Yu Luyan, Wu Yiheng, Lin Nan, Sun Changxuan, Zhou Ying, Chu Xiaoyi, Guan Lejing, Bai Guannan, Zhu Jihua
Department of Neurosurgery, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China.
Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Transl Pediatr. 2025 Jun 27;14(6):1137-1146. doi: 10.21037/tp-2024-629. Epub 2025 Jun 25.
Acute chemotherapy-induced nausea and vomiting (CINV) affects 80-95% of pediatric cancer patients, with distinct risk patterns from adults, yet few risk prediction models exist for this population. We aimed to develop and validate a prediction model for acute CINV in pediatric patients with cancers, providing a tool to guide the clinical implementation of CINV prophylaxis and reduce CINV occurrence in children.
A total of 378 hospitalized children who underwent chemotherapy at the Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China, between August 1, 2022, and March 31, 2023, were enrolled. Demographic, disease-related, and chemotherapy-related factors were collected using a self-developed questionnaire. Multivariate logistic regression was employed to identify predictors for the model. Nomograms, receiver operating characteristic (ROC) curves, calibration curves, and decision curve analyses were used to evaluate model performance. External validation was conducted on 230 patients treated at the Children's Hospital, Zhejiang University School of Medicine from 1 May to 31 August 2023.
Independent predictors of chemotherapy-induced nausea (CIN) included prior CINV experience, body weight, and negative emotions or mood changes during chemotherapy. Predictors of chemotherapy-induced vomiting (CIV) included chemotherapy cycle count, emetogenicity risk grade of chemotherapy drugs, adequate sleep duration, tumor type, and prior CINV experience. The nomogram parameters, along with ROC, calibration, and decision curves demonstrated good predictive performance for both CIN and CIV.
This is the first study to develop a risk prediction model for CINV among pediatric cancer patients. The prediction models were relatively fit. It provides clinical healthcare professionals with an effective and easy-to-use tool for predicting the risk of having CINV; thus, they could provide timely and personalized interventions to prevent CINV and reduce adverse events associated with CINV before chemotherapy.
急性化疗引起的恶心和呕吐（CINV）影响80%-95%的儿科癌症患者，其风险模式与成人不同，但针对该人群的风险预测模型很少。我们旨在开发并验证一种针对患有癌症的儿科患者急性CINV的预测模型，提供一种工具来指导CINV预防的临床实施，并减少儿童CINV的发生。
共纳入了2022年8月1日至2023年3月31日期间在浙江大学医学院附属儿童医院住院接受化疗的378名儿童。使用自行开发的问卷收集人口统计学、疾病相关和化疗相关因素。采用多变量逻辑回归来确定模型的预测因素。使用列线图、受试者操作特征（ROC）曲线、校准曲线和决策曲线分析来评估模型性能。对2023年5月1日至8月31日在浙江大学医学院附属儿童医院接受治疗的230名患者进行了外部验证。
化疗引起的恶心（CIN）的独立预测因素包括既往CINV经历、体重以及化疗期间的负面情绪或情绪变化。化疗引起的呕吐（CIV）的预测因素包括化疗周期数、化疗药物的致吐风险等级、充足的睡眠时间、肿瘤类型以及既往CINV经历。列线图参数以及ROC、校准和决策曲线对CIN和CIV均显示出良好的预测性能。
这是第一项针对儿科癌症患者CINV开发风险预测模型的研究。该预测模型拟合度相对较好。它为临床医护人员提供了一种有效且易于使用的工具来预测发生CINV的风险；因此，他们可以在化疗前提供及时且个性化的干预措施以预防CINV并减少与CINV相关的不良事件。
