Dilimulati Muheremu, Yuan Shuhua, Jiang Hejun, Wang Yahua, Ma Hui, Shen Shiyu, Lin Jilei, Chen Jiande, Yin Yong
Department of Respiratory Medicine, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Child Health Advocacy Institute, China Hospital Development Institute, Shanghai Jiao Tong University, Shanghai, China.
Front Oncol. 2024 Aug 8;14:1385600. doi: 10.3389/fonc.2024.1385600. eCollection 2024.
With the widespread use of computed tomography (CT), the detection rate of pulmonary nodules in children has gradually increased. Due to the lack of epidemiological evidence and clinical guideline on pulmonary nodule treatment in children, we aimed to provide a reference for the clinical diagnosis and management of pediatirc pulmonary nodules.
This retrospective study collected consecutive cases from April 2012 to July 2021 in the Shanghai Children's Medical Center. The sample included children with pulmonary nodules on chest CT scans and met the inclusion criteria. All patients were categorized into tumor and non-tumor groups by pre-CT clinical diagnosis. Nodule characteristics between groups were analyzed. To establish a clinical assessment model for the benign versus malignant pulmonary nodules, patients who have been followed-up for three months were detected and a decision tree model for nodule malignancy prediction was constructed and validated.
The sample comprised 1341 patients with an average age of 7.2 ± 4.6 years. More than half of them (51.7%) were diagnosed with malignancies before CT scan. 48.3% were diagnosed with non-tumor diseases or healthy. Compared to non-tumor group, children with tumor were more likely to have multiple nodules in both lungs, with larger size and often be accompanied by osteolytic or mass lesions. Based on the decision tree model, patients' history of malignancies, nodules diameter size≥5mm, and specific nodule distribution (multiple in both lungs, multiple in the right lung or solitary in the upper or middle right lobe) were important potential predictors for malignity. In the validation set, sensitivity, specificity and AUC were 0.855, 0.833 and 0.828 (95%CI: 0.712-0.909), respectively.
This study conducted a clinical assessment model to differentiate benignity and malignancy of pediatric pulmonary nodules. We suggested that a nodule's diameter, distribution and patient's history of malignancies are predictable factors in benign or malignant determination.
随着计算机断层扫描（CT）的广泛应用，儿童肺结节的检出率逐渐上升。由于缺乏儿童肺结节治疗的流行病学证据和临床指南，我们旨在为儿童肺结节的临床诊断和管理提供参考。
这项回顾性研究收集了2012年4月至2021年7月在上海儿童医学中心的连续病例。样本包括胸部CT扫描发现肺结节且符合纳入标准的儿童。所有患者根据CT检查前的临床诊断分为肿瘤组和非肿瘤组。分析两组之间的结节特征。为建立肺结节良恶性的临床评估模型，对随访三个月的患者进行检测，并构建和验证结节恶性预测的决策树模型。
样本包括1341例患者，平均年龄为7.2±4.6岁。其中超过一半（51.7%）在CT扫描前被诊断为恶性肿瘤。48.3%被诊断为非肿瘤疾病或健康。与非肿瘤组相比，肿瘤患儿更易出现双肺多发结节，结节更大，且常伴有溶骨性病变或肿块。基于决策树模型，患者的恶性肿瘤病史、结节直径≥5mm以及特定的结节分布（双肺多发、右肺多发或右上叶或右中叶单发）是恶性的重要潜在预测因素。在验证集中，敏感性、特异性和AUC分别为0.855、0.833和0.828（95%CI：0.712 - 0.909）。
本研究建立了一个临床评估模型以区分儿童肺结节的良恶性。我们认为结节直径大小、分布以及患者的恶性肿瘤病史是判断良恶性的可预测因素。
