Validation Of A New Prognostic Body Composition Parameter In Cancer Patients.

JOURNAL OF CLINICAL ONCOLOGY(2019)

Cited 10|Views48
No score
Abstract
11597 Background: In cancer patients protein-calorie imbalances are responsible for decreased lean body mass and, in turn, for worse clinical outcome. We evaluated the prognostic value of a new body composition parameter (creatinine height index [CHI]) obtained from bioimpedance vectorial analysis-derived body cell mass and its association with nutritional and functional status. Methods: Data from Italian and German cancer patients based on information from previous prospective cohort studies were used. Multivariable models (adjusted for age, gender, hydration status, performance status, and disease stage) were built in both cohorts to assess the association between body composition outcome parameters (low fat-free mass [FFM], <15 [females] and <17 [males] kg/m2; low standardized phase angle [SPA], <-1.65; low CHI, <510 [females] and <660 [males] mg/24h/m) and 1-year all-cause mortality, low body mass index (BMI; <20 [<70 years] and <22 [>/=70 years] kg/m2), clinically significant weight loss (WL; >/=10% in 6 months) and low handgrip strength (HG; <20 [females] and <30 [males] kg). Results: Overall, 1084 cancer patients were included (Italians, N=454; Germans, N=630). Low CHI was independently associated with mortality in both Italian and German cohorts (Table). Low FFMI and low SPA did not predict survival in the German cohort. In patients with low CHI, worse nutritional and functional status were observed in both study populations. Performance of models addressing the study endpoints showed substantial consistency with both cohorts, particularly of those including low CHI. Conclusions: We validated a new prognostic body composition parameter, which is easier to interpret than standard nutritional parameters and may be useful for identifying cancer patients at nutritional risk, requiring early nutritional support. [Table: see text]
More
Translated text
Key words
cancer patients,body
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined