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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BMJ Publishing Group Ltd.
2011
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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. |
format | Online Article Text |
id | pubmed-3162041 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BMJ Publishing Group Ltd. |
record_format | MEDLINE/PubMed |
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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