Development and validation of a machine learning-based diagnostic model for identifying nonneutropenic invasive pulmonary aspergillosis in suspected patients: a multicenter cohort study.

Journal: Microbiology spectrum
Published Date: Jul 1, 2025

Abstract

UNLABELLED: This study aims to develop and validate an optimized diagnostic model for nonneutropenic invasive pulmonary aspergillosis (IPA) among suspected cases. A cohort of 344 nonneutropenic suspected cases from 13 medical centers (August 2020 to February 2024) was analyzed. The cohort was divided into a training data set (70%) and a testing data set (30%) using stratified sampling based on the IPA diagnosis. Three machine learning models (a regularized logistic regression model, a support vector machine model, and a weighted ensemble model) were developed. SHapley Additive explanation (SHAP) method was used for model interpretation. Six predictor variables were finally selected: sputum culture, -specific IgG, imaging feature of cavity, serum galactomannan, critical condition, and plasma pentraxin 3. The weighted ensemble model, exhibiting the significantly higher specificity of 95.1% in internal cross-validation and 95.7% in testing among the three models, was selected as the optimal prediction model despite comparable discrimination capacity, calibration ability, and clinical applicability across all models. The risk score derived from SHAP values showed a highly significant correlation with the predicted probability of the weighted ensemble model (Spearman = 0.974), achieving an area under the curve of 0.857 in internal cross-validation and 0.871 in external testing. Using the optimal cut-off value of 3, the risk score demonstrated sensitivity (68.8%) and specificity (87.5%) comparable to those of bronchoalveolar lavage fluid galactomannan (cut-off = 1.0). The diagnostic model and risk score could assist in identifying nonneutropenic IPA from suspected cases independently of invasive procedures, thereby enhancing clinical applicability.

Authors

  • Xinyu Wang
    Department of Endocrinology, Institute of Translational Medicine, Health Science Center, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen, Guangdong, China.
  • Yajie Lu
    Department of Respiratory and Critical Care Medicine, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
  • Chao Sun
    Hospital for Skin Diseases and Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, China.
  • Huanhuan Zhong
    Department of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
  • Yuchen Cai
    Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Min Cao
    Guangzhou Panyu Sanatorium, Guangzhou, Guangdong, China.
  • Xuefan Cui
    Department of Respiratory and Critical Care Medicine, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
  • Wenkui Sun
    Department of Respiratory and Critical Care Medicine, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
  • Li Wang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Xin Lu
    CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
  • Cheng Chen
    Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, University of Science and Technology of China, China.
  • Yanbin Chen
    Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Soochow University, Suzhou, China.
  • Chunlai Feng
    School of Pharmacy, Jiangsu University, Zhenjiang, China.
  • Yujian Tao
    Department of Respiratory and Critical Care Medicine, Affiliated Hospital of Yangzhou University, Yangzhou, Jiangsu, China.
  • Jun Zhou
    Department of Clinical Research Center, Dazhou Central Hospital, Dazhou 635000, China.
  • Jiaxin Shi
    School of Science, Yanshan University, Qinhuangdao 066001, China.
  • Guoer Ma
    Department of Respiratory and Critical Care Medicine, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, China.
  • Yuanqin Li
    Department of Respiratory and Critical Care Medicine, Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, China.
  • Xin Su
    Department of Integrative Oncology, China-Japan Friendship Hospital, Beijing 100029, China.

Keywords

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