We developed and validated a tool assessing the adherence to the Mediterranean diet based on current nutritional recommendations for health promotion (MEDI-Quest). Four-hundred-and-eleven clinically healthy subjects completed both the MEDI-Quest-score and the validated MedDietScore (MDS). A good accordance between MEDI-Quest and MDS was observed (R = 0.638), as well as for the percentage of individuals having similar scores with both methods for each food group. Regarding socio-cultural-factors, higher adherence was observed in people with older-age (OR = 1.030, p < .0001), more qualifier-employment (OR = 1.136, p < .005), higher-income (OR = 1.925, p < .0001), interest in reading-food-labels (OR = 2.057, p < .0001), and having frequent physical activity (OR = 1.608, p < .05). In conclusion, our findings show that (1) the MEDI-Quest score well correlate with MDS, and (2) the adherence to the Mediterranean diet is not particularly high due to less cultural roots. It could be necessary to improve people's knowledge about food and nutrition, taking into consideration believes embedded in their family, tradition and religion.

Background/Objectives: Cancer and related treatments can impair body composition (BC), increasing the risk of malnutrition and sarcopenia, poor prognosis, and Health-Related Quality of Life (HRQoL). To enhance BC parameter interpretation through Bioelectrical Impedance Analysis (BIA), we developed a predictive model based on unsupervised approaches including Principal Component Analysis (PCA) and k-means clustering for sarcopenia risk in cancer patients at the Istituto Nazionale Tumori IRCCS “Fondazione G. Pascale” (Naples). Methods: Sarcopenia and malnutrition risks were assessed using the NRS-2002 and SARC-F questionnaires, anthropometric measurements, and BIA. HRQoL was evaluated with the EORTC QLQ-C30 questionnaire. PCA and clustering analysis were performed to identify different BC profiles. Results: Data from 879 cancer patients (mean age: 63 ± 12.5 years) were collected: 117 patients (13%) and 128 (15%) were at risk of malnutrition and sarcopenia, respectively. PCA analysis identified three main components, and k-means determined three clusters, namely HMP (High Muscle Profile), MMP (Moderate Muscle Profile), and LMP (Low Muscle Profile). Patients in LMP were older, with a higher prevalence of comorbidities, malnutrition, and sarcopenia. In the multivariable analysis, age, lung cancer site, diabetes, and malnutrition risk were significantly associated with an increased risk of sarcopenia; among the clusters, patients in LMP had an increased risk of sarcopenia (+62%, p = 0.006). Conclusions: The NUTRISCREEN project, part of the ONCOCAMP study (ClinicalTrials.gov ID: NCT06270602), provides a personalized nutritional pathway for early screening of malnutrition and sarcopenia. Using an unsupervised approach, we provide distinct BC profiles and valuable insights into the factors associated with sarcopenia risk. This approach in clinical practice could help define risk categories, ensure the most appropriate nutritional strategies, and improve patient outcomes by providing data-driven care.

Background: Unplanned hospital readmissions (HRAs) are very common in cancer patients. These events can potentially impair the patients’ health-related quality of life and increase cancer care costs. In this study, data-driven prediction models were developed for identifying patients at a higher risk for HRA. Methods: A large dataset on cancer pain and additional data from clinical registries were used for conducting a Bayesian network analysis. A cohort of gastrointestinal cancer patients was selected. Logical and clinical relationships were a priori established to define and associate the considered variables including cancer type, body mass index (BMI), bone metastasis, serum albumin, nutritional support, breakthrough cancer pain (BTcP), and radiotherapy. Results: The best model (Bayesian Information Criterion) demonstrated that, in the investigated setting, unplanned HRAs are directly related to nutritional support (p = 0.05) and radiotherapy. On the contrary, BTcP did not significantly affect HRAs. Nevertheless, the correlation between variables showed that when BMI ≥ 25 kg/m², the spontaneous BTcP is more predictive for HRAs. Conclusions: Whilst not without limitations, a Bayesian model, combined with a careful selection of clinical variables, can represent a valid strategy for predicting unexpected HRA events in cancer patients. These findings could be useful for calibrating care interventions and implementing processes of resource allocation.

Background/Objectives: Cancer and their treatments could impact physical, nutritional, and psychological health, negatively influencing overall well-being. Accordingly, Health-Related Quality of Life (HRQoL) could be influenced by lifestyle habits, such as physical activity. This study aimed to assess physical activity levels in patients with a primary cancer diagnosis and their association with HRQoL at the first nutritional assessment. Methods: Data from the NUTRISCREEN project, part of the ONCOCAMP study (ClinicalTrials.gov ID: NCT06270602), were analyzed. Nutritional and sarcopenia risk, anthropometry and body composition parameters were collected. HRQoL and physical activity (as MET levels) were assessed through validated questionnaires. Descriptive statistics summarized categorical and continuous variables, and multivariable ordinal logistic regression models were performed. Results: Nutritional and sarcopenia risk decreased progressively with higher MET levels (p = 0.005 and p < 0.001, respectively). Adjusted multivariable models showed that HRQoL functional scores improved with increasing MET levels, with significant positive trends for physical (p < 0.001), role (p < 0.001), emotional (p = 0.003), and social functioning (p = 0.001), and global health status (p < 0.001). Conversely, symptom burden, including fatigue, nausea and vomiting, pain, dyspnea, insomnia, appetite loss, and constipation, decreased across MET quartiles (all p < 0.05). Conclusions: Overall, our findings suggest that physical activity may positively influence HRQoL among cancer patients. Early assessment helps to identify patients at risk of inactivity and support tailored rehabilitation programs to promote active lifestyles, preserve muscle mass, improve outcomes and overall health status.

Body composition (BC) analysis may integrate assessment of nutritional risk in patients with gastrointestinal cancers. Applying unsupervised machine learning techniques, we derived BC profiles (BCPs) and investigated their association with malnutrition risk and quality of life. This cross-sectional analysis includes gastrointestinal cancer patients enrolled in the NUTRItional and sarcopenia SCREENing project, part of the ONCOCAMP study (ClinicalTrials.gov ID: NCT06270602). Malnutrition assessment was performed using the NRS-2002, anthropometry and BC analysis; HRQoL was evaluated with the EORTC QLQ-C30 questionnaire. Principal component analysis and k-means clustering identified BCPs. Data from 189 patients (mean age: 66.3 ± 11.2 years) with gastric (37%), pancreatic (26.5%), rectal (24.3%) and hepatocellular carcinoma (12.2%) were analyzed. Overall, 36.5% of patients were at nutritional risk (NRS-2002 ≥ 3). Two BC clusters, High Muscle Profile (HMP) and Low Muscle Profile (LMP), were derived. Although no statistically significant association was observed in the overall cohort, multivariable analysis stratified by gender identified an association between LMP and nutritional risk among male patients (OR = 3.77, 95% CI: 1.08–14.3, p = 0.042); however, this finding should be considered exploratory. Nutritional risk, but not BC profiles, was associated with poorer Summary Score (β = 8.0, 95% CI: −14 to −2.3, p = 0.007) and higher Symptom Score (β = 9.8, 95% CI:4.5 to 15, p < 0.001). These preliminary results warrant further confirmation in larger, adequately powered longitudinal cohorts. Future studies should determine whether BCPs provide additional value beyond established nutritional screening and individual BC parameters in clinical practice.