Risk factors and nomogram prediction model for checkpoint inhibitor-related pneumonitis in patients with advanced non-small cell lung cancer.
1/5 보강
PICO 자동 추출 (휴리스틱, conf 2/4)
유사 논문P · Population 대상 환자/모집단
환자: advanced NSCLC treated with ICIs between January 2021 and December 2024
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
Subgroup analyses showed consistent associations across immune checkpoint inhibitor types and treatment lines. [CONCLUSION] The developed nomogram, incorporating key clinical and psychological predictors, offers a practical tool for individualized risk assessment of CIP in advanced NSCLC patients, potentially guiding early intervention and improving immunotherapy safety.
[BACKGROUND] Immune checkpoint inhibitors have improved outcomes in advanced non-small cell lung cancer (NSCLC) but are associated with immune-related adverse events such as pneumonitis.
- 95% CI 1.20-2.31
APA
Chen YF, Tian J, et al. (2026). Risk factors and nomogram prediction model for checkpoint inhibitor-related pneumonitis in patients with advanced non-small cell lung cancer.. Frontiers in medicine, 13, 1742594. https://doi.org/10.3389/fmed.2026.1742594
MLA
Chen YF, et al.. "Risk factors and nomogram prediction model for checkpoint inhibitor-related pneumonitis in patients with advanced non-small cell lung cancer.." Frontiers in medicine, vol. 13, 2026, pp. 1742594.
PMID
41958570 ↗
Abstract 한글 요약
[BACKGROUND] Immune checkpoint inhibitors have improved outcomes in advanced non-small cell lung cancer (NSCLC) but are associated with immune-related adverse events such as pneumonitis. This study aimed to identify risk factors for checkpoint inhibitor-related pneumonitis (CIP) and to develop a predictive nomogram for individualized risk assessment in advanced NSCLC patients.
[METHODS] This retrospective study included consecutive patients with advanced NSCLC treated with ICIs between January 2021 and December 2024. All patients who developed CIP were included as cases ( = 96), and non-CIP controls were selected from the source population using propensity score matching ( = 191). CIP was diagnosed using a standardized adjudication process with systematic exclusion of infectious, malignant, radiation-related, and cardiogenic etiologies. Multivariate logistic regression was performed to identify independent predictors, and a nomogram was constructed. Model performance was evaluated using receiver operating characteristic analysis, calibration curves, bootstrap internal validation, and decision curve analysis.
[RESULTS] Disease duration (OR 1.66, 95% CI 1.20-2.31), smoking history (OR 3.32, 95% CI 1.34-8.26), prior chest radiotherapy (OR 2.75, 95% CI 1.09-6.92), and baseline Hamilton Anxiety Rating Scale score (OR 1.12 per point, 95% CI 1.04-1.21) were independent predictors of CIP. The nomogram demonstrated good discrimination (AUC 0.819, 95% CI 0.752-0.891) and calibration, with a bootstrap-corrected C-index of 0.751. Subgroup analyses showed consistent associations across immune checkpoint inhibitor types and treatment lines.
[CONCLUSION] The developed nomogram, incorporating key clinical and psychological predictors, offers a practical tool for individualized risk assessment of CIP in advanced NSCLC patients, potentially guiding early intervention and improving immunotherapy safety.
[METHODS] This retrospective study included consecutive patients with advanced NSCLC treated with ICIs between January 2021 and December 2024. All patients who developed CIP were included as cases ( = 96), and non-CIP controls were selected from the source population using propensity score matching ( = 191). CIP was diagnosed using a standardized adjudication process with systematic exclusion of infectious, malignant, radiation-related, and cardiogenic etiologies. Multivariate logistic regression was performed to identify independent predictors, and a nomogram was constructed. Model performance was evaluated using receiver operating characteristic analysis, calibration curves, bootstrap internal validation, and decision curve analysis.
[RESULTS] Disease duration (OR 1.66, 95% CI 1.20-2.31), smoking history (OR 3.32, 95% CI 1.34-8.26), prior chest radiotherapy (OR 2.75, 95% CI 1.09-6.92), and baseline Hamilton Anxiety Rating Scale score (OR 1.12 per point, 95% CI 1.04-1.21) were independent predictors of CIP. The nomogram demonstrated good discrimination (AUC 0.819, 95% CI 0.752-0.891) and calibration, with a bootstrap-corrected C-index of 0.751. Subgroup analyses showed consistent associations across immune checkpoint inhibitor types and treatment lines.
[CONCLUSION] The developed nomogram, incorporating key clinical and psychological predictors, offers a practical tool for individualized risk assessment of CIP in advanced NSCLC patients, potentially guiding early intervention and improving immunotherapy safety.
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