Influencing factors of IgA nephropathy combined with hyperuricemia and a nomogram to predict the risk of hyperuricemia in IgA nephropathy patients - Zhou Jie; Xian Wei-ying; Li Ji-tian; Zeng Jin-cheng (Linchuang shenzangbing zazhi)
ObjectiveTo investigate the factors influencing the complication of hyperuricemia （HUA） in patients with immunoglobulin A nephropathy （IgAN） and to construct a nomogram to predict it.MethodsFrom December 1， 2020 to December 1， 2023， 332 IgAN patients admitted to Shenzhen University General Hospital were regarded as the observation subjects. They were randomly grouped into a modeling group （233 cases） and a validation group （99 cases） at a ratio of 7∶3 using a random number table method. According to the presence of HUA， patients in the modeling group were assigned into HUA group and non-HUA group. Multivariate logistic regression was applied to analyze the risk factors for HUA in IgAN patients. R software was applied to construct a nomogram to predict the occurrence of HUA in IgAN patients. The receiver operating characteristic （ROC） curve was plotted to evaluate the discriminability of the nomogram in predicting HUA in IgAN patients. Calibration curves were plotted to assess the consistency of the nomogram. The value of the clinical application of the model was assessed using clinical decision curve analysis （DCA）.ResultsHUA occurred in 79 out of 233 IgAN patients in the modelling group， with an incidence rate of 33.91%. There were significant differences in the male proportion （65.82% vs 47.40%）， body mass index ［BMI， （24.67 ± 4.52）kg/m2 vs （22.28 ± 3.17）kg/m2］， hypertension （43.04% vs 23.38%）， triglyceride ［TG， （2.16 ± 0.61）mmol/L vs （1.72 ± 0.30）mmol/L］， white blood cell count ［WBC， （7.28 ± 2.06）×109L vs （5.75 ± 1.52）×109L］， estimated glomerular filtration rate ［eGFR，（66.93 ± 19.85）mL·min-1·（1.73 m2）-1 vs （86.42 ± 22.37）mL·min-1·（1.73 m2）-1］ and IgA/C3 ［（3.07 ± 0.96） vs （2.35 ± 0.62）］ between HUA group and non-HUA group （P<0.05）. Multivariate logistic regression analysis showed that male gender （OR=6.147， 95%CI： 2.303-16.411）， BMI （OR=4.201， 95%CI： 2.740-6.440）， hypertension （OR=12.935， 95%CI： 3.589-46.615）， TG （OR=3.057， 95%CI： 1.097-8.521）， WBC （OR=4.876， 95%CI： 2.500-9.510）， and IgA/C3 （OR=2.657， 95%CI： 1.473-4.793） were the risk factors for the development of HUA in patients with IgAN （P<0.05）， and eGFR （OR=0.547， 95 %CI： 0.303-0.987） was a protective factor （P<0.05）. The area under curve （AUC） of the ROC curve in the modelling group was 0.912 （95%CI： 0.872-0.952）， and the slope of the calibration curve was close to 1. The H-L test showed a chi-square statistic （χ2） of 6.579 （P=0.654）， with good agreement. The internal validation AUC was 0.913 （95%CI： 0.855-0.971）， the slope of the calibration curve was close to 1， and the H-L test showed χ2 of 6.486 （P=0.723）， with good agreement. DCA curve showed the high risk threshold of 0.04 to 0.84， suggesting that the nomogram had a high clinical use value in predicting the occurrence of HUA in IgAN patients.ConclusionMale， BMI， hypertension， TG， WBC， and IgA/C3 are risk factors for HUA in IgAN patients， and eGFR is a protective factor. The nomogram constructed based on the above factors has good discrimination and consistency， and it can predict the risk of HUA in IgAN patients， and guide the interventions earlier to reduce the risk of HUA.