Yang Qian-Kun, Su Yan-Na, Wang Wei, Wang Nan, Yao Zhong-Xiang, Zhang Xiao-Jing
Department of Bone and Soft Tissue Surgery, Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, Liaoning 110042, People's Republic of China.
Clinical Laboratory, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110042, People's Republic of China.
Cancer Manag Res. 2020 Jun 3;12:4193-4208. doi: 10.2147/CMAR.S251814. eCollection 2020.
Nutritional and immune status is paramount for the overall survival (OS) of patients with advanced osteosarcoma. Comprehensive prognostic predictors based on the two indices are scarce. This study aimed to construct and validate individualized web dynamic nomograms based on CONUT score or/and peripheral blood CD4+/CD8+ ratio for OS in patients with advanced osteosarcoma.
The clinical data of 376 advanced osteosarcoma patients from January 2000 to December 2019 were retrospectively collected. Data from the 301 patients (diagnosed in the first 15 years) were used as the development set and data from the remaining 75 patients were assigned as the validation set. Multivariate Cox regression analyses were conducted and three prediction models were constructed, namely, CD4+/CD8+ ratio univariate model (model 1), CONUT score univariate model (model 2), and CD4+/CD8+ ratio plus CONUT score (model 3). These models were visualized by conventional nomograms and individualized web dynamic nomograms, and their performances were further evaluated by C-index, calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA), respectively.
In multivariate Cox analysis, age, metastasis, ALP, CD4+/CD8+ ratio, chemotherapy, and CONUT score were identified as independent prognostic factors for OS. The calibration curves of the three models all showed good agreement between the actual observation and nomogram prediction for 1-year overall survival. In the development set, the C-index and area under the curve (AUC) of model 3 (0.837, 0.848) were higher than that of model 1 (0.765, 0.773) and model 2 (0.712, 0.749). Similar trends were observed in the validation set. The net benefits of model 3 were better than the other two models within the threshold probability of 36-80% in DCA.
CONUT score and peripheral CD4+/CD8+ ratio are easily available, reliable, and economical prognostic predictors for survival prediction and stratification in patients with advanced osteosarcoma, but the two predictors combined can establish a better prognosis prediction model.
营养和免疫状态对晚期骨肉瘤患者的总生存期（OS）至关重要。基于这两个指标的综合预后预测因素较少。本研究旨在构建并验证基于CONUT评分或/和外周血CD4+/CD8+比值的个体化网络动态列线图，用于预测晚期骨肉瘤患者的OS。
回顾性收集2000年1月至2019年12月376例晚期骨肉瘤患者的临床资料。将301例患者（在前15年诊断）的数据用作开发集，其余75例患者的数据用作验证集。进行多因素Cox回归分析并构建三个预测模型，即CD4+/CD8+比值单因素模型（模型1）、CONUT评分单因素模型（模型2）以及CD4+/CD8+比值加CONUT评分（模型3）。这些模型通过传统列线图和个体化网络动态列线图进行可视化，并分别通过C指数、校准曲线、受试者工作特征（ROC）曲线和决策曲线分析（DCA）进一步评估其性能。
在多因素Cox分析中，年龄、转移、碱性磷酸酶（ALP）、CD4+/CD8+比值、化疗和CONUT评分被确定为OS的独立预后因素。三个模型的校准曲线在1年总生存期的实际观察值和列线图预测值之间均显示出良好的一致性。在开发集中，模型3的C指数和曲线下面积（AUC）（0.837，0.848）高于模型1（0.765，0.773）和模型2（0.712，0.749）。在验证集中也观察到类似趋势。在DCA中，模型3在36%-80%的阈值概率范围内的净效益优于其他两个模型。
CONUT评分和外周血CD4+/CD8+比值是晚期骨肉瘤患者生存预测和分层中易于获得、可靠且经济的预后预测因素，但两者结合可建立更好的预后预测模型。
