ArticleCancer medicine2024
Development and validation of a nomogram for predicting immune-related pneumonitis after sintilimab treatment.
Article in Cancer medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.
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Who cites it
4 citing papers in PubMed, 2 syntheses or guidelines pooled it, 4 citations in OpenAlex.
- Predictive value of machine learning for radiation pneumonitis and checkpoint inhibitor pneumonitis in lung cancer patients: a systematic review and meta-analysis.Scientific reports · 2025Pooled it
- Risk factors for checkpoint inhibitor pneumonitis in lung cancer patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis.Frontiers in immunology · 2025Pooled it
- A multidimensional investigation of myelosuppression associated with sintilimab: integrating pharmacovigilance signal mining with real-world clinical evidence.Frontiers in pharmacology · 2026Article
- Development and validation of a nomogram for predicting immune-related pneumonitis after sintilimab treatment.Cancer medicine · 2024Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundImmune-related pneumonitis is a rare and potentially fatal adverse event associated with sintilimab. We aimed to develop and validate a nomogram for predicting the risk of immune-related pneumonitis in patients treated with sintilimab.
methodsThe least absolute shrinkage and selection operator (LASSO) regression was used to determine risk factors. Multivariable logistic regression was used to establish a prediction model. Its clinical validity was evaluated using calibration, discrimination, decision, and clinical impact curves. Internal validation was performed against the validation set and complete dataset.
resultsThe study included 632 patients; 59 were diagnosed with immune-related pneumonitis. LASSO regression analysis identified that the risk factors for immune-related pneumonitis were pulmonary metastases (odds ratio [OR], 4.015; 95% confidence interval [CI]: 1.725-9.340) and metastases at >3 sites (OR, 2.687; 95% CI: 1.151-6.269). The use of combined antibiotics (OR, 0.247; 95% CI: 0.083-0.738) and proton pump inhibitors (OR, 0.420; 95% CI: 0.211-0.837) were protective factors. The decision and clinical impact curves showed that the nomogram had clinical value for patients treated with sintilimab.
conclusionsWe have developed and validated a practical nomogram model of sintilimab-associated immune-related pneumonitis, which provides clinical value for determining the risk of immune-related pneumonitis and facilitating the safe administration of sintilimab therapy.
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