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Background: Immune‐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. Methods: The 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. Results: The 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. Conclusions: We 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. [ABSTRACT FROM AUTHOR]

Background and Aims: Immune-mediated liver injury is a fatal side effect of sintilimab. This study aimed to shed light on the associated risk factors and characteristics of this adverse event., Methods: The clinical records of 772 patients treated with sintilimab were retrospectively reviewed to investigate risk factors associated with sintilimab immune-related hepatotoxicity, as well as its incidence and outcome. The Roussel Uclaf Causality Assessment Method was used to identify cases of sintilimab-induced hepatotoxicity. Furthermore, logistic regressions were performed to compare the clinical and bloodwork characteristics of patients with and without immune-mediated liver injury caused by checkpoint inhibitors., Results: Of the 585 patients included in the study, 71 (12.1%) developed liver injury during sintilimab use. The median RUCAM score with interquartile range was 7 (6, 8). Hypoproteinemia, dyslipidemia, and the presence of thyroid peroxidase antibodies were risk factors for sintilimab-related hepatotoxicity. A nomogram model was constructed for sintilimab-induced immune-mediated liver injury based on these risk factors, which had a C-index value of 0.713 and a good calibration curve. When applied to patients with grade ≥3 and ≥4 sintilimab-induced immune-mediated liver injury, it achieved C-index values of 0.752 and 0.811, respectively. The nomogram model also showed a good prediction potential in patients ≥65 years and males. Six of the patients with sintilimab-related hepatotoxicity showed improved liver function upon treatment with steroids., Conclusions: This study demonstrated that hypoproteinemia, dyslipidemia, and the presence of thyroid peroxidase antibodies were clinically feasible prognostic biomarkers to predict liver injury in patients treated with sintilimab., Competing Interests: The authors have no conflict of interests related to this publication., (© 2023 Authors.)