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Predicting survival in malignant pleural mesothelioma using routine clinical and laboratory characteristics

INTRODUCTION: The prognosis of malignant pleural mesothelioma (MPM) is poor, with a median survival of 8–12 months. The ability to predict prognosis in MPM would help clinicians to make informed decisions regarding treatment and identify appropriate research opportunities for patients. The aims of t...

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Autores principales: Gunatilake, Samal, Lodge, David, Neville, Daniel, Jones, Thomas, Fogg, Carole, Bassett, Paul, Begum, Selina, Kerley, Sumita, Marshall, Laura, Glaysher, Sharon, Elliott, Scott, Stores, Rebecca, Bishop, Lesley, Chauhan, Anoop
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7797245/
https://www.ncbi.nlm.nih.gov/pubmed/33414260
http://dx.doi.org/10.1136/bmjresp-2019-000506
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author Gunatilake, Samal
Lodge, David
Neville, Daniel
Jones, Thomas
Fogg, Carole
Bassett, Paul
Begum, Selina
Kerley, Sumita
Marshall, Laura
Glaysher, Sharon
Elliott, Scott
Stores, Rebecca
Bishop, Lesley
Chauhan, Anoop
author_facet Gunatilake, Samal
Lodge, David
Neville, Daniel
Jones, Thomas
Fogg, Carole
Bassett, Paul
Begum, Selina
Kerley, Sumita
Marshall, Laura
Glaysher, Sharon
Elliott, Scott
Stores, Rebecca
Bishop, Lesley
Chauhan, Anoop
author_sort Gunatilake, Samal
collection PubMed
description INTRODUCTION: The prognosis of malignant pleural mesothelioma (MPM) is poor, with a median survival of 8–12 months. The ability to predict prognosis in MPM would help clinicians to make informed decisions regarding treatment and identify appropriate research opportunities for patients. The aims of this study were to examine associations between clinical and pathological information gathered during routine care, and prognosis of patients with MPM, and to develop a 6-month mortality risk prediction model. METHODS: A retrospective cohort study of patients diagnosed with MPM at Queen Alexandra Hospital, Portsmouth, UK between December 2009 and September 2013. Multivariate analysis was performed on routinely available histological, clinical and laboratory data to assess the association between different factors and 6-month survival, with significant associations used to create a model to predict the risk of death within 6 months of diagnosis with MPM. RESULTS: 100 patients were included in the analysis. Variables significantly associated with patient survival in multivariate analysis were age (HR 1.31, 95% CI 1.09 to 1.56), smoking status (current smoker HR 3.42, 95% CI 1.11 to 4.20), chest pain (HR 2.14, 95% CI 1.23 to 3.72), weight loss (HR 2.13, 95% CI 1.18 to 3.72), platelet count (HR 1.05, 95% CI 1.00 to 1.10), urea (HR 2.73, 95% CI 1.31 to 5.69) and adjusted calcium (HR 1.47, 95% CI 1.10 to 1.94). The resulting risk model had a c-statistic value of 0.76. A Hosmer-Lemeshow test confirmed good calibration of the model against the original dataset. CONCLUSION: Risk of death at 6 months in patients with a confirmed diagnosis of MPM can be predicted using variables readily available in clinical practice. The risk prediction model we have developed may be used to influence treatment decisions in patients with MPM. Further validation of the model requires evaluation of its performance on a separate dataset.
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spelling pubmed-77972452021-01-21 Predicting survival in malignant pleural mesothelioma using routine clinical and laboratory characteristics Gunatilake, Samal Lodge, David Neville, Daniel Jones, Thomas Fogg, Carole Bassett, Paul Begum, Selina Kerley, Sumita Marshall, Laura Glaysher, Sharon Elliott, Scott Stores, Rebecca Bishop, Lesley Chauhan, Anoop BMJ Open Respir Res Lung Cancer INTRODUCTION: The prognosis of malignant pleural mesothelioma (MPM) is poor, with a median survival of 8–12 months. The ability to predict prognosis in MPM would help clinicians to make informed decisions regarding treatment and identify appropriate research opportunities for patients. The aims of this study were to examine associations between clinical and pathological information gathered during routine care, and prognosis of patients with MPM, and to develop a 6-month mortality risk prediction model. METHODS: A retrospective cohort study of patients diagnosed with MPM at Queen Alexandra Hospital, Portsmouth, UK between December 2009 and September 2013. Multivariate analysis was performed on routinely available histological, clinical and laboratory data to assess the association between different factors and 6-month survival, with significant associations used to create a model to predict the risk of death within 6 months of diagnosis with MPM. RESULTS: 100 patients were included in the analysis. Variables significantly associated with patient survival in multivariate analysis were age (HR 1.31, 95% CI 1.09 to 1.56), smoking status (current smoker HR 3.42, 95% CI 1.11 to 4.20), chest pain (HR 2.14, 95% CI 1.23 to 3.72), weight loss (HR 2.13, 95% CI 1.18 to 3.72), platelet count (HR 1.05, 95% CI 1.00 to 1.10), urea (HR 2.73, 95% CI 1.31 to 5.69) and adjusted calcium (HR 1.47, 95% CI 1.10 to 1.94). The resulting risk model had a c-statistic value of 0.76. A Hosmer-Lemeshow test confirmed good calibration of the model against the original dataset. CONCLUSION: Risk of death at 6 months in patients with a confirmed diagnosis of MPM can be predicted using variables readily available in clinical practice. The risk prediction model we have developed may be used to influence treatment decisions in patients with MPM. Further validation of the model requires evaluation of its performance on a separate dataset. BMJ Publishing Group 2021-01-07 /pmc/articles/PMC7797245/ /pubmed/33414260 http://dx.doi.org/10.1136/bmjresp-2019-000506 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Lung Cancer
Gunatilake, Samal
Lodge, David
Neville, Daniel
Jones, Thomas
Fogg, Carole
Bassett, Paul
Begum, Selina
Kerley, Sumita
Marshall, Laura
Glaysher, Sharon
Elliott, Scott
Stores, Rebecca
Bishop, Lesley
Chauhan, Anoop
Predicting survival in malignant pleural mesothelioma using routine clinical and laboratory characteristics
title Predicting survival in malignant pleural mesothelioma using routine clinical and laboratory characteristics
title_full Predicting survival in malignant pleural mesothelioma using routine clinical and laboratory characteristics
title_fullStr Predicting survival in malignant pleural mesothelioma using routine clinical and laboratory characteristics
title_full_unstemmed Predicting survival in malignant pleural mesothelioma using routine clinical and laboratory characteristics
title_short Predicting survival in malignant pleural mesothelioma using routine clinical and laboratory characteristics
title_sort predicting survival in malignant pleural mesothelioma using routine clinical and laboratory characteristics
topic Lung Cancer
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7797245/
https://www.ncbi.nlm.nih.gov/pubmed/33414260
http://dx.doi.org/10.1136/bmjresp-2019-000506
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