Introduction

Accurate diagnosis of distant metastasis especially uncommon site of metastasis (UCM) in patients with Wilms tumor (WTs) is a demanding prerequisite for administration of appropriate therapy and achieving better survival outcome.

Objective

To develop and validate a nomogram to predict probability of distant metastasis, and identify population demanded for rigorous imaging evaluations in children with WTs.

Material and methods

Data of patients diagnosed with unilateral WTs and aged under 18 years old, were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The included patients were randomly allocated to the training and the validation cohort. Logistic regression analyses were performed to identify the independent risk factors and develop a predicting model of distant metastasis in WTs. The model-based nomogram was created and internally validated. Cut-off value of nomogram points was derived by using the receiver operating characteristics (ROC) curve analysis. Performance of the nomogram was evaluated in terms of discrimination, calibration and clinical usefulness.

Results

A total 717 WTs patients were included in the study. Age at diagnosis (OR 1.173, 95%CI: 1.079–1.279), LND (OR 8.260, 95%CI: 2.837–24.814) and tumor size (OR 2.141, 95%CI: 1.378–3.329) were identified as the independent risk factors of distant metastasis in WTs. These three factors were incorporated to develop a model and a nomogram. The nomogram presented with good discriminative ability in the training cohort (C-statistics, 0.703) and validation cohort (C-statistics, 0.764), respectively. The calibration curves demonstrated adequate agreement between predicted probability and observed probability of distant metastasis. The nomogram also revealed its clinical usefulness by application of decision curve analysis (DCA). Cut-off value of nomogram points was 58 and its corresponding probability of distant metastasis was 0.22. The value was applied in risk stratification dividing the general cohort into high-risk and low-risk group.

Discussion

Our study for the first time developed and validated a model and a visualized nomogram for individualized prediction of distant metastasis in WTs. C-statistics, calibration curves and DCA demonstrated good performance and clinical usefulness of the nomogram. Patients stratified as high-risk group were demanded for rigorous imaging evaluations to accurately identify UCM.

Conclusion

The nomogram, developed by incorporation of three independent risk factors, which are age at diagnosis, LND and tumor size, is used to facilitate individualized prediction of distant metastasis in WTs. Rigorous imaging evaluations are recommended for patients in high-risk group to identify UCM.

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Summary figure. Flow chart constructed to present the selection process.

中文翻译：

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诺模图可预测儿童恶性肿瘤远处转移：基于SEER数据库的研究。

介绍

对于Wilms肿瘤（WTs）患者，准确诊断远处转移，尤其是罕见的转移部位（UCM），是进行适当治疗并获得更好生存结果的先决条件。

目的

开发并验证诺模图以预测远处转移的可能性，并确定需要进行严格影像学评估的WT患者的人群。

材料与方法

从监测，流行病学和最终结果（SEER）数据库中提取诊断为单侧WT且年龄在18岁以下的患者数据。纳入的患者被随机分配到培训和验证队列中。进行逻辑回归分析以鉴定独立的危险因素，并建立WTs远处转移的预测模型。创建了基于模型的列线图，并在内部进行了验证。通过使用接收器工作特性（ROC）曲线分析得出列线图点的截止值。根据辨别力，校准和临床实用性评估了列线图的性能。

结果

该研究共包括717名WTs患者。诊断时的年龄（OR 1.173，95％CI：1.079–1.279），LND（OR 8.260，95％CI：2.837–24.814）和肿瘤大小（OR 2.141，95％CI：1.378–3.329）被确定为独立风险WTs远处转移的因素。将这三个因素结合起来以建立模型和列线图。列线图在训练队列（C统计量，0.703）和验证队列（C统计量，0.764）中分别具有良好的判别能力。校正曲线表明远处转移的预测概率与观察到的概率之间具有足够的一致性。诺模图还通过应用决策曲线分析（DCA）揭示了其临床实用性。列线图点的截止值为58，其相应的远处转移概率为0.22。

讨论区

我们的研究首次开发并验证了模型和可视化列线图，用于个体化预测野生型患者的远处转移。C统计量，校准曲线和DCA证明了列线图的良好性能和临床实用性。要求将高危组分层的患者进行严格的影像学评估，以准确识别UCM。

结论

通过结合三个独立的危险因素（诊断时的年龄，LND和肿瘤大小）开发的列线图用于促进WT远处转移的个体化预测。建议对高危人群进行严格的影像学评估以识别UCM。

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汇总图。构造流程图以展示选择过程。