Cargando…
Lung cancer prognostic index: a risk score to predict overall survival after the diagnosis of non-small-cell lung cancer
INTRODUCTION: Non-small-cell lung cancer outcomes are poor but heterogeneous, even within stage groups. To improve prognostic precision we aimed to develop and validate a simple prognostic model using patient and disease variables. METHODS: Prospective registry and study data were analysed using Cox...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5572183/ https://www.ncbi.nlm.nih.gov/pubmed/28728168 http://dx.doi.org/10.1038/bjc.2017.232 |
_version_ | 1783259479304830976 |
---|---|
author | Alexander, Marliese Wolfe, Rory Ball, David Conron, Matthew Stirling, Robert G Solomon, Benjamin MacManus, Michael Officer, Ann Karnam, Sameer Burbury, Kate Evans, Sue M |
author_facet | Alexander, Marliese Wolfe, Rory Ball, David Conron, Matthew Stirling, Robert G Solomon, Benjamin MacManus, Michael Officer, Ann Karnam, Sameer Burbury, Kate Evans, Sue M |
author_sort | Alexander, Marliese |
collection | PubMed |
description | INTRODUCTION: Non-small-cell lung cancer outcomes are poor but heterogeneous, even within stage groups. To improve prognostic precision we aimed to develop and validate a simple prognostic model using patient and disease variables. METHODS: Prospective registry and study data were analysed using Cox proportional hazards regression to derive a prognostic model (hospital 1, n=695), which was subsequently tested (Harrell’s c-statistic for discrimination and Cox–Snell residuals for calibration) in two independent validation cohorts (hospital 2, n=479 and hospital 3, n=284). RESULTS: The derived Lung Cancer Prognostic Index (LCPI) included stage, histology, mutation status, performance status, weight loss, smoking history, respiratory comorbidity, sex, and age. Two-year overall survival rates according to LCPI in the derivation and two validation cohorts, respectively, were 84, 77, and 68% (LCPI 1: score⩽9); 61, 61, and 42% (LCPI 2: score 10–13); 33, 32, and 14% (LCPI 3: score 14–16); 7, 16, and 5% (LCPI 4: score ⩾15). Discrimination (c-statistic) was 0.74 for the derivation cohort, 0.72 and 0.71 for the two validation cohorts. CONCLUSIONS: The LCPI contributes additional prognostic information, which may be used to counsel patients, guide trial eligibility or design, or standardise mortality risk for epidemiological analyses. |
format | Online Article Text |
id | pubmed-5572183 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-55721832018-08-22 Lung cancer prognostic index: a risk score to predict overall survival after the diagnosis of non-small-cell lung cancer Alexander, Marliese Wolfe, Rory Ball, David Conron, Matthew Stirling, Robert G Solomon, Benjamin MacManus, Michael Officer, Ann Karnam, Sameer Burbury, Kate Evans, Sue M Br J Cancer Epidemiology INTRODUCTION: Non-small-cell lung cancer outcomes are poor but heterogeneous, even within stage groups. To improve prognostic precision we aimed to develop and validate a simple prognostic model using patient and disease variables. METHODS: Prospective registry and study data were analysed using Cox proportional hazards regression to derive a prognostic model (hospital 1, n=695), which was subsequently tested (Harrell’s c-statistic for discrimination and Cox–Snell residuals for calibration) in two independent validation cohorts (hospital 2, n=479 and hospital 3, n=284). RESULTS: The derived Lung Cancer Prognostic Index (LCPI) included stage, histology, mutation status, performance status, weight loss, smoking history, respiratory comorbidity, sex, and age. Two-year overall survival rates according to LCPI in the derivation and two validation cohorts, respectively, were 84, 77, and 68% (LCPI 1: score⩽9); 61, 61, and 42% (LCPI 2: score 10–13); 33, 32, and 14% (LCPI 3: score 14–16); 7, 16, and 5% (LCPI 4: score ⩾15). Discrimination (c-statistic) was 0.74 for the derivation cohort, 0.72 and 0.71 for the two validation cohorts. CONCLUSIONS: The LCPI contributes additional prognostic information, which may be used to counsel patients, guide trial eligibility or design, or standardise mortality risk for epidemiological analyses. Nature Publishing Group 2017-08-22 2017-07-20 /pmc/articles/PMC5572183/ /pubmed/28728168 http://dx.doi.org/10.1038/bjc.2017.232 Text en Copyright © 2017 Cancer Research UK http://creativecommons.org/licenses/by-nc-sa/4.0/ From twelve months after its original publication, this work is licensed under the Creative Commons Attribution-NonCommercial-Share Alike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/ |
spellingShingle | Epidemiology Alexander, Marliese Wolfe, Rory Ball, David Conron, Matthew Stirling, Robert G Solomon, Benjamin MacManus, Michael Officer, Ann Karnam, Sameer Burbury, Kate Evans, Sue M Lung cancer prognostic index: a risk score to predict overall survival after the diagnosis of non-small-cell lung cancer |
title | Lung cancer prognostic index: a risk score to predict overall survival after the diagnosis of non-small-cell lung cancer |
title_full | Lung cancer prognostic index: a risk score to predict overall survival after the diagnosis of non-small-cell lung cancer |
title_fullStr | Lung cancer prognostic index: a risk score to predict overall survival after the diagnosis of non-small-cell lung cancer |
title_full_unstemmed | Lung cancer prognostic index: a risk score to predict overall survival after the diagnosis of non-small-cell lung cancer |
title_short | Lung cancer prognostic index: a risk score to predict overall survival after the diagnosis of non-small-cell lung cancer |
title_sort | lung cancer prognostic index: a risk score to predict overall survival after the diagnosis of non-small-cell lung cancer |
topic | Epidemiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5572183/ https://www.ncbi.nlm.nih.gov/pubmed/28728168 http://dx.doi.org/10.1038/bjc.2017.232 |
work_keys_str_mv | AT alexandermarliese lungcancerprognosticindexariskscoretopredictoverallsurvivalafterthediagnosisofnonsmallcelllungcancer AT wolferory lungcancerprognosticindexariskscoretopredictoverallsurvivalafterthediagnosisofnonsmallcelllungcancer AT balldavid lungcancerprognosticindexariskscoretopredictoverallsurvivalafterthediagnosisofnonsmallcelllungcancer AT conronmatthew lungcancerprognosticindexariskscoretopredictoverallsurvivalafterthediagnosisofnonsmallcelllungcancer AT stirlingrobertg lungcancerprognosticindexariskscoretopredictoverallsurvivalafterthediagnosisofnonsmallcelllungcancer AT solomonbenjamin lungcancerprognosticindexariskscoretopredictoverallsurvivalafterthediagnosisofnonsmallcelllungcancer AT macmanusmichael lungcancerprognosticindexariskscoretopredictoverallsurvivalafterthediagnosisofnonsmallcelllungcancer AT officerann lungcancerprognosticindexariskscoretopredictoverallsurvivalafterthediagnosisofnonsmallcelllungcancer AT karnamsameer lungcancerprognosticindexariskscoretopredictoverallsurvivalafterthediagnosisofnonsmallcelllungcancer AT burburykate lungcancerprognosticindexariskscoretopredictoverallsurvivalafterthediagnosisofnonsmallcelllungcancer AT evanssuem lungcancerprognosticindexariskscoretopredictoverallsurvivalafterthediagnosisofnonsmallcelllungcancer |