Department of Orthopaedics, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu, 610041, Sichuan, People's Republic of China.
Health Management Center, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu, 610041, Sichuan, People's Republic of China.
Sci Rep. 2022 Jul 13;12(1):11851. doi: 10.1038/s41598-022-16055-z.
Retroperitoneal leiomyosarcomas (RLS) are the second most common type of retroperitoneal sarcoma and one of the most aggressive tumours. The lack of early warning signs and delay in regular checkups lead to a poor prognosis. This study aims to create a nomogram to predict RLS patients' overall survival (OS). Patients diagnosed with RLS in the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2018 were enrolled in this study. First, univariable and multivariable Cox regression analyses were used to identify independent prognostic factors, followed by constructing a nomogram to predict patients' OS at 1, 3, and 5 years. Secondly, the nomogram's distinguishability and prediction accuracy were assessed using receiver operating characteristic (ROC) and calibration curves. Finally, the decision curve analysis (DCA) investigated the nomogram's clinical utility. The study included 305 RLS patients, and they were divided into two groups at random: a training set (216) and a validation set (89). The training set's multivariable Cox regression analysis revealed that surgery, tumour size, tumour grade, and tumour stage were independent prognostic factors. ROC curves demonstrated that the nomogram had a high degree of distinguishability. In the training set, area under the curve (AUC) values for 1, 3, and 5 years were 0.800, 0.806, and 0.788, respectively, while in the validation set, AUC values for 1, 3, and 5 years were 0.738, 0.780, and 0.832, respectively. As evidenced by the calibration curve, the nomogram had high prediction accuracy. Moreover, DCA revealed that the nomogram had high clinical utility. Furthermore, the risk stratification system based on the nomogram could effectively categorise patients into three mortality risk subgroups. Therefore, the developed nomogram and risk stratification system may aid in optimising the treatment decisions of RLS patients to improve treatment prognosis and maximise their healthcare outcomes.
腹膜后平滑肌肉瘤（RLS）是腹膜后肉瘤中第二常见的类型，也是最具侵袭性的肿瘤之一。由于缺乏早期预警信号和定期检查的延误，导致预后较差。本研究旨在建立一个列线图来预测 RLS 患者的总生存（OS）。本研究纳入了 2000 年至 2018 年期间在监测、流行病学和最终结果（SEER）数据库中诊断为 RLS 的患者。首先，使用单变量和多变量 Cox 回归分析来确定独立的预后因素，然后构建一个列线图来预测患者的 1、3 和 5 年 OS。其次，使用接收者操作特征（ROC）和校准曲线评估列线图的区分度和预测准确性。最后，决策曲线分析（DCA）评估了列线图的临床实用性。本研究共纳入 305 例 RLS 患者，随机分为两组：训练集（216 例）和验证集（89 例）。训练集的多变量 Cox 回归分析显示，手术、肿瘤大小、肿瘤分级和肿瘤分期是独立的预后因素。ROC 曲线表明该列线图具有高度的区分度。在训练集中，1、3 和 5 年的曲线下面积（AUC）值分别为 0.800、0.806 和 0.788，而在验证集中，1、3 和 5 年的 AUC 值分别为 0.738、0.780 和 0.832。校准曲线表明该列线图具有较高的预测准确性。此外，DCA 显示该列线图具有较高的临床实用性。此外，基于列线图的风险分层系统可以有效地将患者分为三个死亡风险亚组。因此，开发的列线图和风险分层系统可以帮助优化 RLS 患者的治疗决策，改善治疗预后，并最大限度地提高他们的医疗保健效果。
