  In confirmatory cancer clinical trials, overall survival (OS) is normally a
primary endpoint in the intention-to-treat (ITT) analysis under regulatory
standards. After the tumor progresses, it is common that patients allocated to
the control group switch to the experimental treatment, or another drug in the
same class. Such treatment switching may dilute the relative efficacy of the
new drug compared to the control group, leading to lower statistical power. It
would be possible to decrease the estimation bias by shortening the follow-up
period but this may lead to a loss of information and power. Instead we propose
a modified weighted log-rank test (mWLR) that aims at balancing these factors
by down-weighting events occurring when many patients have switched treatment.
  As the weighting should be pre-specified and the impact of treatment
switching is unknown, we predict the hazard ratio function and use it to
compute the weights of the mWLR. The method may incorporate information from
previous trials regarding the potential hazard ratio function over time.
  We are motivated by the RECORD-1 trial of everolimus against placebo in
patients with metastatic renal-cell carcinoma where almost 80\% of the patients
in the placebo group received everolimus after disease progression. Extensive
simulations show that the new test gives considerably higher efficiency than
the standard log-rank test in realistic scenarios.

Methodology