library(openxlsx) 
library(ggplot2)
library(tidyverse)
library(MASS)#有序polr函数
library(nnet)#无序多分类multinom函数
library(brant)#检验有序logistic回归平行性
library(rms)#列线图

igadata1 <- read_xlsx("C:/Users/99405/Desktop/igar.xlsx")
igadata1$Lee氏分级合并<-factor(igadata1$Lee氏分级合并,levels=c(2,3,4))
igadata1$性别<-factor(igadata1$性别,levels=c(0,1))
igadata1$高血压<-factor(igadata1$高血压,levels=c(0,1))
igadata1$E内皮细胞<-factor(igadata1$E内皮细胞,levels=c(0,1))
igadata1$蛋白质<-factor(igadata1$蛋白质,levels=c(0,0.5,1,2,3))
igadata1$贫血四分类<-factor(igadata1$贫血四分类,levels=c(0,1,2,3))
igadata1$红细胞<-as.numeric(igadata1$红细胞)
igadata1$隐血<-factor(igadata1$隐血,levels=c(0,0.5,1,2,2.5,3))

#二分类logistic回归
model <- glm(E内皮细胞~ 贫血四分类+高血压+蛋白质+尿蛋白定量+肌酐+总蛋白+白蛋白, data = igadata1, family = "binomial")
#无序多分类logistic回归
model1 <- multinom(Lee氏分级合并~ 贫血四分类+高血压+蛋白质+尿蛋白定量+肌酐+总蛋白+白蛋白,data=igadata1)
model1
#有序多分类logistic回归
model <- polr(Lee氏分级合并~ 贫血四分类+高血压+蛋白质+尿蛋白定量+肌酐+总蛋白+白蛋白,data=igadata1)
brant(model)#平行性检验



#列线图
#二分类
  dd<-datadist(igadata1)
  options(datadist="dd")
  formula1<-as.formula(E内皮细胞~ 贫血四分类+隐血+红细胞+尿蛋白定量+尿素+肌酐+总蛋白+白蛋白)
  fit1<-lrm(formula1,data =igadata1,x=T,y=T)
  fun1=function(x)1/(1+exp(-x))
  g <- nomogram(fit1,fun=list('E内皮细胞增生'=fun1),fun.at = c(0.1,0.5,0.9),lp=F)
  plot(g)
  fit1
#有序
  dd<-datadist(igadata1)
  options(datadist="dd")
  formula1<-as.formula(Lee氏分级合并~ 贫血四分类+性别+年龄+高血压+尿蛋白定量+肌酐+总蛋白+白蛋白)
  fit1<-lrm(formula1,data =igadata1,x=T,y=T)
  fun1 <- function(x) plogis(x-fit1$coef[1]+fit1$coef[1])
  fun2 <- function(x) plogis(x-fit1$coef[1]+fit1$coef[2])
  g <- nomogram(fit1,fun=list('Lee氏等级3'=fun1,'Lee氏等级4'=fun2),fun.at = c(0.1,0.5,0.9),lp=F)
  plot(g)
  fit1
  dd<-datadist(igadata1)
  options(datadist="dd")
  formula1<-as.formula(T肾小管萎缩~ 贫血四分类+高血压+红细胞+尿蛋白定量+尿素+肌酐+总蛋白+白蛋白)
  fit1<-lrm(formula1,data =igadata1,x=T,y=T)
  fun1 <- function(x) plogis(x-fit1$coef[1]+fit1$coef[1])
  fun2 <- function(x) plogis(x-fit1$coef[1]+fit1$coef[2])
  g <- nomogram(fit1,fun=list('肾小管萎缩25%-50%'=fun1,'肾小管萎缩>75%'=fun2),fun.at = c(0.1,0.5,0.9),lp=F)
  plot(g)