Risk prediction of the progression of chronic kidney disease stage 1 based on peripheral blood samples: construction and internal validation of a nomogram

Patients with chronic kidney disease (CKD) have high morbidity and mortality, and the disease progression has a significant impact on their survival and living standards.This research aims to analyze risk factors for CKD stage 1 and provide a reference for clinical decision making.The clinical data and peripheral blood samples of 300 patients with CKD stage 1 were collected retrospectively.Patients were randomly assigned into a training set (n = 210) and a validation set (n = 90).Patients' baseline characteristic levels were subjected to statistical tests for difference.Univariate and multivariate Cox regression analyses were utilized to identify risk factors influencing disease progression.Subsequently, a prediction model for disease progression was developed using a nomogram, and the model's accuracy was assessed using the C-index and calibration curve.The results revealed that hypertension, diabetes, and urinary albumin were essential factors in the progression of CKD stage 1.The nomogram was constructed and then the C-index was calculated.The calibration curve was utilized to assess the risk model.The C-index of the training set was 0.75, and the C-index of the validation set was 0.73, suggesting a good predictive ability of the model.The risk model accurately predicted the progression of CKD stage 1, which is of great significance to developing personalized treatment for patients in clinical practice.