A prospective study examining cachexia predictors in patients with incurable cancer
Abstract Background Early intervention against cachexia necessitates a predictive model. The aims of this study were to identify predictors of cachexia development and to create and evaluate accuracy of a predictive model based on these predictors. Methods A secondary analysis of a prospective, obse...
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doaj-690e8bfd6495402387672f7cef2abb192020-11-25T03:16:52ZengBMCBMC Palliative Care1472-684X2019-06-0118111010.1186/s12904-019-0429-2A prospective study examining cachexia predictors in patients with incurable cancerOla Magne Vagnildhaug0Cinzia Brunelli1Marianne J. Hjermstad2Florian Strasser3Vickie Baracos4Andrew Wilcock5Maria Nabal6Stein Kaasa7Barry Laird8Tora S. Solheim9Department of Clinical and Molecular Medicine, Faculty of Medicine and Health Sciences, NTNU - Norwegian University of Science and TechnologyPalliative Care, Pain Therapy and Rehabilitation Unit, Fondazione IRCCS Istituto Nazionale dei TumoriEuropean Palliative Care Research Centre (PRC), Department of Oncology, Oslo University Hospital, and Institute of Clinical Medicine, University of OsloDepartment of Internal Medicine and Palliative Care Centre, Cantonal Hospital, Oncological Palliative Medicine, Section OncologyDivision of Palliative Care Medicine, Department of Oncology, University of Alberta, Cross Cancer Institute 11560 University AvenueNottingham University Hospitals NHS TrustHospital Universitari Arnau de Vilanova and Universidad de LleidaEuropean Palliative Care Research Centre (PRC), Department of Oncology, Oslo University Hospital, and Institute of Clinical Medicine, University of OsloEdinburgh Cancer Research UK Centre, University of Edinburgh, Western General HospitalDepartment of Clinical and Molecular Medicine, Faculty of Medicine and Health Sciences, NTNU - Norwegian University of Science and TechnologyAbstract Background Early intervention against cachexia necessitates a predictive model. The aims of this study were to identify predictors of cachexia development and to create and evaluate accuracy of a predictive model based on these predictors. Methods A secondary analysis of a prospective, observational, multicentre study was conducted. Patients, who attended a palliative care programme, had incurable cancer and did not have cachexia at baseline, were amenable to the analysis. Cachexia was defined as weight loss (WL) > 5% (6 months) or WL > 2% and body mass index< 20 kg/m2. Clinical and demographic markers were evaluated as possible predictors with Cox analysis. A classification and regression tree analysis was used to create a model based on optimal combinations and cut-offs of significant predictors for cachexia development, and accuracy was evaluated with a calibration plot, Harrell’s c-statistic and receiver operating characteristic curve analysis. Results Six-hundred-twenty-eight patients were included in the analysis. Median age was 65 years (IQR 17), 359(57%) were female and median Karnofsky performance status was 70(IQR 10). Median follow-up was 109 days (IQR 108), and 159 (25%) patients developed cachexia. Initial WL, cancer type, appetite and chronic obstructive pulmonary disease were significant predictors (p ≤ 0.04). A five-level model was created with each level carrying an increasing risk of cachexia development. For Risk-level 1-patients (WL < 3%, breast or hematologic cancer and no or little appetite loss), median time to cachexia development was not reached, while Risk-level 5-patients (WL 3–5%) had a median time to cachexia development of 51 days. Accuracy of cachexia predictions at 3 months was 76%. Conclusion Important predictors of cachexia have been identified and used to construct a predictive model of cancer cachexia. Trial registration ClinicalTrials.gov Identifier: NCT01362816.http://link.springer.com/article/10.1186/s12904-019-0429-2CachexiaPre-cachexiaWeight lossCancerPalliative care |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ola Magne Vagnildhaug Cinzia Brunelli Marianne J. Hjermstad Florian Strasser Vickie Baracos Andrew Wilcock Maria Nabal Stein Kaasa Barry Laird Tora S. Solheim |
spellingShingle |
Ola Magne Vagnildhaug Cinzia Brunelli Marianne J. Hjermstad Florian Strasser Vickie Baracos Andrew Wilcock Maria Nabal Stein Kaasa Barry Laird Tora S. Solheim A prospective study examining cachexia predictors in patients with incurable cancer BMC Palliative Care Cachexia Pre-cachexia Weight loss Cancer Palliative care |
author_facet |
Ola Magne Vagnildhaug Cinzia Brunelli Marianne J. Hjermstad Florian Strasser Vickie Baracos Andrew Wilcock Maria Nabal Stein Kaasa Barry Laird Tora S. Solheim |
author_sort |
Ola Magne Vagnildhaug |
title |
A prospective study examining cachexia predictors in patients with incurable cancer |
title_short |
A prospective study examining cachexia predictors in patients with incurable cancer |
title_full |
A prospective study examining cachexia predictors in patients with incurable cancer |
title_fullStr |
A prospective study examining cachexia predictors in patients with incurable cancer |
title_full_unstemmed |
A prospective study examining cachexia predictors in patients with incurable cancer |
title_sort |
prospective study examining cachexia predictors in patients with incurable cancer |
publisher |
BMC |
series |
BMC Palliative Care |
issn |
1472-684X |
publishDate |
2019-06-01 |
description |
Abstract Background Early intervention against cachexia necessitates a predictive model. The aims of this study were to identify predictors of cachexia development and to create and evaluate accuracy of a predictive model based on these predictors. Methods A secondary analysis of a prospective, observational, multicentre study was conducted. Patients, who attended a palliative care programme, had incurable cancer and did not have cachexia at baseline, were amenable to the analysis. Cachexia was defined as weight loss (WL) > 5% (6 months) or WL > 2% and body mass index< 20 kg/m2. Clinical and demographic markers were evaluated as possible predictors with Cox analysis. A classification and regression tree analysis was used to create a model based on optimal combinations and cut-offs of significant predictors for cachexia development, and accuracy was evaluated with a calibration plot, Harrell’s c-statistic and receiver operating characteristic curve analysis. Results Six-hundred-twenty-eight patients were included in the analysis. Median age was 65 years (IQR 17), 359(57%) were female and median Karnofsky performance status was 70(IQR 10). Median follow-up was 109 days (IQR 108), and 159 (25%) patients developed cachexia. Initial WL, cancer type, appetite and chronic obstructive pulmonary disease were significant predictors (p ≤ 0.04). A five-level model was created with each level carrying an increasing risk of cachexia development. For Risk-level 1-patients (WL < 3%, breast or hematologic cancer and no or little appetite loss), median time to cachexia development was not reached, while Risk-level 5-patients (WL 3–5%) had a median time to cachexia development of 51 days. Accuracy of cachexia predictions at 3 months was 76%. Conclusion Important predictors of cachexia have been identified and used to construct a predictive model of cancer cachexia. Trial registration ClinicalTrials.gov Identifier: NCT01362816. |
topic |
Cachexia Pre-cachexia Weight loss Cancer Palliative care |
url |
http://link.springer.com/article/10.1186/s12904-019-0429-2 |
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