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        <datestamp>2026-09-17T15:58:28Z</datestamp>
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          <dc:title>Supplementary file 2_Nutritional ultrasound cut off for predicting complications and mortality in lung cancer patients: a multicenter longitudinal study from the VALONC project.docx</dc:title>
          <dc:creator>Jose M. Romero-Márquez (24596253)</dc:creator>
          <dc:creator>María González-Pacheco (25033132)</dc:creator>
          <dc:creator>Rocío Fernández-Jiménez (17437566)</dc:creator>
          <dc:creator>Alba Carmona-Llanos (25033135)</dc:creator>
          <dc:creator>María Teresa Zarco-Martín (18006841)</dc:creator>
          <dc:creator>Pablo Rodríguez de Vera-Gómez (25033138)</dc:creator>
          <dc:creator>Fernanda Mucarzel-Suarez-Arana (25033141)</dc:creator>
          <dc:creator>Silvia García-Rey (22654979)</dc:creator>
          <dc:creator>Ana Sanz-Sanz (25033144)</dc:creator>
          <dc:creator>María Isabel Rebollo Pérez (25033147)</dc:creator>
          <dc:creator>María Luisa Fernandez-Soto (25033150)</dc:creator>
          <dc:creator>Vicente Mustieles (8955020)</dc:creator>
          <dc:creator>Araceli Muñoz-Garach (5164697)</dc:creator>
          <dc:creator>José Manuel García-Almeida (20380101)</dc:creator>
          <dc:subject>Clinical and Sports Nutrition</dc:subject>
          <dc:subject>dynapenia</dc:subject>
          <dc:subject>GLIM criteria</dc:subject>
          <dc:subject>malnutrition</dc:subject>
          <dc:subject>morphofunctional assessment</dc:subject>
          <dc:subject>nutritional ultrasound</dc:subject>
          <dc:subject>rectus femoris</dc:subject>
          <dc:subject>sarcopenia</dc:subject>
          <dc:description>Introduction&lt;p&gt;Lung cancer remains a leading cause of cancer-related mortality, often exacerbated by malnutrition and muscle depletion that traditional weight-centric metrics may fail to identify. This study assessed the clinical and prognostic relevance of rectus femoris (RF) ultrasound as a practical bedside tool for evaluating muscle-related parameters and clinical outcomes.&lt;/p&gt;Methods&lt;p&gt;This multicenter longitudinal study involved 374 patients (114 females, 260 males) across 10 Spanish hospitals. Researchers performed ultrasonographic assessments of the RF, measuring cross-sectional area (RF-CSA), thickness (Y-axis), and circumference, alongside GLIM malnutrition criteria and PG-SGA. Statistical analyses included Random Forest algorithms, ROC curves, and Cox regression models adjusted for age, BMI, ECOG performance status, cancer type, and cancer stage to determine sex-specific associations with clinical outcomes.&lt;/p&gt;Results&lt;p&gt;Significant sexual dimorphism was observed; men exhibited larger muscle parameters, while women had higher subcutaneous fat. RF-CSA and RF-Y-axis showed the highest discriminative performance for GLIM-defined malnutrition, with AUCs of 0.706 and 0.713 in men and 0.814 and 0.804 in women, respectively. The corresponding RF-CSA cut-offs were 3.88 cm&lt;sup&gt;2&lt;/sup&gt; in men and 2.78 cm&lt;sup&gt;2&lt;/sup&gt; in women, whereas RF-Y-axis cut-offs were 1.09 cm in men and 0.95 cm in women. In men, RF-Y-axis was significantly associated with all-cause mortality (HR = 0.32, 95% CI: 0.15–0.71), whereas RF-CSA, RF-CIR, and RF-X-axis were associated with clinical complications. No significant associations with mortality or complications were observed in women. A moderate agreement was observed between GLIM and PG-SGA (weighted κ = 0.51), suggesting that these criteria capture overlapping but not identical dimensions of malnutrition.&lt;/p&gt;Discussion&lt;p&gt;Rectus femoris ultrasound may provide objective, sex-specific clinical information that complements the GLIM framework and traditional anthropometric assessments. By identifying clinically relevant muscle waste, this bedside tool allows for the early detection of high-risk patients, potentially directing timely nutritional and rehabilitative interventions to improve survival and treatment tolerance in lung cancer.&lt;/p&gt;</dc:description>
          <dc:date>2026-09-17T15:58:28Z</dc:date>
          <dc:type>Dataset</dc:type>
          <dc:type>Dataset</dc:type>
          <dc:identifier>10.3389/fnut.2026.1876352.s001</dc:identifier>
          <dc:relation>https://figshare.com/articles/dataset/Supplementary_file_2_Nutritional_ultrasound_cut_off_for_predicting_complications_and_mortality_in_lung_cancer_patients_a_multicenter_longitudinal_study_from_the_VALONC_project_docx/33900202</dc:relation>
          <dc:rights>CC BY 4.0</dc:rights>
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