I am looking to fit a Cox proportional hazards survival model.  Looking at the K-M curve (below) for one variable (with 2 categories) it appears there is a change in hazard ratios at around day 110.  I was thinking of modeling this with a changepoint model.

![KM-Curve][1]


  [1]: https://i.sstatic.net/xZBjJ.png

I'm having trouble implementing it.  I have defined days_ind as 1 if days>=110 and 0 otherwise.  Then I run the model:

coxph(Surv(time=days,event=event2)~x*days_ind)

I get several warning messages about convergence and the results don't seem to make any sense.

Am I approaching this in the correct way?  I thought of bringing in the interaction of factor(x)*days instead but this too does not converge and also leads to strange estimates.