小细胞肺癌患者化疗期间肺部感染风险评分模型的构建与验证

Development and validation of a risk scoring model for pulmonary infection during chemotherapy in patients with small cell lung cancer

摘要

目的：探究小细胞肺癌（small cell lung cancer，SCLC）患者化疗期间肺部感染的危险因素，建立风险预测模型并验证。方法：回顾性纳入2020年4月—2022年3月在南京医科大学第一附属医院接受化疗的SCLC患者作为训练集（251例），同期前瞻性连续纳入SCLC患者作为验证集（112例）。根据随访结果分为肺部感染组和非肺部感染组，在训练集采用单因素及多因素Logistic回归分析筛选独立危险因素并构建评分模型，采用受试者工作特征（receiver operating characteristic，ROC）曲线评价模型区分度，校准曲线评估模型一致性，并与既往预测模型进行比较，在验证集中对模型进行外部验证。结果：多因素Logistic回归分析显示，吸烟史、胸腔积液、声音嘶哑、单药化疗方案及首次化疗后白蛋白<35 g/L是SCLC患者化疗期间肺部感染的独立危险因素（P均< 0.05）。基于上述5个变量建立SCLC-PIR评分模型。在训练集中应用此模型的ROC曲线下面积（area under the curve，AUC）为0.870（95% CI：0.818~0.922），最佳截断值为5分，对应的灵敏度为71.7%，特异度为89.4%。校准曲线显示此模型预测的感染风险与实际风险一致性良好。在验证集中应用此模型的预测效能保持稳定，AUC为0.896（95% CI：0.832~0.961），且此模型的预测效能高于既往列线图模型。结论：基于吸烟史、胸腔积液、声音嘶哑、单药化疗方案及化疗后白蛋白<35 g/L构建的SCLC-PIR评分模型具有良好的区分度和一致性，能够有效预测SCLC患者化疗期间肺部感染风险，可为早期识别高风险患者提供参考。

Abstract

Objective：To investigate the risk factors for pulmonary infection during chemotherapy in patients with small cell lung cancer（SCLC）and to develop and validate a risk prediction model. Methods：Patients with SCLC who received chemotherapy at the First Affiliated Hospital of Nanjing Medical University from April 2020 to March 2022 were retrospectively enrolled as the training cohort（n=251），and a prospective cohort of SCLC patients was consecutively included as the validation cohort（n=112）. According to follow-up outcomes，patients were divided into the pulmonary infection and non-infection groups. In the training cohort，univariate and multivariate logistic regression analyses were performed to identify independent risk factors and to construct a scoring model. The discriminative ability of the model was evaluated using the receiver operating characteristic（ROC）curve，and calibration was assessed using calibration curves. The model was compared with previously reported nomogram models and further validated in the validation cohort. Results：Multivariate logistic regression analysis showed that smoking history，pleural effusion，hoarseness，single-agent chemotherapy，and albumin <35 g/L after the first cycle of chemotherapy were independent risk factors for pulmonary infection in patients with SCLC（all P < 0.05）. Based on these five variables，the SCLC-PIR scoring model was established. In the training cohort，the area under the curve（AUC）was 0.870（95% CI：0.818-0.922），with an optimal cutoff value of 5 points，yielding a sensitivity of 71.7% and a specificity of 89.4%. The calibration curve demonstrated good consistency between the infection risks predicted by this model and the actual risks. The predictive performance of the model remained stable when applied to the validation cohort，with an AUC of 0.896（95% CI：0.832-0.961）. Furthermore，the predictive efficacy of this model outperformed previous nomogram models. Conclusion：The SCLC-PIR scoring model，based on smoking history，pleural effusion，hoarseness，single-agent chemotherapy，and post-chemotherapy albumin <35 g/L，shows good discrimination and calibration in predicting pulmonary infection during chemotherapy in patients with SCLC，and may be useful for early identification of high-risk patients.

关键词

小细胞肺癌 / 肺部感染 / 风险预测 / 评分模型

Key words

small cell lung cancer / pulmonary infection / risk prediction / scoring model

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基金资助

江苏省人民医院“临床能力提升工程”护理项目(JSPH-NC-2021-17)