Construction of a comprehensive predictive model for axillary lymph node metastasis in breast cancer: a retrospective study

• Published in: BMC cancer Vol. 23; no. 1; pp. 1 - 1028
• Main Authors: Li, Yan, Han, Dong, Shen, Cong, Duan, Xiaoyi
• Format: Journal Article
• Language: English
• Published: London BioMed Central Ltd 24-10-2023; BioMed Central; BMC
• Subjects: Analysis; Biomarkers; Breast cancer; Cable television broadcasting industry; Cancer; Care and treatment; Development and progression; Diagnosis; Lymph node Metastasis; Lymph nodes; Lymphatic metastasis; Lymphatic system; Mammography; Metabolism; Metastases; Metastasis; Oncology, Experimental; PET imaging; PET/CT; Prediction models; Radiomics; Software; Statistical analysis; Ultrasonic imaging; Ultrasound; China; Canada; United States; United States > US
• ISSN: 1471-2407; 1471-2407
• DOI: 10.1186/s12885-023-11498-7

Purpose The accurate assessment of axillary lymph node metastasis (LNM) in early-stage breast cancer (BC) is of great importance. This study aimed to construct an integrated model based on clinicopathology, ultrasound, PET/CT, and PET radiomics for predicting axillary LNM in early stage of BC. Materials and methods 124 BC patients who underwent 18 F-fluorodeoxyglucose (18 F-FDG) PET/CT and whose diagnosis were confirmed by surgical pathology were retrospectively analyzed and included in this study. Ultrasound, PET and clinicopathological features of all patients were analyzed, and PET radiomics features were extracted to establish an ultrasound model (clinicopathology and ultrasound; model 1), a PET model (clinicopathology, ultrasound, and PET; model 2), and a comprehensive model (clinicopathology, ultrasound, PET, and radiomics; model 3), and the diagnostic efficacy of each model was evaluated and compared. Results The T stage, US_BIRADS, US_LNM, and PET_LNM in the positive axillary LNM group was significantly higher than that of in the negative LNM group (P = 0.013, P = 0.049, P < 0.001, P < 0.001, respectively). Radiomics score for predicting LNM (RS_LNM) for the negative LNM and positive LNM were statistically significant difference (-1.090 [+ or -] 0.448 vs. -0.693 [+ or -] 0.344, t = -4.720, P < 0.001), and the AUC was 0.767 (95% CI: 0.674-0.861). The ROC curves showed that model 3 outperformed model 1 for the sensitivity (model 3 vs. model 1, 82.86% vs. 48.57%), and outperformed model 2 for the specificity (model 3 vs. model 2, 82.02% vs. 68.54%) in the prediction of LNM. The AUC of mode 1, model 2 and model 3 was 0.687, 0.826 and 0.874, and the Delong test showed the AUC of model 3 was significantly higher than that of model 1 and model 2 (P < 0.05). Decision curve analysis showed that model 3 resulted in a higher degree of net benefit for all the patients than model 1 and model 2. Conclusion The use of a comprehensive model based on clinicopathology, ultrasound, PET/CT, and PET radiomics can effectively improve the diagnostic efficacy of axillary LNM in BC. Trial registration: This study was registered at ClinicalTrials Gov (number NCT05826197) on 7th, May 2023. Keywords: Breast cancer, Lymph node Metastasis, Radiomics, PET/CT, Ultrasound