A prospective study examining cachexia predictors in patients with incurable cancer

Ola Magne Vagnildhaug, Cinzia Brunelli, Marianne J. Hjermstad, Florian Strasser, Vickie Baracos, Andrew Wilcock, Maria Nabal, Stein Kaasa, Barry Laird, Tora S. Solheim

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Article number46
JournalBMC Palliative Care
Issue number1
Publication statusPublished - Jun 4 2019


  • Cachexia
  • Cancer
  • Palliative care
  • Pre-cachexia
  • Weight loss

ASJC Scopus subject areas

  • Medicine(all)


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