Two-sample comparison of survival times with "cured patients" is of major interest and a challenging issue in many areas, particularly in cancer clinical research. Recently, several authors have proposed various procedures of comparison, including tests of no overall, no short-term and no long-term differences between two samples. In clinical practice, it is often of interest to detect the difference in treatment effects among noncured patients regardless of the difference between cure fractions. In this paper, we propose a statistical test to compare two samples with cured patients and possibly heterogeneous treatment effects based on a class of semi-parametric transformation models, and our main focus is on the survival times of noncured patients. The empirical and quantile processes are used to construct strong approximations for the empirical curves. The two-sample test is then constructed from general least squares estimators derived from these processes. Simulation results show that the proposed test perform well. As an example of application, a set of bladder cancer data is analyzed to illustrate the proposed methods.