Peking University China-Japan Friendship School of Clinical Medicine, Beijing 100029, China.
Department of Orthopedic Surgery, China-Japan Friendship Hospital, Beijing 100029, China.
Biomed Res Int. 2021 May 15;2021:4510423. doi: 10.1155/2021/4510423. eCollection 2021.
We aimed to develop and validate a nomogram for predicting the overall survival of patients with limb chondrosarcomas.
The Surveillance, Epidemiology, and End Results (SEER) program database was used to identify patients diagnosed with chondrosarcomas, from which data was extracted from 18 registries in the United States between 1973 and 2016. A total of 813 patients were selected from the database. Univariate and multivariate analyses were performed using Cox proportional hazards regression models on the training group to identify independent prognostic factors and construct a nomogram to predict the 3- and 5-year survival probability of patients with limb chondrosarcomas. The predictive values were compared using concordance indexes (-indexes) and calibration plots.
All 813 patients were randomly divided into a training group ( = 572) and a validation group ( = 241). After univariate and multivariate Cox regression, a nomogram was constructed based on a new model containing the predictive variables of age, site, grade, tumor size, histology, stage, and use of surgery, radiotherapy, or chemotherapy. The prediction model provided excellent -indexes (0.86 and 0.77 in the training and validation groups, respectively). The good discrimination and calibration of the nomograms were demonstrated for both the training and validation groups.
The nomograms precisely and individually predict the overall survival of patients with limb chondrosarcomas and could assist personalized prognostic evaluation and individualized clinical decision-making.
我们旨在开发和验证一个列线图，用于预测肢体软骨肉瘤患者的总生存率。
使用监测、流行病学和最终结果（SEER）计划数据库来确定在美国 1973 年至 2016 年期间的 18 个登记处诊断为软骨肉瘤的患者，并从中提取数据。从数据库中总共选择了 813 名患者。使用 Cox 比例风险回归模型对训练组进行单变量和多变量分析，以确定独立的预后因素，并构建一个列线图来预测肢体软骨肉瘤患者的 3 年和 5 年生存率。通过一致性指数（-指数）和校准图比较预测值。
所有 813 名患者被随机分为训练组（n = 572）和验证组（n = 241）。经过单变量和多变量 Cox 回归分析，根据包含年龄、部位、分级、肿瘤大小、组织学、分期以及手术、放疗或化疗使用等预测变量的新模型构建了一个列线图。预测模型提供了出色的-指数（训练组和验证组分别为 0.86 和 0.77）。该列线图在训练组和验证组中均显示出良好的区分度和校准度。
该列线图能够精确地个体化预测肢体软骨肉瘤患者的总生存率，可辅助进行个性化预后评估和个体化临床决策。
