Protocol B7791001 Statistical Analysis Plan PFIZER CONFIDENTIAL Page 2610.APPENDICES 10.1. Appendix: Statistical Methods for Immunogenicity (serology) Definitions: Let x i, i=1, 2, n, be the titer for subject i where n is the number of subjects. Then the geometric mean titer (GMT) is defined as follows GMT= exp[(1/n) Σlog (x i)], where log is the natural logarithm. Within each vaccine group and for each antibody, geometric mean titers (GMTs) will be calculated. Each titer will be logarithmically transformed for anal ysis. Two (2) -sided, 80% confidence intervals will be constructed by back transformation of the confidence intervals for the mean of the logarithmically transformed assay results. Let x i, i=1, 2, n, be the titer for test group and let yi, i=1, 2, m, be the tite r for reference group. Then the geometric mean ratio (GMR) is defined as follows: GMR =exp[(1/n) Σlog (x i) -(1/m) Σlog (y i)]. Also for the GMR s, the confidence intervals will be constructed b y back transformation of the confidence intervals for the mean difference of the l ogarithmically transformed assay results ( testrelative to reference ). Let x i, i=1, 2, n, be the titer prior vaccination and let y i, i=1, 2, n, be the titer post vaccination. Then the geometric mean fold rise (GMFR) is defined as follows: GMFR= exp[(1/n) Σlog (y i/xi)]. For the geometric mean fold rise, the confidence intervals will be constructed by back transformation of the confidence intervals for the mean difference of the logarithmically transformed assay results ( post to prior ). GMTs, GMRs and GMFR wi ll be estimated by an ANCOVA model with natural log transformed anti -body titer as outcome variable, and treatment group as factor and baseline (in log scale) as covariates at each of the post- dose measurement. These analy ses based on log-transformed data , the L SMEAN estimates and confidence interval will be back -transformed (exponentiated) and presented. The estimated treatment difference and corresponding confidence intervals from the model will also be back -transformed. -For GMTs the variable ofintere st, that will be back transformed, is log (x i) xi, i=1, 2, n, be the titer for subject i -For GMFRs the variable of interest, that will be back transformed, is log (yi) –log (x i) Protocol B7791001 Statistical Analysis Plan PFIZER CONFIDENTIAL Page 27xi, i=1, 2, n, be the titer prior vaccination and let yi, i=1, 2, n, be the titer post vaccination Back-transformation of estimated difference in GMTs (with contrasts) is interpreted as GMR between treatment and placebo group . In addition to the adjusted anal ysis for GMTs, GMRs and GMFRs between groups through analysis of covari ance, unadjusted (crude) GMTs, GMRs and GMFRs will be calculated as a sensitivity anal ysis. For GMTs, t wo (2) -sided, 80% confidence intervals will be constructed b y back transformation of the confidence intervals for the mean of the logarithmically transformed assay results computed using the Student t distribution . For the GMRs , the confidence intervals will be constructed by back transformation of the confidence intervals for the mean difference of the logarithmicall y transformed assay results (testrelative to reference ) computed using the Student t distribution. For reporting purposes, 1 decimal place will be used for geometric mean titers (GMTs), and 2decimal will be used for geometric mean ratios (GMFRs, GMRs). Protocol B7791001 Statistical Analysis Plan PFIZER CONFIDENTIAL Page 2810.2. Appendix: PSA kinetics _AppendiCES PSA velocity is defined as the slope of the linear regression line of PSA against time in month. PSA slope is the slope of the linear regression line of natural log of PSA against time in month. PSA doubling time is defined as the natural log of 2 divided by the slope of the linear regression line of the natural log of PSA against time in month As a numerical example Date PSA Log n Log 2 5/1/2016 0.5 -0.69 -1.00 6/1/2016 1 0.00 0.00 7/1/2016 0.6 -0.51 -0.74 8/1/2016 1 0.00 0.00 10/1/2106 1.6 0.47 0.68 PSA Slope 0.20 PSA Doubling Time3.49 months PSA Velocity 0.19 ng/ml/mo Protocol B7791001 Statistical Analysis Plan PFIZER CONFIDENTIAL Page 2910.3. Appendix: Time to Event Data Analysis Censoring Rules The specific programming specifications and censoring rules for PFS/rPFS will be defined in the Anal ysis Programming Specification.