Appendix A to this document describes the simulation methodology. Table 1 below shows the results of the simulations. Table 1: Simulation Results Case # Delayed Effect Specified # deaths Time to specified deaths (y) 1-sided type I error probability estimate (%) Power estimate (%) Critical hazard ratio 1 No 340 3.4 1.17 90.2 0.784 2 Yes 340 3.3 1.13 44.5 0.784 3 Yes 534 5.1 1.23 86.1 0.823 4 No 534 5.2 1.12 98.8 0.823 Notes: •Simulations are for the comparison of one of the experimental arms to control arm, that is, 800 subjects, 400 per arm, accrued over two years, with a 19 month ramp time followed by a constant accrual rate for 11 months (2.5 year total accrual) . •10,000 replications for each case. •Significance level is one-sided 0.0125. The column “One-sided type I error probability estimate (%)” from the simulations should be approximately 1.25%. Target power with delayed effect is 85% or more. •The control arm data are g enerated under the exponential distribution with 22 month median survival. •The experimental arm data under the specific alternative and when delayed effect (if applicable ) are generated so that hazard rates are equal for 4 months (hazard ratio = 1), follow ed by a linear transition over next 4 months to target hazard ratio of 0.68, with hazard ratio = 0.68 from 8 months onward. •The estimated type I error and power are the percent rejection of the nullhypothesis when the data are simulated under the null or specific alternative hypotheses, respectively. The estimated type I error probabilities in the table aresufficiently close to 1.25% considering they are estimated from simulations. •The “C ritical hazard ratio ” is the maximum hazard ratio that resulted in rejection of the null. This is an estimate of the threshold of significance. At the end of the trial larger hazard ratios will not result in rejection of the null hypothesis. Case # 1 simulates a trial without delayed effect and a target power of 90% or greater and corresponds to conventional (proportional hazards) trial sizing computations, where the usual formula computed a requirement for 340 deaths. Case # 2 is based on the required number of deaths computed for Case # 1 (340) but with the data in the s imulations generated under the specified delayed effect. The power for an analysis at 3 40 deaths when the specified delayed effect is applicable is not sufficient ( 44.5%). Note that 3 40 deaths are realized sooner than for Case # 2 than Case # 1 because the experimental arm will have a higher early hazard rate in Case # 2 than in Case # 1. Bavarian Nordic, Inc. Statistical Analysis Plan Amendment 1 Protocol: BNIT -PRV -301 Date Issued: 29 June 2015 C onfidential 8 Revised: June 2015 Case # 3 represents a solution to the required number of deaths for a target power of 85% or more under the delayed effect specified. The number of deaths required is found to be 534, with time to realization of 5 34 deaths projected to be 5.1 years. Case # 4 illustrates the estimated power of a trial with 5 34 deaths at the final analysis but without delayed effect. The high power (98.8) is the result of early events bei ng differentiating. Thus, these simulations show that a final analysis at 5 34 deaths provides protection against unacceptable loss of power if the projected delayed effect is applicable, and yet assures that the type I error probability is protected. The t rial’s power will be 85% or greater if the delayed effect does not exceed that specified in the simulations. 4.2. Randomization, Stratification, and Blinding B lock randomization will be used to randomly assign subjects in a 1:1:1 manner. Randomization will be stratified according to the following two factors, PSA (equal and above or below 50 ng/ml) and LDH (equal and above or below 200 U/L). These two stratification factors will be used to create a four -level categorical stratification variable for the followi ng combinations of the stratification factors: (PSA < 50 & LDH < 200), (PSA < 50 & LDH ≥ 200), (PSA ≥ 50 & LDH < 200), and (PSA ≥ 50 & LDH ≥ 200). This stratification variable will be used to stratify analyses as specified subsequently. U nblinding will be performed only in the event of a medical emergency in which the Investigator determines that knowledge of the subject’s treatment assignment is necessary for effective treatment. If unblinding is required, the Investigator must contact t he Medical Monitor or designee who will record who requested the unblinding, for what purpose, and for which subject, and will notify the DMC in a timely manner. 4.3.