysis, 11 core variables (pulse rate, general health status, mental test score, performance status, presence of anorexia, presence of any site of metastatic disease, presence of liver metastases, C reactive protein, white blood count, platelet count, and urea) independently predicted both two week and two month survival. Four variables had prognostic significance only for two week survival (dyspnoea, dysphagia, bone metastases, and alanine transaminase), and eight variables had prognostic significance only for two month survival (primary breast cancer, male genital cancer, tiredness, loss of weight, lymphocyte count, neutrophil count, alkaline phosphatase, and albumin). Separate prognostic models were created for patients without (PiPS-A) or with (PiPS-B) blood results. The area under the curve for all models varied between 0.79 and 0.86. Absolute agreement between actual survival and PiPS predictions was 57.3% (after correction for over-optimism). The median survival across the PiPS-A categories was 5, 33, and 92 days and survival across PiPS-B categories was 7, 32, and 100.5 days. All models performed as well as, or better than, clinicians' estimates of survival. ConclusionsIn patients with advanced cancer no longer being treated, a combination of clinical and laboratory variables can reliably predict two week and two month survival. IntroductionPatients with advanced cancer and their carers often wish to know how long they have left to live. 1 2 Accurate prognostic information can allow patients adequate time to prepare for their impending death. 3 Qualitative studies show that patients in palliative care want to be given honest and accurate prognostic information but that this information needs to be shared sensitively and in a way that respects patients' desire to maintain hope. 4 5 Prognostic information is also important for clinicians. Realistic survival estimates can inform decisions about the appropriateness of medical interventions and the timing of referral to specialist palliative care services or admission to a hospice. Clinicians' predictions are routinely used to prioritise patients who are suitable for inclusion in programmes such as the Gold Standards Framework, 6 to determine which patients RESEARCHare suitable for "fast-tracking" arrangements for ...

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