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1.
Clin Nutr ; 40(2): 615-623, 2021 02.
Article in English | MEDLINE | ID: mdl-32636113

ABSTRACT

BACKGROUND & AIMS: Estimation errors associated with bioelectric impedance evaluation may affect the accuracy of body composition and its prognostic value. We evaluated the prognostic value of a new body composition parameter (Nutrigram®) obtained from bioimpedance vectorial analysis-derived body cell mass and its association with nutritional and functional status. DESIGN: Data of Italian and German cancer patients observed prospectively until death were used. Multivariable models (adjusted for age, gender, hydration status, performance status, and disease's 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 Nutrigram®, <510 [females] and <660 [males] mg/24 h/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: Low Nutrigram® was independently associated with mortality in both Italian (HR = 1.84 [95%CI, 1.18-2.86]; P = 0.007) and German cohorts (HR = 1.52 [95%CI, 1.17-2.07]; P = 0.008). Low FFMI and low SPA did not predict survival in the German cohort. In patients with low Nutrigram®, 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 Nutrigram®. 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.


Subject(s)
Body Composition , Body Mass Index , Malnutrition/diagnosis , Neoplasms/mortality , Nutrition Assessment , Aged , Anthropometry , Cause of Death , Creatinine/urine , Electric Impedance , Female , Functional Status , Germany , Hand Strength , Humans , Italy , Male , Malnutrition/etiology , Middle Aged , Neoplasms/complications , Neoplasms/physiopathology , Nutritional Status , Predictive Value of Tests , Prognosis , Prospective Studies , Reproducibility of Results , Weight Loss
2.
Support Care Cancer ; 20(8): 1919-28, 2012 Aug.
Article in English | MEDLINE | ID: mdl-22314972

ABSTRACT

PURPOSE: There is little information about the nutritional status of cancer outpatients because the practice of nutritional screening is rarely performed. This study aims to define the pattern of scores of nutritional risk in 1,453 outpatients and factors associated with a high nutrition risk score, to facilitate the identification of such patients by the oncologists. METHODS: We prospectively screened the nutritional status of cancer outpatients according to the NRS-2002 score which combines indicators of malnutrition and of severity of the disease (1-3 points, respectively). A score ≥ 3 indicates "nutritional risk". The association of the nutritional scores with some patient/tumour/therapy-related variables was investigated through univariable and multivariable linear regression models. RESULTS: Thirty-two percent of outpatients were at nutritional risk. Primary tumour site, Eastern Cooperative Oncology Group score and presence of anorexia or fatigue were significantly associated with the nutrition risk score. Depending on the combination of these variables, it was possible to estimate different probabilities of nutritional risk. CONCLUSIONS: The frequency of a relevant nutritional risk was higher than expected considering the favourably selected population. The nutritional risk was associated with common clinical variables which are usually recorded in the charts and could easily alert the oncologist on the need of a further nutritional assessment or a nutritional support.


Subject(s)
Nutrition Disorders/etiology , Outpatients/statistics & numerical data , Aged , Female , Humans , Italy/epidemiology , Linear Models , Male , Middle Aged , Nutrition Assessment , Nutrition Disorders/epidemiology , Nutritional Status , Prospective Studies , Risk Assessment , Severity of Illness Index
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