4.1.2. Delay of Vaccine Effect T here is evidence, both from the PROSTVAC phase 2 study and other prostate ca ncer trials, as well as trials of therapeutic vaccines in other cancers, that there exists the possibility of a delay in the effect of the experimental vaccine. Taking into account the possibility of a delay in effect precludes using trial size computation methods that assume proportional hazards because the proportional hazards assumption is not valid if there is delayed effect. The existence of a delayed effect means that early deaths will not differentiate between the arms and therefore the number of deaths required for the same power will be greater. Thus, the use of methods that do not take into account delay of effect could lead to underestimating the power of the trial. Simulations were used for both delayed effect scenarios and scenarios where delayed effect was not assumed. Appendix A to this document describes the simulation methodology. Bavarian Nordic, Inc. Statistical Analysis Plan Amendment 1 Protocol: BNIT -PRV -301 Date Issued: 29 June 2015 C onfidential 6 Revised: June 2015 4.1.3. Effect Size for Survival T he hazard ratio in the specific alternative hypotheses used to compute trial size is 0.68, that is, a 32% smaller hazard rate in Arm VG or Arm V as compared to Arm P. This hazard ratio is based on hazard ratio estimates from the previously completed rando mized phase 2 trial with an allowance that the phase 2 trial likely provides an over -optimistic estimate of the true hazard ratio. The hazard ratio estimate from the phase 2 trial was 0.56 when delayed effect is not taken into account, and was approximately 0.5 when delayed effect is taken into account (depending on the quantification of the delayed effect – see next paragraph). Proportional hazards regression with time -dependent covariate implementation of delayed effect was used to obtain estimates of the ultimate hazard ratio following delayed effect in the previously completed randomized phase 2 study. It was found that estimates of this ultimate hazard ratio were reasonably uniform over a range of delayed effect specifications and that having delayed ef fect in the model resulted in a better fit to the survival data than models without delayed effect. The delayed effect estimate of the hazard ratio is approximately 0.5. The shape of the delay of effect used to plan this trial is based on that observed in the phase 2 study, but with an allowance that the phase 2 trial likely provides an over- optimistic estimate of the true hazard ratio. The delay of effect used in the simulations done to plan this trial is based on that observed in the randomized phase 2 s tudy. This delay of effect is characterized as follows: the hazard ratio is initially unity (no effect) for four months, and over the next four months transitions linearly to the hypothesized 0.68. 4.1.4. Power and Significance Level T he trial is planned so that a between -arm logrank test for all subjects will have the target power. The target power taking into account the possibility of a delay in effect is specified to be 85% or greater. The two comparisons will be done with Bonferroni correction to the overall type I error probability so that the type I error probability for each will not exceed one-sided 0.0125 (=0.025/2). 4.1.5. Number of Subjects and Required Number of Deaths T he number of subjects per arm is set to be 400 ( Approximately 1200 total subjects). The accrual rate distribution is 19 months of linear ramp up followed by 11 months of constant rate of accrual (2 .5 years to accrue approximately 1200 subject s). Note: Th e accrual distribution assumptions have been updated from the assumptions used originally to plan this trial and are based on current accrual experience. The table below has been revised to reflect these new accrual assumptions and there is no material modif ication to power, hypothesized hazard ratio, or any other important aspect of the trial design. As expected, t he revised computations do change the projections for time to analysis. The assumptions used in Table 1 matc h the assumptions used in the interim analysis plan ning computations outlined on pages 23 and 24. Please see Appendix B for more detail around the 19 month linear ramp followed by 11 months constant rate of accrual. Bavarian Nordic, Inc. Statistical Analysis Plan Amendment 1 Protocol: BNIT -PRV -301 Date Issued: 29 June 2015 C onfidential 7 Revised: June 2015 The trial is planned as an event driven trial. Simulation is used to compute the required number of deaths after setting other specifications.