Big Issues

1. Considerations for the choice and interpretation of endpoints ininternational trials of antiretroviral therapiesVictor De Gruttola

2. Big Issues When do results from a study in one region apply to another region? Do safety and efficacy endpoints have the same meaning across populations of interest? Can we improve ability to generalize results by investigating predictors of and surrogates for efficacy and safety endpoints in the populations of interest?

3. Predictors of Safety and Efficacy Are populations similar with regard to: - predictors of safety and efficacy and safety in presence and absence of treatment (Rx)? - surrogates for Rx effects Of special interest, factors that modify the effect of Rx on endpoints.

4. Botswana BOTSWANA: World AIDS Day March

5. Tshepo Study Question: What is the best first line therapy and adherence strategy for reducing virological failure with development of resistance. Factorial Design: 660 patients Factor 1: Efavirenz vs Nevirapine Factor 2: ZDV/3TC vs D4T/3TC vs ZDV/ddI Factor 3: Treatment Partner (Mopati) vs SOC Primary Endpoint: Time to virological failure with significant resistance mutations as defined by the Stanford website. Last on-treatment viral load will be genotyped

6. Tshepo • Primary endpoint may occur after failure of first regimen. • Second regimen is Nelfinavir + other nucleosides. About 25% of patients in ACTG 384 had no resistance mutations at the time of failure of the first regimen. • Patients will receive intensive adherence monitoring after virological failure but before being switched.

7. ACTG 5175 Arm A: (BID) ZDV/3TC + efavirenz (EFV) or nevirapine (NVP) Arm B: (QD)+atazanavir (ATV) + FTC +d4T-XR Arm C: (QD) FTC + tenofovir (TDF) + EFV or NVP

8. A5175 Primary Endpoint: • Time to treatment failure is time to first occurrence of: - Disease progression. New or recurrent AIDS defining opportunistic infection or malignancy after 12 weeks of therapy. - Virologic failure. Plasma HIV-1 RNA > 1,000 copies/mL on two consecutive measurements after 24 weeks of therapy. Power: 1250 patients (allowing 10% dropout rate) provides 80% power to reject a hazard ratio of > 1.4 if treatments being compared have same true endpoint rates. Arms B and C compared to arm A.

9. UNAIDS 2001 A5175 Site Locations

10. Factors that Affect Endpoints • Pre-Rx factors that predict (safety and efficacy) endpoints in presence and absence of Rx • Pre-Rx factors that alter the effect of Rx on endpoints • Disease Markers that capture Rx effects on endpoints (surrogate endpoints)

11. Pre-Rx Predictive Factors • Baseline hemoglobin is may predict anemia during treatment • Suppose Rx reduces Hb by . • Even if baseline Hb does not affect , patients with low Hb at baseline may be at higher risk of anemia

12. Baseline Factors That Alter Rx Effects • Presence of HIV resistance mutations alter Rx effects on virologic endpoints. • Clade of HIV alters the type and effect of resistance mutations. • Prevalence of viral clade and of mutant viruses in a population impact Rx efficacy. • To predict of Rx effects in a new population requires knowledge of prevalence of clade/ resistance mutations as well as their impact on Rx effects.

13. Disease Markers • Disease markers may capture Rx effects on safety and efficacy endpoints • Difference across populations in the levels and meaning of these marker in the presence and absence of Rx may complicate both generalization of Rx effects and patient management in the new population

14. Example: Neutropenia • In Botswana, anecdotal reports of higher than expected levels of neutropenia in ART-treated patients, but not higher rates of diseases associated with neutropenia. • Does neutropenia have a different meaning in Botswana than in the US/Europe? • Use of neutropenia as a toxicity endpoint may be problematic unless answer is no. • Need to collect clinical and lab information.

15. Surrogate Endpoints Example: Neutropenia • Is the Rx effect on risk of neutropenia different across populations? • Does given level of neutropenia in treated patients have the same impact on risk of infections associated with neutropenia?

16. Surrogate Endpoints X T S X T S

17. Surrogate Endpoints • Do surrogates (disease markers) for clinical endpoints (toxicity or efficacy) have the same relationship to clinical endpoints across different populations (different Rx’s?) ? • Knowledge of surrogates helps in generalizing results across populations. • Small studies on surrogates in populations of interest may help generalization.

18. Latent variable models: Zeger and Xu For study 1: For study 2: S1 S2 1 X1 2 X2 T1 T2 Sm For study m: m Xm Tm

19. Latent variable models • In these models, S provides indirect information about latent variable . • Is knowledge of X and S adequate to predict T, i.e. is S a surrogate for T? • Also of interest: variability in  associated with region.

20. Surrogate endpoint analyses • If S: - is surrogate for T across regions - responds similarly to X (and is similar in untreated pts.) across populations • Then X should have same effect on T across populations • Reduces need to study effect of X on T in every region.

21. Review of HIV Example International research on ART exemplifies problems that arise in generalizing across populations. Specifically, we are concerned about variability in: • Prevalence of important pre-Rx predictors (e.g. hemoglobin). • Prevalence of important pre-Rx modifiers (e.g. viral clade/resistance mutations). • Prevalence of important disease markers pre- and during Rx (e.g. neutropenia) and in their meaning.

22. How to Investigate These Issues? • Need for randomized and observational studies across populations of interest providing information on both marker and clinical endpoints. • Need to make data available to investigators/regulators because large data sets required to estimate effects. • Why observational as well? To generate hypotheses that may be further investigated in randomized studies about predictors and disease markers

23. Conclusions • Generalizing results of intervention studies across populations involves consideration of: • Predictors of safety and efficacy endpoints. • Modifiers of Rx effects on endpoints. • Surrogates for endpoints. • Large databases that permit surrogacy-type analyses are needed for such investigations.