ArticleClinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico2026
Baseline fdg pet/ct-derived tumor burden and host metabolic activity predict complete metabolic response to neoadjuvant chemotherapy in ınvasive ductal breast cancer.
Article in Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeTo evaluate the prognostic significance of FDG PET/CT-derived tumor burden, host metabolic activity, inflammatory biomarkers, and body composition parameters for predicting complete metabolic response (CMR) following neoadjuvant chemotherapy (NAC) in patients with invasive ductal breast cancer. MATERIALS AND
methodsNinety women with histologically confirmed invasive ductal breast cancer who underwent baseline and post-treatment FDG PET/CT examinations following NAC were retrospectively included. Metabolic tumor volume (MTV), total lesion glycolysis (TLG), brain-to-liver ratio (Brain/LR), bone marrow-to-liver ratio (BM/LR), neutrophil-to-lymphocyte ratio (NLR), and psoas muscle-to-subcutaneous fat thickness ratio (PS/SCFT) were analyzed. Correlation analyses, multivariable regression analyses, and ROC analyses were performed.
resultsCMR was achieved in 77 patients (85.6%), whereas 13 patients (14.4%) demonstrated residual metabolic disease. Baseline MTV and TLG were significantly higher in non-CMR patients (p=0.024 and p = 0.004, respectively). Brain/LR was significantly lower in non-responders (p = 0.007). Ki-67 demonstrated a significant inverse correlation with MTV (ρ = - 0.309, p = 0.003). In multivariable regression analysis, baseline BM/LR (β = 0.363, p = 0.017) and baseline PS/SCFT (β = - 0.268, p = 0.017) independently predicted post-treatment SUVmax. ROC analysis demonstrated AUC values of 0.705 for MTV, 0.757 for TLG, 0.734 for Brain/LR, and 0.864 for the combined predictive model.
conclusionBaseline volumetric tumor burden is strongly associated with metabolic response following NAC. Integration of tumor burden parameters with host metabolic and body composition biomarkers may improve individualized treatment-response prediction in breast cancer.
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