Bavarian Nordic, Inc. Statistical Analysis Plan Amendment 1 Protocol: BNIT -PRV -301 Date Issued: 29 June 2015 C onfidential 17 Revised: June 2015 8.5.1. HLA- A2 Status P ositive HLA -A2 status is defined by a positive serological response to a HLA -A2-specific antibody. The previously completed phase 2 found that HLA- A2 positive subjects had a larger effect size than did HLA -A2 negative subjects. This finding will be confirmed in this study through an effect modification analysis in the primary model (including stratification). The primary proportional hazard regression model will be re-analyzed with the addition of HLA- A2 status (positive vs. negative) and HLA- A2 status by treatment interaction terms. The criterion for significant effect modification will be a P value of 0.1 or less for the coefficient of the HLA- A2 status by treatment interaction term. If there is significant effect modification then the hazard ratios specific to negative and positive HLA -A2 status will be estimated along with additional supporting analyses such as Kaplan -Meier estimate graphs. 8.5.2. Absence of Progression at 12 Months T o model the likelihood of remaining radiologically event-free at 12 months as compared to scans at 6 months is of interest. Subjects may become secondarily stable, allowing for time for the vaccine to induce an immune response, and then establish a new baseline at 6 months. The between -arm comparison of this outcome is not a comparison free of the confounding of post- randomization events that have the potential of being arm-dependent. Regression modeling of being free of progression, which is AWE at 12 months, with covariates for baseline prognostic factors and AWE at 6 months, will be conducted. 8.5.3. Post-Progression Anti -Cancer Therapies B ecause the primary endpoint is survival and subjects can have access to other anticancer therapies following progression there is the possibility that post-progression anticanc er therapies (PPACTs) could provide an alternative explanation for any observed survival differences. Analyses for assessing the possibility of PPACT effects are necessarily open -ended because the challenge is to find an alternative explanation for an observed outcome from a pre-planned analysis. Thus, such analyses are necessarily data -directed because they are challenge analyses, leaving the assessment of meaning in the context of being data-directed and the multiplicity of analyses to be assessed through consideration of clinical and biological considerations. T he following classes of analyses are anticipated at this time: •Compare the Kaplan -Meier estimates from each arm to the Kaplan -Meier estimate where subjects are censored at the time of initiation o f a PPACT. •Model the use of PPACTs as time-dependent covariates added to the primary survival models (FAS, arms as randomized). In addition, baseline covariates of prognostic importance will be added to these models in order to attempt adjustment for progn osis factors in the selection of subjects getting PPACTs (confounding between subjectattributes and selection for PPACTs). Bavarian Nordic, Inc. Statistical Analysis Plan Amendment 1 Protocol: BNIT -PRV -301 Date Issued: 29 June 2015 C onfidential 18 Revised: June 2015 8.5.4. Immune Responses P ROSTVAC has been found to induce various immune responses. The arms will be compared with respect to previously identified immune responses and other immune responses that may not have been previously identified. The prognostic value of immune responses will be assessed. 8.5.5. Circulating Tumor Cells T echnology for assessing for CTCs has become more available and reliable, however limited information exists on CTC counts in the target population. Modeling will be used to assess the prognostic value of baseline CTC measures and other prognostic measures on outcome. 8.5.6. Tumor Regression and Growth Rate T umor regression and grow th rates will be derived for each subject with sufficient PSA data per the method described in Stein, et al, 2010. Linear regressions to evaluate the relationship between the growth rate constant, g, or other parameters and survival will be performed. Regression rate constants, d, and growth rate constants, g, will be presented in the data listings for each subject. 8.5.7. Overall Prognostic Model A dditional data -driven analyses may be performed at the discretion of the sponsor. The tertiary objectives above focus on specific classes of factors that are potential explanatory of survival. There will be an attempt to model all of these factors, including arm, potential baseline prognostic factors collected at screening, including baseline subject attributes and circulating tumor cells, immune responses, the use of post- progression anti -cancer therapies, and tumor regression and growth rates for their relationship to survival. 9. Safety Analysis A ll safety analyses will be conducted on the FAS. All summaries in the safety analysis will be presented by treatment arm and overall.