dc.contributor.author |
Vagnildhaug, Ola Magne |
dc.contributor.author |
Brunelli, Cinzia |
dc.contributor.author |
Hjermstad, Marianne J. |
dc.contributor.author |
Strasser, Florian |
dc.contributor.author |
Baracos, Vickie |
dc.contributor.author |
Wilcock, Andrew |
dc.contributor.author |
Nabal Vicuña, Maria |
dc.contributor.author |
Kaasa, Stein |
dc.contributor.author |
Laird, Barry |
dc.contributor.author |
Solheim, Tora S. |
dc.date |
2020-02-25T10:37:52Z |
dc.date |
2020-02-25T10:37:52Z |
dc.date |
2019 |
dc.identifier |
1472-684X |
dc.identifier |
http://hdl.handle.net/10459.1/68090 |
dc.identifier |
https://doi.org/10.1186/s12904-019-0429-2 |
dc.identifier.uri |
http://hdl.handle.net/10459.1/68090 |
dc.description |
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. |
dc.language |
eng |
dc.publisher |
BioMed Central |
dc.relation |
Reproducció del document publicat a https://doi.org/10.1186/s12904-019-0429-2 |
dc.relation |
BMC Palliative Care, 2019, vol. 18, núm. 46 |
dc.rights |
cc-by (c) Vagnildhaug et al., 2019 |
dc.rights |
http://creativecommons.org/licenses/by/4.0/ |
dc.rights |
info:eu-repo/semantics/openAccess |
dc.subject |
Cachexia |
dc.subject |
Pre-cachexia |
dc.subject |
Weight loss |
dc.subject |
Cancer |
dc.subject |
Palliative care |
dc.title |
A prospective study examining cachexia predictors in patients with incurable cancer |
dc.type |
info:eu-repo/semantics/article |
dc.type |
info:eu-repo/semantics/publishedVersion |