Xiang Guang-Heng, Zhu Juan-Juan, Ke Chen-Rong, Weng Yi-Min, Fang Ming-Qiao, Zhu Si-Pin, Li Yu-An, Xiao Jian, Xu Lei
Department of Orthopaedic, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325035, China.
School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, Zhejiang 325035, China.
J Oncol. 2020 Sep 26;2020:8284931. doi: 10.1155/2020/8284931. eCollection 2020.
Due to the rarity, it is difficult to predict the survival of patients with fibrosarcoma. This study aimed to apply a nomogram to predict survival outcomes in patients with fibrosarcoma.
A total of 2235 patients with diagnoses of fibrosarcoma were registered in the Surveillance, Epidemiology, and End Results database, of whom 663 patients were eventually enrolled. Univariate and multivariate Cox analyses were used to identify independent prognostic factors. Nomograms were constructed to predict 3-year and 5-year overall survival and cancer-specific survival of patients with fibrosarcoma.
In univariate and multivariate analyses of OS, age, sex, race, tumor stage, pathologic grade, use of surgery, and tumor size were identified as independent prognostic factors. Age, sex, tumor stage, pathologic grade, use of surgery, and tumor size were significantly associated with CSS. These characteristics were further included to establish the nomogram for predicting 3-year and 5-year OS and CSS. For the internal validation of the nomogram predictions of OS and CSS, the -indices were 0.784 and 0.801.
We developed the nomograms that estimated 3-year and 5-year OS and CSS. These nomograms not only have good discrimination performance and calibration but also provide patients with better clinical benefits.
由于纤维肉瘤较为罕见，难以预测其患者的生存期。本研究旨在应用列线图预测纤维肉瘤患者的生存结局。
共有2235例诊断为纤维肉瘤的患者被纳入监测、流行病学和最终结果数据库，其中663例患者最终被纳入研究。采用单因素和多因素Cox分析来确定独立的预后因素。构建列线图以预测纤维肉瘤患者的3年和5年总生存率及癌症特异性生存率。
在总生存期的单因素和多因素分析中，年龄、性别、种族、肿瘤分期、病理分级、手术应用情况和肿瘤大小被确定为独立的预后因素。年龄、性别、肿瘤分期、病理分级、手术应用情况和肿瘤大小与癌症特异性生存率显著相关。将这些特征进一步纳入以建立预测3年和5年总生存期及癌症特异性生存率的列线图。对于列线图对总生存期和癌症特异性生存率预测的内部验证，C指数分别为0.784和0.801。
我们开发了可估计3年和5年总生存期及癌症特异性生存率的列线图。这些列线图不仅具有良好的区分性能和校准度，还为患者提供了更好的临床益处。
