AUTHOR=Tong Yuexin , Xu Shaoqing , Jiang Liming , Zhao Chengliang , Zhao Dongxu 

TITLE=A visualized model for identifying optimal candidates for aggressive locoregional surgical treatment in patients with bone metastases from breast cancer

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2023.1266679

DOI=10.3389/fendo.2023.1266679

ISSN=1664-2392

ABSTRACT=Propensity score matching (PSM) analysis was performed to reduce selection bias. Kaplan-Meier (K-M) survival analysis and Cox regression analysisanalyses were conducted before and after PSM to study the survival difference between the two groups. We also investigated theThe survival outcome and treatment modality were also investigated in patients with different metastatic patterns. The logistic regression analyses were utilized to determine significant surgery-benefitrelated predictors and, develop a screening nomogram and itits online version to, and quantify the beneficial probability of local surgery for BC patients with BM. Receiver operating characteristic (ROC) curves, the area under the curves (AUC)), and calibration curves were plotted to evaluate the predictive performance and calibration of this model, andwhereas decision curve analysis (DCA) was used to assessedassess its clinical usefulness.Results: This study included 56255,625 eligible patients, of whom 2133 patients2,133 (37.92%) received surgical resection of primary lesion. Kaplan-Meierlesions. K-M survival analysis and Cox regression analysis showeddemonstrated that local surgery was independently associated with better survival. InSurgery provided significant survival benefits in most subgroups and metastatic patterns, surgery provided significant survival benefit.. After PSM, patients who received surgery had a longer survival time (OS: 46 months vs. 32 months, p< < 0.001; CSS: 50 months vs. 34 months, p< < 0.001). Logistic regression analysis determined six significant surgery-benefit-related variables, including: T stage, radiotherapy, race, liver metastasis, brain metastasis, and breast subtype. These factors were combined to establish the nomogram and a web probability calculator (https://sunshine1.shinyapps.io/DynNomapp/ ), with an AUC of 0.673 in the training cohort and an AUC of 0.640 in the validation cohort. and theThe calibration curves showedexhibited excellent agreement. DCA indicated that the nomogram was clinically useful. Based on this model, surgery patients were assigned into two subsets: estimated sur-nonbenefitnon-benefit and estimated sur-benefit. Patients in the estimated sur-benefit subset were associated with longer survival (median OS: 64 months vs. 33 months, P< < 0.001). Besides, there was no difference in survival between the estimated sur-nonbenefitnon-benefit subset and the non-surgery group.Our study further confirmed the significance of local surgery in BC patients with BM and proposed a novel tool to identify optimal surgical candidates.