BACKGROUND: How to assess cachexia is a barrier both in research and in clinical practice. This study examines the need for assessing both reduced food intake and loss of appetite, to see if these variables can be used interchangeably. A secondary aim is to assess the variance explained by food intake, appetite and weight loss by using tumor-related factors, symptoms and biological markers as explanatory variables. MATERIAL AND METHODS: One thousand and seventy patients with incurable cancer were registered in an observational, cross sectional multicenter study. A total of 885 patients that had complete data on food intake (PG-SGA), appetite (EORTC QLQ-C30) and weight loss were included in the present analysis. The association between reduced food intake and appetite loss was assessed using Spearman's correlation. To find the explained variance of the three symptoms a multivariate analysis was performed. RESULTS: The mean age was 62 years with a mean survival of 247 days and a mean Karnofsky performance status of 72. Thirteen percent of the patients who reported eating less than normal had good appetite and 25% who had unchanged or increased food intake had reduced appetite. Correlation between appetite loss and food intake was 0.50. Explained variance for the regression models was 44% for appetite loss, 27% for food intake and only 13% for weight loss. CONCLUSION: Both appetite loss and food intake should be assessed in cachectic patients since conscious control of eating may sometimes overcome appetite loss. The low explained variance for weight loss is probably caused by the need for more knowledge about metabolism and inflammation, and is consistent with the cancer cachexia definition that claims that in cachexia weight loss is not caused by reduced food intake alone. The questions concerning appetite loss from EORTC-QLQ C30 and food intake from PG-SGA seem practical and informative when dealing with advanced cancer patients.
BACKGROUND: How to assess cachexia is a barrier both in research and in clinical practice. This study examines the need for assessing both reduced food intake and loss of appetite, to see if these variables can be used interchangeably. A secondary aim is to assess the variance explained by food intake, appetite and weight loss by using tumor-related factors, symptoms and biological markers as explanatory variables. MATERIAL AND METHODS: One thousand and seventy patients with incurable cancer were registered in an observational, cross sectional multicenter study. A total of 885 patients that had complete data on food intake (PG-SGA), appetite (EORTC QLQ-C30) and weight loss were included in the present analysis. The association between reduced food intake and appetite loss was assessed using Spearman's correlation. To find the explained variance of the three symptoms a multivariate analysis was performed. RESULTS: The mean age was 62 years with a mean survival of 247 days and a mean Karnofsky performance status of 72. Thirteen percent of the patients who reported eating less than normal had good appetite and 25% who had unchanged or increased food intake had reduced appetite. Correlation between appetite loss and food intake was 0.50. Explained variance for the regression models was 44% for appetite loss, 27% for food intake and only 13% for weight loss. CONCLUSION: Both appetite loss and food intake should be assessed in cachectic patients since conscious control of eating may sometimes overcome appetite loss. The low explained variance for weight loss is probably caused by the need for more knowledge about metabolism and inflammation, and is consistent with the cancer cachexia definition that claims that in cachexia weight loss is not caused by reduced food intake alone. The questions concerning appetite loss from EORTC-QLQ C30 and food intake from PG-SGA seem practical and informative when dealing with advanced cancerpatients.
Authors: Brittany R Counts; Justin P Hardee; Dennis K Fix; Brandon N VanderVeen; Ryan N Montalvo; James A Carson Journal: Med Sci Sports Exerc Date: 2019-10-23 Impact factor: 5.411
Authors: Matteo Cesari; Bruno Vellas; Fang-Chi Hsu; Anne B Newman; Hani Doss; Abby C King; Todd M Manini; Timothy Church; Thomas M Gill; Michael E Miller; Marco Pahor Journal: J Gerontol A Biol Sci Med Sci Date: 2014-11-11 Impact factor: 6.053
Authors: Alejandro Schcolnik-Cabrera; Alma Chávez-Blanco; Guadalupe Domínguez-Gómez; Alfonso Dueñas-González Journal: Am J Cancer Res Date: 2017-05-01 Impact factor: 6.166
Authors: Brittany R Counts; Justin P Hardee; Dennis K Fix; Brandon N Vanderveen; Ryan N Montalvo; James A Carson Journal: Med Sci Sports Exerc Date: 2020-03
Authors: Seul Ki Kim; Yu Hyun Kwon; Jung Hwan Cho; Da Young Lee; Se Eun Park; Hyung Geun Oh; Cheol Young Park; Won Young Lee; Ki Won Oh; Sung Woo Park; Eun Jung Rhee Journal: Endocrinol Metab (Seoul) Date: 2017-11-21