Identifying and validating surrogate endpoints for overall survival (OS) in metastatic castration-resistant prostate cancer (CRPC) Xiaowei Guan, De Phung, Eren Demirhan, Suha Sari, Michelle Casey JSM, 2018

Methodology: Assessing Surrogacy Objective To evaluate if radiographic progression-free survival (rPFS) and time to prostate-specific antigen (PSA) progression could be considered surrogate endpoints for OS Approach Correlation proposed by Burzykowski et al1 using bivariate copula models in which 2 criteria for the correlation are required: Individual level surrogacy Demonstrate an association between rPFS or time to PSA progression and OS at the individual patient level; these methods account for the bivariate distribution and the treatment effect Measured by either Kendall’s τ or Spearman’s ρ estimated based on the copula parameter Trial level surrogacy Demonstrate an association between the estimated treatment effect on rPFS or time to PSA progression and the estimated treatment effect on OS, in which estimates should ideally account for bias and measurement error Measured by the coefficient of determination, R2, which indicates a goodness of fit of a regression line 1. Burzykowski T et al. J R Stat Soc Ser C Appl Stat. 2001;50(4):405-422.

Data: Assessing Surrogacy Background Developed by Burzykowski et al1; the preferred approach to evaluate surrogacy is based on individual patient data from several trials Xie et al2 demonstrated that metastasis-free survival (MFS) is a strong surrogate for OS in localized prostate cancer Smith et al3 published poster results of association between MFS and OS in nonmetastatic CRPC using the Fleischer et al4 method Methods Data from 3 placebo-controlled, randomized, phase 3 trials of enzalutamide in metastatic CRPC were considered to assess rPFS and time to PSA progression as potential surrogate for OS rPFS: defined as the time from randomization to the earliest objective evidence of radiographic (bone or soft tissue) progression or death on study PSA progression: defined as the time from randomization to the date of first the PSA value demonstrating progression, which was subsequently confirmed (for patients with PSA decline at week 17, PSA progression date was defined as the date that a ≥ 25% increase and an absolute increase of ≥ 2 µg/L [2 ng/mL] above nadir [or baseline for patients with no PSA decline by week 17] was documented and confirmed by second consecutive assessment made ≥ 3 weeks later) OS: defined as the time from randomization to death due to any cause 1. Burzykowski T et al. J R Stat Soc Ser C Appl Stat. 2001;50(4):405-422. 2. Xie N et al. Int J Cancer. 2015;136(4):E27-E38. 3. Smith MR et al. J Clin Oncol. 2018;36(15_suppl):5032. 4. Fleischer F et al. Stat Med. 2009;28(21):2669-2686.

Overview of Studies Included Study PREVAIL Asian PREVAIL AFFIRM Primary endpoints OS and rPFS Time to PSA progression OS OS, HR (95% CI) 0.71 (0.60-0.84) 0.33 (0.16-0.67) 0.63 (0.53-0.75) Population mCRPC Treatments* Enzalutamide vs placebo No. of subjects 1717 388 1199 No. of countries 22 4 15 Dates of trial enrollment 22 Jun 2010 23 Apr 2014 30 Sep 2009 Length of follow-up, mo 31.5 for OS 11.0 for rPFS 5.6 for time to PSA progression 16.4 for OS rPFS, HR (95% CI) 0.19 (0.15-0.23) 0.31 (0.2-0.46) 0.4 (0.35-0.47) Time to PSA progression, HR (95% CI) 0.17 (0.15-0.20) 0.38 (0.27-0.52) 0.25 (0.20-0.30) Abbreviations: CI, confidence interval; HR, hazard ratio; mCRPC, metastatic castration-resistant prostate cancer. *Planned treatments were utilized in the modeling.

rPFS or time to PSA progression as a surrogate for OS Analysis Flow rPFS or time to PSA progression as a surrogate for OS Approach 1 Use 3 trials as trial effect Use 3 regions as trial effect Center effect = trial effect Center are subsets of the trial First, rPFS was tested for surrogacy to OS Second, time to PSA progression was tested in a similar approach For each approach there were 3 copula models tested: Clayton, Hougaard, and Plackett Both individual and trial level correlations will be demonstrated for those 3 models Approach 2 Approach 3

Results of rPFS vs OS: Data Facts Study PREVAIL Asian PREVAIL AFFIRM Endpoints rPFS vs OS No. of subjects 1717 388 1199 No. of countries 22 4 15 Approach 1 Study North America Europe Rest of world No. of subjects 821 1570 913 No. of countries 2 15 11 Approach 2&3* *In approaches 2 and 3, 3 new regions were defined according to geographical characteristics.

Approach 1 for rPFS vs OS: Use 3 Real Trials as the Trial Effect, Also Making Trial = Center Parameter Model Estimates Kendall's τ Hougaard 0.37 Clayton 0.42 Plackett Spearman's ρ 0.53 0.59 0.52 Individual level Type Model R2 Unweighted Hougaard 0.05 Clayton 0.04 Plackett 0.02 Weighted* 0.15 0.07 Trial level *Weighted refers to weighted by samples size.

Approach 2 for rPFS vs OS: Use 3 Regions as the Trial Effect, Also Making Trial = Center Parameter Model Estimates Kendall's τ Hougaard 0.37 Clayton 0.44 Plackett 0.38 Spearman's ρ 0.53 0.61 Individual level Type Model R2 Unweighted Hougaard 1 Clayton Plackett 0.99 Weighted* 0.98 Trial level *Weighted refers to weighted by samples size.

Approach 3 for rPFS vs OS: Use 3 Regions as the Trial Effect, Also Making Country Variables the Center Effect Parameter Model Estimates Kendall's τ Hougaard 0.38 Clayton 0.44 Plackett Spearman's ρ 0.53 0.62 0.54 Individual level Type Model R2 Unweighted Hougaard 0.26 Clayton 0.22 Plackett 0.25 Weighted* 0.27 Trial level *Weighted refers to weighted by samples size.

Observations From rPFS and OS Surrogacy Analysis Individual level correlations are more consistent than the trial level correlation Individual level correlations show a moderate correlation between rPFS and OS (0.37-0.62) Individual level data is less affected by trial heterogeneity than the trial level correlation The bigger difference with approach 2 than approaches 1 and 3 (R2 assessments are distributed on 2 extremes) may stem from the convergence issue of certain countries/centers as the copula model would require a certain number of events in each treatment arm

Results of Time to PSA Progression vs OS: Data Facts Study PREVAIL Asian PREVAIL AFFIRM Endpoints rPFS vs OS No. of subjects 1717 388 1199 No. of countries 22 4 15 Approach 1 Study North America Europe Rest of world No. of subjects 821 1570 913 No. of countries 2 15 11 Approach 2&3* *In approaches 2 and 3, 3 new regions were defined according to geographical characteristics.

Approach 1 for Time to PSA Progression vs OS: Use 3 Real Trials as the Trial Effect, Also Making Trial = Center Parameter Model Estimates Kendall's τ Hougaard 0.32 Clayton 0.21 Plackett 0.25 Spearman's ρ 0.46 0.31 0.37 Individual level Type Model R2 Unweighted Hougaard 0.49 Clayton 0.71 Plackett Weighted* 0.34 0.61 0.63 Trial level *Weighted refers to weighted by samples size.

Approach 2 for Time to PSA Progression vs OS: Use 3 Regions as the Trial Effect, Also Making Trial = Center Parameter Model Estimates Kendall's τ Hougaard 0.34 Clayton 0.23 Plackett 0.26 Spearman's ρ 0.48 0.33 0.38 Individual level Type Model R2 Unweighted Hougaard 0.77 Clayton 0.13 Plackett 0.54 Weighted* 0.69 0.06 0.43 Trial level *Weighted refers to weighted by samples size.

Approach 3 for Time to PSA Progression vs OS: Use 3 Regions as the Trial Effect, Also Making Country Variables the Center Effect Parameter Model Estimates Kendall's τ Hougaard 0.34 Clayton 0.22 Plackett Not converge Spearman's ρ 0.48 0.32 Individual level Type Model R2 Unweighted Hougaard 0.0 Clayton Plackett Not converge Weighted* 0.07 0.02 Trial level *Weighted refers to weighted by samples size.

Observations From Time to PSA Progression and OS Surrogacy Analysis Individual level correlations are more consistent than the trial level correlation Individual level correlations show a moderate correlation between time to PSA progression and OS (0.21-0.48) Individual level data is less affected by trial heterogeneity than the trial level correlation Approaches 1 and 2 both show a strong correlation between time to PSA progression and OS; this may be attributed to the fact that the primary endpoint of the Asian AFFIRM study is time to PSA progression

Conclusions Investigation of rPFS or time to PSA progression vs OS shows a moderate correlation between rPFS or time to PSA progression and OS at the individual level of 0.37- 0.62 for rPFS and 0.21-0.48 for time to PSA progression At the trial level investigation of rPFS vs OS, different approaches (using either real trial or region factors as a trial effect) were investigated to assess surrogacy by including or excluding the country as center effects; in general, approach 1 is recommended Different disease stages and relative immaturity of OS data should be considered for the interpretation of the results