nomogram

Nomogram is a graphical calculating device, a two-dimensional diagram designed to allow the approximate graphical computation of a function (wiki).

We can make nomogram using "rms" package.

I executed example(nomogram) and result is below.

This result obtained by logistic analysis.

library(rms)

set.seed(17)				# so can reproduce the results
n              <- 1000			# define sample size
age            <- rnorm(n, 50, 10)
blood.pressure <- rnorm(n, 120, 15)
cholesterol    <- rnorm(n, 200, 25)
sex            <- factor(sample(c('female','male'), n,TRUE))

L     <- .4*(sex=='male') + .045*(age-50) + (log(cholesterol - 10)-5.2)*(-2*(sex=='female') + 2*(sex=='male'))
y     <- ifelse(runif(n) < plogis(L), 1, 0)
ddist <- datadist(age, blood.pressure, cholesterol, sex)
options(datadist='ddist')


f   <- lrm(y ~ lsp(age,50)+sex*rcs(cholesterol,4)+blood.pressure)
nom <- nomogram(f, 
	fun      = function(x)1/(1+exp(-x)), 
	fun.at   = c(.001,.01,.05,seq(.1,.9,by=.1),.95,.99,.999), 
	funlabel = "Risk of Death")
plot(nom, xfrac=.45)
print(nom)

Japanese nomogram of prostate cancer is below.

http://www.tmd.ac.jp/med/uro/practice/cure/nomogram.html

And survplot function is useful to visualize survival analysis.

cens      <- 15*runif(n)
h         <- .02*exp(.04*(age-50)+.8*(sex=='female'))
dt        <- -log(runif(n))/h
label(dt) <- 'Follow-up Time'
e         <- ifelse(dt <= cens,1,0)
dt        <- pmin(dt, cens)
units(dt) <- "Year"
dd        <- datadist(age, sex)
options(datadist='dd')

S <- Surv(dt,e)
f <- cph(S ~ pol(age,2)*strat(sex), x=TRUE, y=TRUE)
survplot(f, sex=., n.risk=TRUE)
survplot(f, sex=., logt=TRUE, loglog=TRUE)

f <- survfit(S ~ sex)
survplot(f)