Abstract
OBJECTIVE: To construct prediction models including baseline 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) metabolic parameters of tumoural lesions and non-tumour lymphoid tissue for recurrence-free survival within 5 years (5y-RFS) after imaging examination in patients with invasive ductal carcinomas (IDCs) of the breast. METHODS: The study included 101 consecutive female patients. Univariable and multivariable Cox regression were used to identify clinicopathological and metabolic parameters associated with risk of recurrence. Four prediction models based on the results of multivariable analysis were constructed and visualized as nomograms. Performance of each nomogram was evaluated using the concordance index (C-index), integrated discrimination improvement, decision curve analysis (DCA), and calibration curve. RESULTS: N3 status, total metabolic tumour volume, the maximum standardized uptake value of spleen, and spleen-to-liver ratio were significant predictors of 5y-RFS. The nomogram including all significant predictors demonstrated superior predictive performance for 5y-RFS, with a C-index of 0.907 (95% CI, 0.833-0.981), greatest net benefit on DCA, good accuracy on calibration curves, and excellent risk stratification on Kaplan-Meier curves. CONCLUSIONS: The model that included metabolic parameters of the spleen had the best performance for predicting 5y-RFS in patients with IDCs of the breast. This model may guide personalized treatment decisions and inform patients and clinicians about prognosis. ADVANCES IN KNOWLEDGE: This research identifies 18F-FDG PET/CT metabolic parameters of non-tumour lymphoid tissue as predictors of recurrence in breast cancer.