Objective To explore the risk factors for renal injury in tumors patients treated with programmed death receptor-1 (PD-1) inhibitor, and further construct a column chart model to predict the likelihood of renal injury in patients. Methods The present study is a single center retrospective analysis. 447 patients with tumors treated with PD-1 inhibitors in the Third Affiliated Hospital of Soochow University between January 2018 and January 2021 were included and followed up until January 2022. Kidney injury was defined as acute kidney disease (AKD). All patients were divided into AKD group (n=71) and non-AKD group (n=376 according to whether PD-1 inhibitor associated with AKD development at the end of follow-up. Basic information, disease and medication situation, laboratory indicators, and the incidence of extrarenal immune related adverse events (irAEs) during follow-up period were compared between the two groups. Univariate and multivariate logistic regression models were used to identify independent risk factors for PD-1 inhibitor associated AKD. The present study randomly divided all samples (n=447) into training set (n=313) and validation set (n=134) in a 7:3 ratio, built nomogram prediction models in the training set according to the screened independent risk factors, drawn the receiver operating characteristic (ROC) curves to evaluate the discrimination of the models, drawn calibration curves to evaluate the calibration of the models, and drawn clinical decision curve analysis (DCA) to explore the clinical validity and benefit rate of the models. Results The combination of antibiotics, diabetes, hypertension, extrarenal irAEs and cystatin C (Cys C) in AKD group were significantly higher than those in non-AKD group (P<0.05), but hemoglobin (Hb) was significantly lower than that in non-AKD group (P<0.05). Single factor logistic regression analysis showed that combination of antibiotics, diabetes, hypertension, extrarenal irAEs, lower Hb, estimated glomerular filtration rate (eGFR), higher blood urea nitrogen (BUN), serum creatinine (SCr), Cys C, fasting blood glucose (FBG), and alanine transaminase (ALT) were risk factors for PD-1 inhibitor related AKD (P<0.05). Multivariate logistic regression analysis showed that concomitant extrarenal irAEs, lower Hb, higher SCr, and direct bilirubin (DBIL) were independent risk factors for PD-1 inhibitor associated AKD (P<0.05). Based on the independent risk factors mentioned above, a column chart prediction model was further established and validated. The results showed that the area under the ROC curve (AUC) of the training and validation sets of the model were 0.703 (95%CI 0.628-0.777) and 0.791 (95%CI 0.671-0.911), respectively, indicating good discrimination. The calibration curves of both the training and validation sets hover around the ideal line of 45°, indicating that the model has good calibration. DCA shows that the constructed model curve is far away from the two polar lines (the curve with a net benefit of 0 and the curve with all samples being positive), indicating that the model has good clinical benefits. Conclusion The combination of extrarenal irAEs, lower Hb, higher SCr, and higher DBIL are independent risk factors for the occurrence of PD-1 inhibitor related AKD; The established column chart model has good discrimination and calibration, which can provide guidance for clinical practice.