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

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 suppo...

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Autores principales: Gwilliam, Bridget, Keeley, Vaughan, Todd, Chris, Gittins, Matthew, Roberts, Chris, Kelly, Laura, Barclay, Stephen, Stone, Patrick C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group Ltd. 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3162041/
https://www.ncbi.nlm.nih.gov/pubmed/21868477
http://dx.doi.org/10.1136/bmj.d4920
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author Gwilliam, Bridget
Keeley, Vaughan
Todd, Chris
Gittins, Matthew
Roberts, Chris
Kelly, Laura
Barclay, Stephen
Stone, Patrick C
author_facet Gwilliam, Bridget
Keeley, Vaughan
Todd, Chris
Gittins, Matthew
Roberts, Chris
Kelly, Laura
Barclay, Stephen
Stone, Patrick C
author_sort Gwilliam, Bridget
collection PubMed
description 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 measures 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.
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spelling pubmed-31620412011-09-08 Development of Prognosis in Palliative care Study (PiPS) predictor models to improve prognostication in advanced cancer: prospective cohort study Gwilliam, Bridget Keeley, Vaughan Todd, Chris Gittins, Matthew Roberts, Chris Kelly, Laura Barclay, Stephen Stone, Patrick C BMJ Research 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 measures 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. BMJ Publishing Group Ltd. 2011-08-25 /pmc/articles/PMC3162041/ /pubmed/21868477 http://dx.doi.org/10.1136/bmj.d4920 Text en © Gwilliam et al 2011 This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode.
spellingShingle Research
Gwilliam, Bridget
Keeley, Vaughan
Todd, Chris
Gittins, Matthew
Roberts, Chris
Kelly, Laura
Barclay, Stephen
Stone, Patrick C
Development of Prognosis in Palliative care Study (PiPS) predictor models to improve prognostication in advanced cancer: prospective cohort study
title Development of Prognosis in Palliative care Study (PiPS) predictor models to improve prognostication in advanced cancer: prospective cohort study
title_full Development of Prognosis in Palliative care Study (PiPS) predictor models to improve prognostication in advanced cancer: prospective cohort study
title_fullStr Development of Prognosis in Palliative care Study (PiPS) predictor models to improve prognostication in advanced cancer: prospective cohort study
title_full_unstemmed Development of Prognosis in Palliative care Study (PiPS) predictor models to improve prognostication in advanced cancer: prospective cohort study
title_short Development of Prognosis in Palliative care Study (PiPS) predictor models to improve prognostication in advanced cancer: prospective cohort study
title_sort development of prognosis in palliative care study (pips) predictor models to improve prognostication in advanced cancer: prospective cohort study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3162041/
https://www.ncbi.nlm.nih.gov/pubmed/21868477
http://dx.doi.org/10.1136/bmj.d4920
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