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小于2岁神经母细胞瘤儿童的特异性生存列线图构建与验证：一项基于SEER数据库的研究
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Abstract:
背景：神经母细胞瘤(NB)是儿童最常见的非中枢神经系统实体肿瘤，占所有儿童恶性肿瘤的8~10%。我们的目的是探讨儿童神经母细胞瘤的预后因素，并构建一个列线图(nomogram)来预测2岁以下儿童神经母细胞瘤的癌症特异性生存(CSS)。方法：从监测、流行病学和最终结果(SEER)数据库下载2000年至2018年2岁以下神经母细胞瘤儿童的临床病理信息。所有患者被随机分配到训练队列(70%)或验证队列(30%)。采用最小绝对收缩和选择算子(LASSO)回归和逐步回归多变量Cox回归分析筛选2岁以下神经母细胞瘤患儿癌症特异性生存(CSS)的独立危险因素。选取的危险因素构建列线图(nomogram)来预测神经母细胞瘤患儿(<2岁)1年、3年和5年时的CSS。列线图的预测精度和判别能力由一致性指数(C-index)、受者工作曲线下面积(AUC)和校正曲线决定。采用决策曲线分析(Decision curve analysis, DCA)和Kaplan-Meier估计量验证预测模型的临床应用效果。结果：研究对象包括631名年龄小于2岁的神经母细胞瘤患儿。LASSO回归和逐步回归多因素Cox回归分析显示，年龄、肿瘤大小、肿瘤分期和远处转移手术是2岁以下神经母细胞瘤患儿发生CSS的独立危险因素。我们构建了一个列线图(nomogram)来预测神经母细胞瘤患者(<2岁)的CSS。训练组和验证组的c指数分别为0.888 (95% CI: 0.849~0.927)和0.885 (95% CI: 0.818~0.952)。训练队列和验证队列的AUC也表明该预测模型具有较好的准确性。修正曲线表明，预测模型的观测值与预测值高度吻合。DCA具有良好的临床应用价值。结论：在这项研究中，我们探讨了小于2岁神经母细胞瘤患者的预后因素。我们发现年龄、肿瘤大小、肿瘤分期和远处转移手术是CSS的独立危险因素。我们构建了一个列线图(nomogram)来预测2岁以下NB患儿的CSS。该预测模型可为医生和患者的临床决策提供参考。
Background: Neuroblastoma(NB) is the most common non-central nervous system solid tumor in children, accounting for 8~10% of all childhood malignancies. We aim to explore prognostic factors of NB in the children and construct a nomogram to predict cancer-specific survival (CSS) in children less than 2 years old with NB. Methods: The clinicopathological information of children (<2 years old) with NB from 2000 to 2018 was downloaded from the Surveillance, Epidemiology, and End Results (SEER) database. All patients were randomly assigned to a training cohort (70%) or a validation cohort (30%). Least absolute shrinkage and selection operator (LASSO) regression and stepwise backward multivariate Cox regression analysis were used to screen the independent risk factors of cancer-specific survival (CSS) in children (<2 years old) with NB. The selected risk factors were used to construct a nomogram to predict the CSS at 1-, 3-, and 5 years in children (<2 years old) with NB. The prediction accuracy and discriminant ability of nomogram are determined by consistency index (C-index), the area under the receiver operating curve (AUC) and correction curve. Decision curve analysis (DCA) and Kaplan-Meier estimator were used to verify the clinical application effect of the predictive model. Results: The subjects included 631 children aged less than 2 years with NB. LASSO regression and stepwise backward multivariate Cox regression analysis showed that age, tumor size, tumor stage and distant surgery were independent risk factors for CSS in children (<2 years old) with NB. We constructed a nomogram to predict CSS in patients(<2 years old) with NB.
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