Bioimpedance-derived body composition parameters predict mortality and dose-limiting toxicity: the multicenter ONCO-BIVA study.

BACKGROUND: In patients with cancer, lean body mass loss is frequent and associated with worse outcomes, including reduced treatment tolerance and survival. Bioelectrical impedance analysis (BIA) is a popular method for body composition assessment. We evaluated the value of BIA-derived body composition parameters in predicting mortality and, for the first time, dose-limiting toxicity (DLT). PATIENTS AND METHODS: We conducted a prospective multicenter (n = 12) observational study in adult patients with solid neoplastic disease and receiving primary systemic treatment. We collected information on BIA-derived parameters: phase angle (PhA) <5th percentile of age and gender-specific normative values; standardized PhA (SPA) <-1.65; Nutrigram® <660 mg/24 h/m and <510 mg/24 h/m for males and females, respectively. The primary outcome and the key secondary were 1-year mortality and DLT (any-type severe toxicity requiring a delay in systemic treatment administration or a reduction of its dosage), respectively. RESULTS: In total, 640 patients were included. At 12 months, death occurred in 286 patients (47.6%). All BIA-derived body composition parameters were independently associated with death: SPA, hazard ratio (HR) = 1.59 [95% confidence interval (CI) 1.30-1.95] (P < 0.001); PhA, HR = 1.38 (95% CI 1.13-1.69) (P = 0.002); Nutrigram®, HR = 1.71 (95% CI 1.42-2.04) (P < 0.001). DLT occurred in 208 patients (32.5%) and body composition parameters were associated with this outcome, particularly SPA: odds ratio = 6.37 (95% CI 2.33-17.44) (P < 0.001). CONCLUSIONS: The study confirmed that BIA-derived body composition parameters are independently associated not only with survival but also with DLT. Although our findings were limited to patients receiving first-line systemic treatment, the evidence reported may have important practice implications for the improvement of the clinical work-up of cancer patients.

Risk of misclassification during diagnosis of malnutrition in retroperitoneal sarcoma patients.

BACKGROUND: Retroperitoneal sarcoma (RPS) is a rare tumour that can reach exceptionally large size at diagnosis and affects body weight with its volume. We investigated the risk of nutritional status misclassification based on the Global Leadership Initiative on Malnutrition (GLIM) criteria in RPS patients. METHODS: We retrospectively analyzed the baseline data of patients with primary RPS including anthropometry, Malnutrition Universal Screening Tool (MUST) score and skeletal muscle index (SMI) calculated on preoperative CT scan. Phenotypic GLIM criteria considered were non-volitional weight loss, low-BMI and low muscle mass. MUST score, being inclusive of weight loss, was chosen as its surrogate. Reduced muscle mass was defined with SMI cut-offs <38.5-52.4 cm2/m2 for female and male respectively. RESULTS: From 2018 to 2020, 100 consecutive patients (male/female: 48/52) were included. Median age was 61 (48-68) years, median BMI 24.6 (21.5-27.4) kg/m2. Seven patients (7%) reported MUST score ≥2 and 80 (80%) score 0. Five patients (5%) were underweight, 44 (44%) overweight and obese. Sixty patients (60%) presented low SMI, of those 56 (93%) were normal or overweight, and 46 (77%) not at nutritional risk according to the MUST score. Both underweight BMI and MUST score ≥2 were not correlated with low SMI (p = 0.406, p = 0.612, respectively). No relevant discrepancy was found in the postoperative course of patients with low or normal muscle mass, although SMI was able to better characterize nutritional risk in the proportion of patents with high-grade liposarcoma and predicted worst overall survival. CONCLUSION: GLIM criteria are a useful tool for diagnosis of malnutrition. However, our analysis suggests that phenotypic criteria are not interchangeable with each other. An altered body composition is often hidden in patients with retroperitoneal sarcoma and the use of weight-based classification does not seem to be appropriate, enhancing the role of mass muscle measurement to prevent misdetections of malnourished patient.

Nutritional status and body composition assessment in patients with a new diagnosis of advanced solid tumour: Exploratory comparison of computed tomography and bioelectrical impedance analysis.

OBJECTIVE: Low skeletal muscle is a common characteristic of cancer-related malnutrition and a predictor of poorer prognosis in oncological patients. In this study we evaluated nutritional status and altered body composition using computed tomography (CT) and bioelectrical impedance analysis (BIA) in newly diagnosed patients. Our purpose was to compare the results of two available techniques to assess body composition suggested by the guidelines and some diagnostic criteria to identify malnutrition. METHODS: In a prospective study, patients with a new diagnosis of advanced solid tumour were enrolled and evaluated before starting first-line chemotherapy. Anthropometric, body composition and systemic inflammation measurements were collected and cut-off points from literature data were used for results classification. Malnutrition was expressed as weight loss (WL) in the previous 6 months >10% and underweight body mass index (BMI). Altered body composition was assessed as low index both skeletal muscle (SMI) derived by CT and fat-free mass by BIA (FFMI). Descriptive statistic was presented. Several statistical correlation analyses were performed. RESULTS: 67 patients were assessed: 40M/27F; average age 59 ± 13 years and BMI 23 ± 4; 43 (64%) upper gastrointestinal, 12 lung, 9 colorectal, 3 other cancers. Fourty-five (67%) were malnourished with WL criteria but only 8 (12%) resulted underweight. From analysis of CT images and BIA, 49 (73%) and 10 (15%) patients respectively reported lower cut-off point. Overall, 35 (52%) had both sarcopenia and WL > 10%. CONCLUSIONS: Our results suggest that prevalence data of malnutrition expressed as WL are more in agreement with those of sarcopenia recognised using CT than BIA method. Further studies are required to confirm these findings and to identify the best and easiest methods for monitoring BC during nutritional intervention and oncological therapies.