Wsrtjtyk

I'd like to calculate the expected risk (cumulative incidences), which are derived from a fitted Cox PH model using R packages.

I have the fitted Cox PH model like as follows:

##[Variables]##

# **Dataset: 10,000 cases(patients) with 6 variabels



# t: time to event, s: event (coded as 0 or 1)

# covariates: X1, X2, X3, X4 (coded as 0 or 1)



fit <- coxph(Surv (t,s) ~ X1 + X2 + X3 + X4, data = data)



summary (fit)



#          coef   exp(coef)  se (coef)   z     P         

#    X1   -0.3777    0.6855   0.1120   -3.37    0.00075

#    X2    0.4014    1.4938   0.0518    7.74   <0.0001

#    X3    0.7417    2.0995   0.0893    8.31   <0.0001

#    X4    0.4330    1.5419   0.1268    3.42   <0.001 

From this model, I'd like to calculate the expected risk (cumulative incidence of events) for each case according to X1 = 0 or X1 = 1.

In other words, if the X1 of all 10,000 cases were 0, how could I calculate the expected risk for each case? At the same time, if the X1 of all 10,000 cases were 1, how could I calculate the expected risk for each case? (using R)

After calculating the expected risk for each patient, then I'd like to calculate the risk-benefit ratio for each patient according to variable X1 [by (Expected risk, when X1 = 0) - (Expected risk, when X1 = 1)], does it right?

Meanwhile, I have tried to plot the expected cumulative risk curve according to X1 like as follows; was it appropriate?

baseha = basehaz(fit, centered=FALSE)



# X1=0: exp (-0.38*0) = 1, X1=1: exp (-0.38*1) = 0.68



plot(baseha$$time[,2], baseha$hazard*(1), type="s", lty=1)

lines(baseha$$time[,2], baseha$hazard*(0.68), type="s", lty=2)

Thanks for your kind answers.