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Risk Factors Analysis of AKI in Patients with Primary Non-small Cell Lung Cancer Treated with PD-1/PD-L1 Inhibitor.
Iranian Journal of Kidney Diseases 2024 March
INTRODUCTION: To investigate the risk factors of Programmed Cell Death Protein 1 (PD-1), Programmed Cell Death Ligand 1(PD-L1) inhibitor associated acute kidney injury (AKI) in patients with primary non-small cell lung cancer (NSCLC) and construct a predictive model.
METHODS: 120 NSCLC patients were selected as the research subjects and their clinical data were collected. Patients were divided into AKI and Non-AKI (N-AKI) group based on the development of AKI. Exploring the risk factors of PD-1P/D-L1 inhibitor related AKI in NSCLC patients using multivariate logistic regression analysis and visualized the logistic regression analysis to obtain a nomogram model. Meanwhile, evaluate the predictive value of the model.
RESULTS: The results of multivariate analysis showed that the presence of extrarenal immune related adverse reactions (irAEs) is a risk factor for PD-1/PD-L1 inhibitor related AKI in NSCLC patients; At the same time, the risk of developing PD-1/PD-L1 inhibitor related AKI in NSCLC patients increases with increasing serum creatinine (SCr) and C-reactive protein (CRP) levels, decreasing baseline estimated glomerular filtration rate (eGFR) levels (P < .05). The analysis results of receiver operator characteristic curve (ROC), calibration curve, and decision curve show that the model has good discrimination and accuracy, and can achieve a high clinical benefit rate.
CONCLUSION: Primary NSCLC patients with extrarenal irAEs, high levels of SCr and CRP, and low levels of eGFR have a higher risk of AKI after PD-1/PD-L1 inhibitor treatment. Establishing a predictive model with high accuracy is more conducive to early detection of high-risk patients. DOI: 10.52547/ijkd.7964.
METHODS: 120 NSCLC patients were selected as the research subjects and their clinical data were collected. Patients were divided into AKI and Non-AKI (N-AKI) group based on the development of AKI. Exploring the risk factors of PD-1P/D-L1 inhibitor related AKI in NSCLC patients using multivariate logistic regression analysis and visualized the logistic regression analysis to obtain a nomogram model. Meanwhile, evaluate the predictive value of the model.
RESULTS: The results of multivariate analysis showed that the presence of extrarenal immune related adverse reactions (irAEs) is a risk factor for PD-1/PD-L1 inhibitor related AKI in NSCLC patients; At the same time, the risk of developing PD-1/PD-L1 inhibitor related AKI in NSCLC patients increases with increasing serum creatinine (SCr) and C-reactive protein (CRP) levels, decreasing baseline estimated glomerular filtration rate (eGFR) levels (P < .05). The analysis results of receiver operator characteristic curve (ROC), calibration curve, and decision curve show that the model has good discrimination and accuracy, and can achieve a high clinical benefit rate.
CONCLUSION: Primary NSCLC patients with extrarenal irAEs, high levels of SCr and CRP, and low levels of eGFR have a higher risk of AKI after PD-1/PD-L1 inhibitor treatment. Establishing a predictive model with high accuracy is more conducive to early detection of high-risk patients. DOI: 10.52547/ijkd.7964.
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