Department of Orthopaedics, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, 310000, Zhejiang, People's Republic of China.
Department of Orthopaedics, Hangzhou Ding Qiao Hospital, Hangzhou, China.
Sci Rep. 2023 Dec 27;13(1):23018. doi: 10.1038/s41598-023-50401-z.
Spindle cell sarcoma (SCS) is rare in clinical practice. The objective of this study was to establish nomograms to predict the OS and CSS prognosis of patients with SCS based on the Surveillance, Epidemiology, and End Results (SEER) database. The data of patients with SCS between 2004 and 2020 were extracted from the SEER database and randomly allocated to a training cohort and a validation cohort. Univariate and multivariate Cox regression analyses were used to screen for independent risk factors for both overall survival (OS) and cancer-specific survival (CSS). Nomograms for OS and CSS were established for patients with SCS based on the results of multivariate Cox analysis. Then, we validated the nomograms by the concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Finally, Kaplan‒Meier curves and log-rank tests were applied to compare patients with SCS at three different levels and in different treatment groups. A total of 1369 patients with SCS were included and randomly allocated to a training cohort (n = 1008, 70%) and a validation cohort (n = 430, 30%). Age, stage, grade, tumour location, surgery, radiation and diagnosis year were found to be independent prognostic factors for OS by Cox regression analysis, while age, stage, grade, tumour location and surgery were found to be independent prognostic factors for CSS. The nomogram models were established based on the results of multivariate Cox analysis for both OS and CSS. The C-indices of the OS model were 0.76 and 0.77 in the training and validation groups, respectively, while they were 0.76 and 0.78 for CSS, respectively. For OS, the 3- and 5-year AUCs were 0.801 and 0.798, respectively, in the training cohort and 0.827 and 0.799, respectively, in the validation cohort; for CSS, they were 0.809 and 0.786, respectively, in the training cohort and 0.831 and 0.801, respectively, in the validation cohort. Calibration curves revealed high consistency in both OS and CSS between the observed survival and the predicted survival. In addition, DCA was used to analyse the clinical practicality of the OS and CSS nomogram models and revealed that they had good net benefits. Surgery remains the main treatment method for SCS patients. The two nomograms we established are expected to accurately predict the personalized prognosis of SCS patients and may be useful for clinical decision-making.
梭形细胞肉瘤（SCS）在临床实践中较为罕见。本研究旨在基于监测、流行病学和最终结果（SEER）数据库，建立预测 SCS 患者总生存期（OS）和癌症特异性生存期（CSS）的列线图。从 SEER 数据库中提取 2004 年至 2020 年期间 SCS 患者的数据，并将其随机分配到训练队列和验证队列中。使用单变量和多变量 Cox 回归分析筛选出 OS 和 CSS 的独立危险因素。根据多变量 Cox 分析的结果，为 SCS 患者建立 OS 和 CSS 的列线图。然后，我们通过一致性指数（C 指数）、接受者操作特征（ROC）曲线、校准曲线和决策曲线分析（DCA）来验证列线图。最后，应用 Kaplan-Meier 曲线和对数秩检验比较了三个不同水平和不同治疗组的 SCS 患者。共纳入 1369 例 SCS 患者，随机分配至训练队列（n=1008，70%）和验证队列（n=430，30%）。Cox 回归分析发现年龄、分期、分级、肿瘤位置、手术、放疗和诊断年份是 OS 的独立预后因素，而年龄、分期、分级、肿瘤位置和手术是 CSS 的独立预后因素。OS 和 CSS 的列线图模型是基于多变量 Cox 分析的结果建立的。OS 模型的 C 指数在训练组和验证组中分别为 0.76 和 0.77，CSS 模型的 C 指数分别为 0.76 和 0.78。OS 方面，训练组和验证组的 3 年和 5 年 AUC 分别为 0.801 和 0.798，0.827 和 0.799；CSS 方面，训练组和验证组的 3 年和 5 年 AUC 分别为 0.809 和 0.786，0.831 和 0.801。校准曲线显示 OS 和 CSS 中观察到的生存与预测生存之间具有高度一致性。此外，我们使用 DCA 分析了 OS 和 CSS 列线图模型的临床实用性，结果表明它们具有良好的净收益。手术仍然是 SCS 患者的主要治疗方法。我们建立的这两个列线图有望准确预测 SCS 患者的个性化预后，可能有助于临床决策。
