# How important is it to transform variable for Cox Proportional Hazards?

I am building a Cox PH model for recurrence-free survival from breast cancer. One of my variables, the number of involved lymph nodes, is highly skewed with many more "0" values than positive integers. It seems to me that this would make any transformation ineffective because this variable cannot be negative. Here is a stem plot of the lymph node data:

 0 | 00000000000000000000000000000000000000000000000000000000000000000000+195
2 | 00000000000000000000000000000000000000000000000000
4 | 00000000000000000000000000000
6 | 000000000000000
8 | 000000000000
10 | 0000000000
12 | 00000
14 | 0000
16 | 0
18 |
20 | 0
22 |
24 | 00
26 | 0
28 | 0
30 |
32 | 0


A log(X+1) transformation doesn't do anything to normalize the data because there is no data less than 0. How important is it to transform this variable? Would using only values <20 and log-transforming them help more? This must be a common problem; are there any creative solutions to it?