Department of Traumatology and Orthopaedics, Affiliated Hospital of Chengde Medical College, Chengde, China.
Cancer Rep (Hoboken). 2022 May;5(5):e1594. doi: 10.1002/cnr2.1594. Epub 2021 Dec 3.
Leiomyosarcoma (LMS) is one of the most common soft tissue sarcomas. LMS is prone to distant metastasis (DM), and patients with DM have a poor prognosis.
In this study, we investigated the risk factors of DM in LMS patients and the prognostic factors of LMS patients with DM.
LMS patients diagnosed between 2010 and 2016 were extracted from the Surveillance, Epidemiology, and End Result (SEER) database. Patients were randomly divided into the training set and validation set. Univariate and multivariate logistic regression analyses were performed, and a nomogram was established. The area under the curve (AUC), calibration curve, and decision curve analysis (DCA) were used to evaluate the nomogram. Based on the nomogram, a web-based nomogram is established. The univariate and multivariate Cox regression analyses were used to assess the prognostic risk factors of LMS patients with DM. Eventually, 2184 patients diagnosed with LMS were enrolled, randomly divided into the training set (n = 1532, 70.14%) and validation set (n = 652, 29.86%). Race, primary site, grade, T stage, and tumor size were correlated with DM incidence in LMS patients. The AUC of the nomogram is 0.715 in training and 0.713 in the validation set. The calibration curve and DCA results showed that the nomogram performed well in predicting the DM risk. A web-based nomogram was established to predict DM's risk in LMS patients (https://wenn23.shinyapps.io/riskoflmsdm/). Epithelioid LMS, in uterus, older age, giant tumor, multiple organ metastasis, without surgery, and chemotherapy had a poor prognosis.
The established web-based nomogram (https://wenn23.shinyapps.io/riskoflmsdm/) is an accurate and personalized tool to predict the risks of LMS developing DM. Advanced age, larger tumor, multiple organ metastasis, epithelioid type, uterine LMS, no surgery, and no chemotherapy were associated with poor prognosis in LMS patients with DM.
平滑肌肉瘤（LMS）是最常见的软组织肉瘤之一。LMS 易发生远处转移（DM），DM 患者预后不良。
本研究旨在探讨 LMS 患者 DM 的危险因素及 LMS 合并 DM 患者的预后因素。
从监测、流行病学和最终结果（SEER）数据库中提取 2010 年至 2016 年间诊断为 LMS 的患者。将患者随机分为训练集和验证集。进行单因素和多因素 logistic 回归分析，并建立列线图。采用曲线下面积（AUC）、校准曲线和决策曲线分析（DCA）评估列线图。基于列线图，建立了一个基于网络的列线图。采用单因素和多因素 Cox 回归分析评估 LMS 合并 DM 患者的预后危险因素。最终纳入 2184 例 LMS 患者，随机分为训练集（n=1532，70.14%）和验证集（n=652，29.86%）。种族、原发部位、分级、T 分期和肿瘤大小与 LMS 患者 DM 的发生率相关。列线图在训练集和验证集中的 AUC 分别为 0.715 和 0.713。校准曲线和 DCA 结果表明，该列线图在预测 DM 风险方面表现良好。建立了一个基于网络的列线图（https://wenn23.shinyapps.io/riskoflmsdm/），用于预测 LMS 患者发生 DM 的风险。上皮样 LMS、子宫内、年龄较大、巨大肿瘤、多器官转移、未手术和未化疗的患者预后较差。
建立的基于网络的列线图（https://wenn23.shinyapps.io/riskoflmsdm/）是一种准确且个性化的工具，可用于预测 LMS 发生 DM 的风险。年龄较大、肿瘤较大、多器官转移、上皮样类型、子宫 LMS、未手术和未化疗与 LMS 合并 DM 患者的不良预后相关。
