Statistical analysis
The variables gathered from our maintained database were compared
between patients with switching IS drugs and patients without switching
IS drugs. Categorical variables were analyzed using a
χ2 test and were expressed using numbers and
proportion (%). Continuous variables were analyzed using a t-test or a
Wilcoxon signed rank test. Continuous normal distribution was expressed
as mean ± standard deviation and non-continuous normal distribution was
expressed as median and interquartile
(IQR). SPSS (IBM, version 26) and
R (R Foundation for Statistics Computing) were used to perform the
analyses.
Variables that were identified as statistically significantly
(p< 0.05) were selected using the univariate logistic
regression analysis, and were retained as candidate predictors for
prediction modeling. After a stepwise selection process, risk factors
were identified in the
multivariate logistic analysis. Finally, a nomogram was constructed
using these determined risk factors to predict the risk of poor curative
effects of those recipients who receive an IS protocol based on TAC, and
then may switch TAC to CsA. The established nomogram was further
evaluated by using calibration curves. In addition, the discriminative
performance of the nomogram was evaluated using the area under receiver
operating characteristic (ROC) curve (AUC) and the clinical usefulness
of the nomogram was assessed using decision curve analysis (DCA).