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 th...

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Main Authors: Lesley Bishop, Samal Gunatilake, Laura Marshall, Carole Fogg, David Lodge, Daniel Neville, Thomas Jones, Selina Begum, Sumita Kerley, Sharon Glaysher, Scott Elliott, Rebecca Stores
Format: Article
Language:English
Published: BMJ Publishing Group 2021-08-01
Series:BMJ Open Respiratory Research
Online Access:https://bmjopenrespres.bmj.com/content/8/1/e000506.full
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spelling doaj-37abe6888aa84d1c86535cebd8398e5b2021-08-10T11:30:06ZengBMJ Publishing GroupBMJ Open Respiratory Research2052-44392021-08-018110.1136/bmjresp-2019-000506Predicting survival in malignant pleural mesothelioma using routine clinical and laboratory characteristicsLesley Bishop0Samal Gunatilake1Laura Marshall2Carole Fogg3David Lodge4Daniel Neville5Thomas Jones6Selina Begum7Sumita Kerley8Sharon Glaysher9Scott Elliott10Rebecca Stores11Department of Respiratory Medicine, Queen Alexandra Hospital, Portsmouth, Portsmouth, UKDepartment of Respiratory Medicine, Hampshire Hospitals NHS Foundation Trust, Winchester, Hampshire, UKDepartment of Respiratory Research & Innovation, Portsmouth Hospitals NHS Trust, Portsmouth, Portsmouth, UKDepartment of Respiratory Research & Innovation, Portsmouth Hospitals NHS Trust, Portsmouth, Portsmouth, UKDepartment of Respiratory Research & Innovation, Portsmouth Hospitals NHS Trust, Portsmouth, Portsmouth, UKDepartment of Respiratory Research & Innovation, Portsmouth Hospitals NHS Trust, Portsmouth, Portsmouth, UKDepartment of Respiratory Research & Innovation, Portsmouth Hospitals NHS Trust, Portsmouth, Portsmouth, UKDepartment of Respiratory Research & Innovation, Portsmouth Hospitals NHS Trust, Portsmouth, Portsmouth, UKDepartment of Respiratory Research & Innovation, Portsmouth Hospitals NHS Trust, Portsmouth, Portsmouth, UKDepartment of Respiratory Research & Innovation, Portsmouth Hospitals NHS Trust, Portsmouth, Portsmouth, UKDepartment of Respiratory Research & Innovation, Portsmouth Hospitals NHS Trust, Portsmouth, Portsmouth, UKInstitute of Biological and Biomedical Sciences, University of Portsmouth, Portsmouth, Hampshire, UKIntroduction 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.https://bmjopenrespres.bmj.com/content/8/1/e000506.full
collection DOAJ
language English
format Article
sources DOAJ
author Lesley Bishop
Samal Gunatilake
Laura Marshall
Carole Fogg
David Lodge
Daniel Neville
Thomas Jones
Selina Begum
Sumita Kerley
Sharon Glaysher
Scott Elliott
Rebecca Stores
spellingShingle Lesley Bishop
Samal Gunatilake
Laura Marshall
Carole Fogg
David Lodge
Daniel Neville
Thomas Jones
Selina Begum
Sumita Kerley
Sharon Glaysher
Scott Elliott
Rebecca Stores
Predicting survival in malignant pleural mesothelioma using routine clinical and laboratory characteristics
BMJ Open Respiratory Research
author_facet Lesley Bishop
Samal Gunatilake
Laura Marshall
Carole Fogg
David Lodge
Daniel Neville
Thomas Jones
Selina Begum
Sumita Kerley
Sharon Glaysher
Scott Elliott
Rebecca Stores
author_sort Lesley Bishop
title 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_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_sort predicting survival in malignant pleural mesothelioma using routine clinical and laboratory characteristics
publisher BMJ Publishing Group
series BMJ Open Respiratory Research
issn 2052-4439
publishDate 2021-08-01
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.
url https://bmjopenrespres.bmj.com/content/8/1/e000506.full
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