1. 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

2. 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):

3. 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): Xie N et al. Int J Cancer. 2015;136(4):E27-E38.
3. Smith MR et al. J Clin Oncol. 2018;36(15_suppl): Fleischer F et al. Stat Med. 2009;28(21):

4. 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 ( )
0.33 ( )
0.63 ( )
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 ( )
0.31 ( )
0.4 ( )
Time to PSA progression, HR (95% CI)
0.17 ( )
0.38 ( )
0.25 ( )
Abbreviations: CI, confidence interval; HR, hazard ratio; mCRPC, metastatic castration-resistant prostate cancer.
*Planned treatments were utilized in the modeling.

5. 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

6. 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.

7. 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.

8. 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.

9. 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.

10. 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 ( )
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

11. 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.

12. 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.

13. 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.

14. 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.

15. 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 ( )
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

16. 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 for rPFS and 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