Volume 24 Issue 4
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Article Navigation >  Chinese Journal of General Practice  > 2026  >  24(4): 589-592
GUO Lijuan, MA Fangxu, BAO Jie, WANG Shuang, LI Yi. A model study of biomarkers combined with lung function to predict the risk of acute exacerbations of COPD[J]. Chinese Journal of General Practice, 2026, 24(4): 589-592. doi: 10.16766/j.cnki.issn.1674-4152.004446
Citation: GUO Lijuan, MA Fangxu, BAO Jie, WANG Shuang, LI Yi. A model study of biomarkers combined with lung function to predict the risk of acute exacerbations of COPD[J]. Chinese Journal of General Practice, 2026, 24(4): 589-592. doi: 10.16766/j.cnki.issn.1674-4152.004446
shu

A model study of biomarkers combined with lung function to predict the risk of acute exacerbations of COPD

doi: 10.16766/j.cnki.issn.1674-4152.004446
  • 1.

    Department of Respiratory and Critical Care Medicine, Hebei Provincial Chest Hospital(Hebei Lung Cancer Prevention and Treatment Research Center), Shijiazhuang, Hebei 050000, China

Funds:

 20242171

  • Received Date: 2025-12-11
    Abstract
  •   Objective  To investigate the value of a combined lung function index model constructed from soluble cancer suppressor factor 2 (sST2), chitinase protein 40 (YKL-40), interleukin-10 (IL-10), and pulmonary surfactant D (SP-D) in early risk assessment of chronic obstructive pulmonary disease (COPD) acute exacerbations.  Methods  A total of 120 COPD patients admitted at Hebei Provincial Chest Hospital between January 2023 and December 2024 were selected as subjects, and divided into stable phase group (60 cases) and acute exacerbation phase group (60 cases) based on whether they experienced acute exacerbations. All patients ' serum levels of sST2, YKL-40, IL-10, and SP-D were measured, along with pulmonary function tests. Multivariate logistic regression was used to identify independent risk factors for COPD acute exacerbations, and a combined prediction model was established. The predictive efficacy of each indicator and the combined model was evaluated using receiver-operating characteristic (ROC) curves.  Results  Patients in the acute exacerbation group showed significantly higher serum levels of sST2, YKL-40, and SP-D compared to the stable phase group (P < 0.05), while IL-10 and FEV1%pred were markedly lower (P < 0.05). Multivariate logistic regression analysis demonstrated that all four biomarkers-sST2, YKL-40, IL-10, SP-D, and FEV1% pred-were independent predictors of COPD acute exacerbations (P < 0.05). The combined predictive model achieved an area under the curve (AUC) of 0.923 (95% CI: 0.881-0.965), with a sensitivity of 86.7% and specificity of 88.3%, demonstrating superior predictive performance compared to single biomarkers.  Conclusion  The integrated pulmonary function biomarker model combining sST2, YKL-40, IL-10, SP-D provides reliable prediction for COPD acute exacerbations, offering valuable insights for early risk assessment and clinical intervention guidance.

     

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