■已初步研究了原发性(PTR)手术切除对乳腺癌(BC)骨转移(BM)患者生存率的影响,但尚不清楚哪些患者适合此手术。最后,这项研究的目的是建立一个预测模型,以筛选可从局部手术中获益的BMBC患者.
■使用监测确定了患有BM的BC患者,流行病学,和最终结果(SEER)数据库(2010年和2015年),39例患者从一家亚洲医疗中心接受外部验证.根据局部手术的情况,患者分为手术组和非手术组。进行倾向评分匹配(PSM)分析以减少选择偏倚。在PSM前后进行Kaplan-Meier(K-M)生存和Cox回归分析,以研究两组之间的生存差异。还研究了具有不同转移模式的患者的生存结果和治疗方式。逻辑回归分析用于确定重要的手术获益相关预测因子,开发一个筛选列线图及其在线版本,并量化BC伴BM患者局部手术的有利概率。接收器工作特性(ROC)曲线,曲线下面积(AUC),并绘制校准曲线以评估该模型的预测性能和校准,而决策曲线分析(DCA)用于评估其临床有效性.
■这项研究包括5,625名符合条件的患者,其中2,133人(37.92%)接受了原发病灶的手术切除。K-M生存分析和Cox回归分析显示,局部手术与更好的生存独立相关。手术在大多数亚组和转移模式中提供了显着的生存益处。PSM之后,接受手术的患者生存时间更长(OS:46个月vs.32个月,p<0.001;CSS:50个月vs.34个月,p<0.001)。Logistic回归分析确定了六个重要的手术获益相关变量:T分期,放射治疗,种族,肝转移,脑转移瘤,和乳房亚型。将这些因素结合起来,以建立列线图和网络概率计算器(https://sunshine1。shinyapps.io/DynNomapp/),训练队列的AUC为0.673,验证队列的AUC为0.640。校准曲线表现出优异的一致性。DCA显示列线图在临床上有用。基于这个模型,手术患者被分为两组:无获益估计和有获益估计.估计受益子集中的患者与更长的生存期相关(中位OS:64个月vs.33个月,P<0.001)。此外,估计的无获益子集和非手术组之间的生存率无差异.
■我们的研究进一步证实了局部手术在患有BM的BC患者中的重要性,并提出了一种新的工具来确定最佳的手术候选者。
The impact of surgical resection of primary (PTR) on the survival of breast cancer (BC) patients with bone metastasis (BM) has been preliminarily investigated, but it remains unclear which patients are suitable for this procedure. Finally, this study aims to develop a predictive model to screen BC patients with BM who would benefit from local surgery.
BC patients with BM were identified using the Surveillance, Epidemiology, and End Results (SEER) database (2010 and 2015), and 39 patients were obtained for external validation from an Asian medical center. According to the status of local surgery, patients were divided into Surgery and Non-surgery groups. Propensity score matching (PSM) analysis was performed to reduce selection bias. Kaplan-Meier (K-M) survival and Cox regression analyses were conducted before and after PSM to study the survival difference between the two groups. The survival outcome and treatment modality were also investigated in patients with different metastatic patterns. The logistic regression analyses were utilized to determine significant surgery-benefit-related predictors, develop a screening nomogram and its online version, 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, whereas decision curve analysis (DCA) was used to assess its clinical usefulness.
This study included 5,625 eligible patients, of whom 2,133 (37.92%) received surgical resection of primary lesions. K-M survival analysis and Cox regression analysis demonstrated that local surgery was independently associated with better survival. Surgery provided significant survival benefits in most subgroups and metastatic patterns. 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: 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. The calibration curves exhibited excellent agreement. DCA indicated that the nomogram was clinically useful. Based on this model, surgery patients were assigned into two subsets: estimated sur-non-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-non-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.