1. How should efficacy of new adjuvant therapies be evaluated in colorectal cancer? Marc Buyse, ScD IDDI, Brussels, Belgium Based on Daniel Sargent’s talks at ODAC in May 2004 and ASCO in June 2004

2. Hypothesis Disease-free survival (DFS), assessed after 3 years, is appropriate to replace overall survival (OS) as an endpoint in adjuvant colon trials (i.e. 3-year DFS is a valid “surrogate endpoint” for 5-year OS)

3. Surrogate Endpoints Multiple statistical methods proposed Prentice’s definition and criteria 1 Freedman’s proportion explained 2 Begg and Leung’ concordance 3 Buyse et al’s correlation 4 No agreement about best practice 1 Stat Med, 1989. 2 Stat Med, 1992. 3 JRSSA, 2000. 4 Biometrics 1998, Biostatistics 2000, JRSSC, 2001.

4. Prentice criteria An endpoint can be used as a surrogate if it predicts the final endpoint it fully captures the effect of treatment upon the final endpoint But, how is this verified? Ref: Prentice, Stat Med, 1989.

5. Proportion explained The proportion explained is defined as the proportion of treatment effect that is captured by a surrogate. But, the associated mathematical construct (the change in a model parameter) is flawed. Ref: Freedman et al, Stat Med, 1992.

6. Concordance of results ‘The validity of a surrogate endpoint should be judged by the probability that the trial results based on the surrogate endpoint alone are ‘concordant’ with the trial results that would be obtained if the true endpoint were observed and used for the analysis’ But, concordance of hypothesis tests is driven by their power Ref: Begg and Leung, JRSSA, 2000.

7. Correlation approach An acceptable surrogate must satisfy two conditions: 1. The surrogate must predict the true endpoint 2. The effect of treatment on the surrogate must predict the effect of treatment on the true endpoint Refs: Buyse and Molenberghs, Biometrics 1998; Buyse et al, Biostatistics 2000.

8. Trial characteristics 33 Arms 9 no treatment control 24 ‘Active’ rx Median follow-up 8 years 5 year data on 93% of patients Due to inconsistent long-term follow-up all analyses censored at 8 years

10. Patient Characteristics Age < 50: 2237 (17%) 50-59: 3487 (27%) 60-69: 5039 (39%) > 70: 2071 (16%) Treatment Control: 2454 (18%) Active: 11610 (82%) Gender M: 7568 (54%) F: 6496 (46%) Stage I: 210 (2%) II: 5137 (36%) III: 8714 (62%)

11. Recurrence rate by 6 mo intervals 0 7.2 6.9 5.6 4 3.2 2.2 2 1.3 1.2 0.9 0.8 0.5 0.4 0.3 0 1 2 3 4 5 6 7 8 00.511.522.533.544.555.566.577.58 Years after randomisation Recurrence Rate (%) 3.5

12. 3 year DFS vs 5 year OS 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.50.550.60.650.70.750.8 Disease-Free Survival Overall Survival R 2 = 0.86 r = 0.89

13. Parameter Intercept Slope Estimate 0.03 0.94 P-value 0.048 <0.001 Regression equation: 5 year OS= 0.03+0.94*3 year DFS Correlation 0.89, R 2 = 0.86 3 year DFS vs 5 year OS

14. On an arm-by-arm basis: 3 year DFS excellent predictor of 5 year OS Formal approaches suggest surrogacy Event rates virtually identical No impact on sample size Power for DFS will adequately power for OS 3 year DFS vs 5 year OS

15. Hazard ratios: DFS vs OS Disease-Free Survival Hazard Ratio

16. Hazard ratios: DFS vs OS Regression equation: OS HR = 0.09 + 0.93 * DFS HR Correlation 0.89, R 2 = 0.87 Parameter Intercept Slope Estimate 0.092 0.93 P-value 0.24 <0.001

17. OS HR attenuated from DFS HR toward unity in 12 of 18 comparisons Hazard ratios: DFS vs OS

18. As an endpoint for comparison: Hazard ratio for DFS an excellent predictor of HR for OS  with slight attenuation Marginally significant improvements in 3 year DFS may not translate into improvements in 5 year OS

19. Predicted and Actual OS Hazard Ratios 0,2 0,4 0,6 0,8 1 1,2 1,4 1,6 FFCD SIENA INT-0035 N-78 C03 GIVIO NCIC N-87 C02 C04 c2C04 c1 C01 N-91 N-89 c3 C05 S9415 N-89 c2N-89 c1 Hazard Ratio Predicted Overall Survival Hazard Ratio Actual Overall Survival Hazard Ratio

20. Disease-Free Survival an excellent predictor of Overall Survival Meets most formal definitions of surrogacy Modest attenuation of treatment effect between the two endpoints Model allows prediction of OS effect based on DFS effect Discussion

21. Discussion Is Overall Survival the most desirable endpoint? It may be the ultimate goal of any therapy for life-threatening disease But, it is highly insensitive True treatment benefit may be confounded by successive lines of therapy

22. Collaborators S Wieand, M O’Connell - NSABP J Benedetti - SWOG R Labianca - Ospedali Riuniti (Italy) D Haller - ECOG L Shepherd - NCIC JF Seitz - University of the Mediterranean (France) G Francini - University of Siena (Italy) A de Gramont - Hospital Saint Antoine (France) R Goldberg - NCCTG/UNC M Buyse - IDDI (Belgium) Acknowledgement: E Green (Mayo)