Abstract
PURPOSE: The administration of immune checkpoint inhibitors (ICIs) may lead to renal adverse events, notably including renal dysfunction. To early predict the probability of renal dysfunction after ICIs therapy, a retrospective case-control study was conducted. METHODS: Clinical information on ICIs-treated patients was collected. Multivariable logistic regression was applied to identify risk factors for renal dysfunction after ICIs treatment. Moreover, a nomogram model was developed and validated internally. RESULTS: A total of 442 patients were included, among which 35 (7.9%) experienced renal dysfunction after ICIs treatment. Lower baseline estimated glomerular filtration rate (eGFR) (OR 0.941; 95% CI 0.917 to 0.966; p<0.001), concurrent exposure of platinum(OR 4.014; 95% CI 1.557 to 10.346; p=0.004), comorbidities of hypertension (OR 3.478; 95% CI 1.600 to 7.562; p=0.002) and infection (OR 5.402; 95% CI 1.544 to 18.904; p=0.008) were found to be independent associated with renal dysfunction after ICIs treatment. To develop a predictive nomogram for the occurrence of renal dysfunction after ICIs treatment, the included cases were divided into training and validation groups in a ratio of 7:3 randomly. The above four independent risk factors were included in the model. The area under the receiver operating characteristic curves of the predictiive model were 0.822 (0.723-0.922) and 0.815 (0.699-0.930) in the training and validation groups, respectively. CONCLUSIONS: Lower baseline eGFR, platinum exposure, comorbidities of hypertension and infection were predictors of renal dysfunction in ICIs-treated patients with cancer. A nomogram was developed to predict the probability of renal dysfunction after ICIs treatment, which might be operable and valuable in clinical practice.