Cox model convergence

Then I perform cox regression as follows
m2_1<-coxph(Surv(X_t0,X_t, vlsupp) ~ nvp  + as.factor(cd4pccat) +
as.factor(vlcat) + as.factor(agecat) + as.factor(whostage)  +
as.factor(hfacat) + as.factor(wfacat) + as.factor(wfhcat) +
as.factor(resistance) + as.factor(postrantb) +
cluster(id),data=myimp$imputations[[1]],method="breslow",robust=TRUE)
summary(m2_1)
The I get the following eWarning message:
In fitter(X, Y, strats, offset, init, control, weights = weights,  :
   Ran out of iterations and did not converge

Failure to converge is highly unusual for coxph unless the model is near singular.  A good 
rule for Cox models is to have 10-20 events for each coefficient.   When models get below 
2 events/coef the results can be unreliable, both numerically and biologically, and some 
version of a shrinkage model is called for.  What are the counts for your data set?

A vector of inital values, if supplied, needs to be of the same length as the 
coefficients.  Make it the same length and in the same order as the printed coefficients 
from your run that did not converge.

Terry Therneau