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<p>To determine the predictors of irreversible respiratory failure in idiopathic inflammatory myopathy-associated interstitial lung disease (IIM-ILD) and create a predictive nomogram. In this retrospective study, 313 IIM patients treated between March 2014 and March 2024 were randomly divided (6:4 ratio) into development (n = 189) and validation (n = 124) cohorts. Irreversible respiratory failure was characterized by persistent hypoxemia with PaO<sub>2</sub> levels below 60&#xa0;mmHg for more than 1&#xa0;month. Predictive factors were initially screened using LASSO regression, and independent predictors were subsequently identified using multivariate Cox regression. A nomogram was developed using key predictors. Model performance was assessed through time-dependent ROC curves and decision curve analysis (DCA). Multivariate Cox analysis identified multiple independent risk factors for respiratory failure (<i>p</i> &lt; 0.05). The final predictive nomogram incorporated six variables: cough, carcinoembryonic antigen, creatine kinase, lymphocyte count, myositis-specific autoantibodies status, and osteopontin (OPN) level. The model demonstrated excellent discrimination in both cohorts, with time-dependent AUCs of 0.926, 0.934, and 0.935 at 6&#xa0;months, 12&#xa0;months, and 60&#xa0;months in the development group, and 0.942, 0.893, and 0.972 at corresponding time points in the validation group. DCA confirmed the model’s clinical utility. We successfully developed and validated a novel nomogram that integrates essential clinical and laboratory indicators. This tool, incorporating the research biomarker OPN, provides a framework for personalized risk assessment in research settings and may aid future risk stratification strategies pending further validation.</p>

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Preliminary nomogram model for predicting respiratory failure of patients with idiopathic inflammatory myopathies

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月29日

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  • Xiaocong Huo,
  • Yanting Yang,
  • Chengcheng Wei,
  • Xinxiang Huang,
  • Jinying Lin,
  • Yongjun Lin

摘要

To determine the predictors of irreversible respiratory failure in idiopathic inflammatory myopathy-associated interstitial lung disease (IIM-ILD) and create a predictive nomogram. In this retrospective study, 313 IIM patients treated between March 2014 and March 2024 were randomly divided (6:4 ratio) into development (n = 189) and validation (n = 124) cohorts. Irreversible respiratory failure was characterized by persistent hypoxemia with PaO2 levels below 60 mmHg for more than 1 month. Predictive factors were initially screened using LASSO regression, and independent predictors were subsequently identified using multivariate Cox regression. A nomogram was developed using key predictors. Model performance was assessed through time-dependent ROC curves and decision curve analysis (DCA). Multivariate Cox analysis identified multiple independent risk factors for respiratory failure (p < 0.05). The final predictive nomogram incorporated six variables: cough, carcinoembryonic antigen, creatine kinase, lymphocyte count, myositis-specific autoantibodies status, and osteopontin (OPN) level. The model demonstrated excellent discrimination in both cohorts, with time-dependent AUCs of 0.926, 0.934, and 0.935 at 6 months, 12 months, and 60 months in the development group, and 0.942, 0.893, and 0.972 at corresponding time points in the validation group. DCA confirmed the model’s clinical utility. We successfully developed and validated a novel nomogram that integrates essential clinical and laboratory indicators. This tool, incorporating the research biomarker OPN, provides a framework for personalized risk assessment in research settings and may aid future risk stratification strategies pending further validation.