影响支气管扩张合并活动性肺结核患者的因素分析及列线图预测模型的建立

Analysis of factors influencing bronchiectasis patients with active pulmonary tuberculosis and development of a nomogram prediction model.

作者信息

Yang Yitian, Du Lianfang, Ye Weilong, Liao Weifeng, Zheng Zhenzhen, Lin Xiaoxi, Chen Feiju, Pan Jingjing, Chen Bainian, Chen Riken, Yao Weimin

机构信息

The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China.

出版信息

Front Med (Lausanne). 2024 Nov 8;11:1457048. doi: 10.3389/fmed.2024.1457048. eCollection 2024.

DOI:10.3389/fmed.2024.1457048

PMID:39582970

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11581853/

Abstract

BACKGROUND

To identify the risk factors for bronchiectasis patients with active pulmonary tuberculosis (APTB) and to develop a predictive nomogram model for estimating the risk of APTB in bronchiectasis patients.

METHODS

A retrospective cohort study was conducted on 16,750 bronchiectasis patients hospitalized at the Affiliated Hospital of Guangdong Medical University and the Second Affiliated Hospital of Guangdong Medical University between January 2019 and December 2023. The 390 patients with APTB were classified as the case group, while 818 patients were randomly sampled by computer at a 1:20 ratio from the 16,360 patients with other infections to serve as the control group. Relevant indicators potentially leading to APTB in bronchiectasis patients were collected. Patients were categorized into APTB and inactive pulmonary tuberculosis (IPTB) groups based on the presence of tuberculosis. The general characteristics of both groups were compared. Variables were screened using the least absolute shrinkage and selection operator (LASSO) analysis, followed by multivariate logistic regression analysis. A nomogram model was established based on the analysis results. The model's predictive performance was evaluated using calibration curves, C-index, and ROC curves, and internal validation was performed using the bootstrap method.

RESULTS

LASSO analysis identified 28 potential risk factors. Multivariate analysis showed that age, gender, TC, ALB, MCV, FIB, PDW, LYM, hemoptysis, and hypertension are independent risk factors for bronchiectasis patients with APTB ( < 0.05). The nomogram demonstrated strong calibration and discrimination, with a C-index of 0.745 (95% CI: 0.715-0.775) and an AUC of 0.744 for the ROC curve. Internal validation using the bootstrap method produced a C-index of 0.738, further confirming the model's robustness.

CONCLUSION

The nomogram model, developed using common clinical serological characteristics, holds significant clinical value for assessing the risk of APTB in bronchiectasis patients.

摘要

背景

确定支气管扩张合并活动性肺结核（APTB）患者的危险因素，并建立预测列线图模型以评估支气管扩张患者发生APTB的风险。

方法

对2019年1月至2023年12月期间在广东医科大学附属医院和广东医科大学第二附属医院住院的16750例支气管扩张患者进行回顾性队列研究。将390例APTB患者分为病例组，从16360例其他感染患者中按1:20的比例通过计算机随机抽取818例患者作为对照组。收集可能导致支气管扩张患者发生APTB的相关指标。根据是否存在结核病将患者分为APTB组和非活动性肺结核（IPTB）组。比较两组的一般特征。使用最小绝对收缩和选择算子（LASSO）分析筛选变量，随后进行多因素逻辑回归分析。根据分析结果建立列线图模型。使用校准曲线、C指数和ROC曲线评估模型的预测性能，并使用自助法进行内部验证。

结果

LASSO分析确定了28个潜在危险因素。多因素分析显示，年龄、性别、总胆固醇（TC）、白蛋白（ALB）、平均红细胞体积（MCV）、纤维蛋白原（FIB）、血小板分布宽度（PDW）、淋巴细胞比例（LYM）、咯血和高血压是支气管扩张合并APTB患者的独立危险因素（<0.05）。列线图显示出良好的校准和区分能力，C指数为0.745（95%CI：0.715-0.775），ROC曲线的AUC为0.744。使用自助法进行内部验证得到的C指数为0.738，进一步证实了模型的稳健性。