title: 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.
  
  
  METHODS
  Prospective multicentre observational cohort study.
  
  
  METHODS
  18 palliative care services in the UK (including hospices, hospital support teams, and community teams).
  
  
  METHODS
  1018 patients with locally advanced or metastatic cancer, no longer being treated for cancer, and recently referred to palliative care services.
  
  
  METHODS
  Performance 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.
  
  
  CONCLUSIONS
  In patients with advanced cancer no longer being treated, a combination of clinical and laboratory variables can reliably predict two week and two month survival.
authors.affiliation: Division of Population, Health Sciences and Education, St George's University of London, London SW17 0RE, UK.
authors.forename: Bridget
authors.initials: B
authors.lastname: Gwilliam
authors.affiliation: Royal Derby Hospital, Derby, UK.
authors.forename: Vaughan
authors.initials: V
authors.lastname: Keeley
authors.affiliation: School of Nursing, Midwifery and Social Work, University of Manchester, Manchester, UK.
authors.forename: Chris
authors.initials: C
authors.lastname: Todd
authors.affiliation: Health Sciences, School of Community Based Medicine, University of Manchester.
authors.forename: Matthew
authors.initials: M
authors.lastname: Gittins
authors.affiliation: Health Sciences, School of Community Based Medicine, University of Manchester.
authors.forename: Chris
authors.initials: C
authors.lastname: Roberts
authors.affiliation: Macmillan Consultant in Palliative Care Team, East Surrey Hospital, Surrey and Sussex Healthcare NHS Trust, Redhill, Surrey, UK.
authors.forename: Laura
authors.initials: L
authors.lastname: Kelly
authors.affiliation: General Practice and Primary Care Research Unit, Department of Public Health and Primary Care, Institute of Public Health, Cambridge, UK.
authors.forename: Stephen
authors.initials: S
authors.lastname: Barclay
authors.affiliation: Division of Population, Health Sciences and Education, St George's University of London, London SW17 0RE, UK.
authors.forename: Patrick C
authors.initials: PC
authors.lastname: Stone