Department of Neurosurgery, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Eur Rev Med Pharmacol Sci. 2024 Feb;28(3):969-980. doi: 10.26355/eurrev_202402_35363.
This study aimed to develop and validate a nomogram and risk stratification system for the overall survival of pediatric patients with medulloblastoma after surgical repair.
In this multicenter, retrospective study, consecutive patients who underwent surgery for medulloblastoma at Shanghai Children's Medical Center and the First Affiliated Hospital of Fujian Medical University from 2010 to 2022 formed the training and external validation datasets, respectively. Univariable and multivariable Cox regression analyses were performed to identify variables associated with mortality in the training dataset. A nomogram prediction model was developed based on independent variables in the multivariable Cox regression analysis to predict the 1-, 3-, and 5-year overall survival. The area under receiver operating characteristic curve (AUC) and calibration curve were used to evaluate the discrimination and calibration of the nomogram. A risk stratification system based on the median risk score was also established to divide patients into two risk groups.
In the training dataset, Cox regression analyses identified tumor size, brainstem involvement and chemotherapy as independent predictors for overall survival. The AUC of the nomogram was 0.75 at 1 year, 0. 75 at 3 years, 0.77 at 5 years in the training dataset, 0.74 at 1 year, 0.70 at 3 years, and 0.70 at 5 years in the validation dataset. The calibration curve for the probability of 1-, 3-, and 5-year survival showed good agreement between the nomogram prediction and actual observation in the training and validation datasets. The risk stratification system could perfectly classify patients into two risk groups, and the overall survival in the two groups had a good division.
This low-cost, convenient, and noninvasive nomogram can be translated into clinical practice as a tool for risk stratification and individualized prognosis prediction for children with medulloblastoma.
本研究旨在开发和验证一种列线图和风险分层系统，用于预测接受手术修复的儿童髓母细胞瘤患者的总体生存率。
在这项多中心回顾性研究中，连续接受手术治疗的髓母细胞瘤患儿来自上海儿童医学中心和福建医科大学附属第一医院，分别构成了训练集和外部验证集。在训练集中，进行单变量和多变量 Cox 回归分析，以确定与死亡率相关的变量。基于多变量 Cox 回归分析中的独立变量，开发了一个列线图预测模型，以预测 1、3 和 5 年的总体生存率。使用接受者操作特征曲线（AUC）和校准曲线来评估列线图的区分度和校准度。还建立了基于中位数风险评分的风险分层系统，将患者分为两个风险组。
在训练集中，Cox 回归分析确定肿瘤大小、脑干侵犯和化疗是总体生存的独立预测因素。该列线图在训练集中的 1 年、3 年和 5 年 AUC 分别为 0.75、0.75 和 0.77，在验证集中分别为 0.74、0.70 和 0.70。1 年、3 年和 5 年生存率概率的校准曲线在训练集和验证集中均显示出列线图预测与实际观察之间的良好一致性。风险分层系统能够完美地将患者分为两个风险组，两组的总体生存率具有良好的划分。
这种低成本、方便、非侵入性的列线图可以转化为临床实践，作为一种用于风险分层和儿童髓母细胞瘤个体化预后预测的工具。
