Surrogate Endpoints in Infectious Diseases Trials: FDA Perspective

1. Surrogate Endpoints in Infectious Diseases Trials:FDA Perspective John H. Powers, MD Lead Medical Officer Antimicrobial Drug Development and Resistance Initiatives Office of Drug Evaluation IV Center for Drug Evaluation and Research U.S. Food and Drug Administration

2. Introduction • Definition of clinical endpoints and surrogate endpoints • Strengths, limitations and utility of surrogates endpoints in drug development • Regulatory considerations with the use of surrogate endpoints • Validating a surrogate endpoint

3. What’s Important to Patients?

4. Definitions • Clinical endpoint = direct measure of how a patient feels, functions or survives • mortality • resolution of symptoms of disease • Surrogate endpoint = laboratory measurement or physical sign used as a substitute for clinical endpoint • Surrogate endpoint by itself does not confer direct clinical benefit to the patient • NIH Biomarkers Definitions Working Group, Clin Pharmacol Ther;2001;69:89-95.

5. Definitions • Examples of surrogate endpoints • measurement of organism (e.g.culture or viral load) • results of antigen testing • changes in x-ray, CT scan, endoscopic appearance • histological changes • “Surrogate of a surrogate” • changes in cultures associated with histological changes • presence of organisms on catheter tip • elimination of organisms in a population without the disease (e.g patients with asymptomatic bacteruria as a surrogate for patients with uncomplicated UTI)

6. Definitions • Surrogate endpoints are a subset of biomarkers • Biomarkers are useful for purposes other than endpoints • diagnostic tool - use of test as an inclusion criteria to define the disease based on presence of organism (increases specificity of diagnosis) • risk factor for disease - neutropenia (WBC) in a patient with hematological malignancy • indicator of disease prognosis - risk factor for outcome (HIV viral load and CD4 in HIV) • Sande MA et al. NIH Consensus Conference on HIV, JAMA 1993;270:2583-89.

7. Biomarkers as Prognostic Indicators Microbiological Success Microbiological Failure CS CS CS CS CS CS CS CS CF CS CS CS CF CF CF CS CS CS CS CS CF CS CS CF CS CF CS CS CS CS CF CS CF CS CS CS CS CS CF CS CS = clinical success, CF = clinical failure

8. Biomarkers as Surrogate Endpoints Clinical Outcomes Microbiological Outcomes MS CS CF MS MS MS CS MF CS CS CS MS MS CS MF CF CF CS CF MF CS MS CS MS CS = clinical success CF = clinical failure MS = micro success MF = micro failure

9. Biomarkers as Surrogate Endpoints Micro Outcomes Clinical Outcomes Good Overlap Not-So-Good Overlap Clinical Outcomes Micro Outcomes

10. Strengths of Surrogate Endpoints • Reproducible • Standardized (in some cases) • Objective • Can be dichotomous (yes/no) • Can lower sample size when success rate is higher higher success rates • In chronic diseases, can measure earlier than clinical endpoint

11. Sample Size per Arm - 80% power D

12. Utility of Surrogate Endpoints • Early clinical development • Mechanistic understanding/pathogenesis of disease • Knowledge about clinical pharmacology • Guidance in dose selection • “Proof of principle” of efficacy in phase 2 trials • Basis for selecting compounds for phase 3 testing • Later stages of drug development • Bring treatment benefits to patients earlier than with trials with clinical outcomes when surrogate endpoint precedes clinical endpoint by significant amount of time (e.g. HIV infection)

13. Limitations of Surrogate Endpoints • Smaller trial may not provide enough data to analyze safety of drug • absence of an adverse event in a safety database of 300 patients will rule out risk of only 1 in 100 (1%) • Benefit in terms of surrogate endpoint may overestimate benefit on true endpoint • in prophylaxis trial high rate of decolonization may predict only small benefit in prevention of infection • in treatment trial rate of culture negativity may overestimate clinical cure rate • Surrogate endpoint may not predict clinical benefit

14. Surrogate Endpoints Clinical Endpoint Surrogate Endpoint Intervention • Surrogate endpoints must be on causal path of disease • Surrogate must capture full benefit of treatment effect • Assumes no other pathway of mechanism of drug effect • Mechanism of action different from effect of drug

15. Surrogate Endpoints Unmeasured benefits Clinical Endpoint Surrogate Endpoint Intervention Unmeasured harm • Surrogate may not take into account unmeasured • benefits and harms of treatment • Knowledge about how a drug achieves clinical results • may be incomplete

16. Surrogate Endpoints • Unmeasured benefits • effects of drug other than “eradication” • sub-inhibitory effects of antimicrobials on organisms • bactericidal therapy not necessary in many infections • direct effects of antimicrobials on host immune system • Labro MT et al. Curr Opin Investig Drugs 2002:3:61-8. • Nau R et al. Clin Micro Rev 2002;15:95-110. • Unmeasured harm • lysis of organisms may have effect on inflammatory cascade and resultant effect on clinical outcomes • replacement of one organism with another • other sources of infection other than that affected by drug

17. Surrogate Endpoints Unmeasured benefits Clinical Endpoint Surrogate Endpoint Intervention Unmeasured harm • Issues with accuracy of how surrogate is measured • it may be reproducible (precision) but is it telling • us the correct inference (accuracy)

18. Limitations of Surrogate EndpointsReasons why Surrogates Fail Unmeasured benefits Clinical Endpoint Surrogate Endpoint Intervention Unmeasured harm • Measurement of clinical endpoint may not • be relevant based on natural history of disease • fixed time points beyond time of natural resolution

19. Endpoints and Timing Nicholson KG et al. Lancet 2000;355:1845-1850.

20. Validating SurrogatesCorrelation/Concordance = concordant = discordant Surrogate success Surrogate failure B A Clinical success D C Clinical failure • Kappa coefficient of correlation • 0 <k< 0.4 = marginal (or no) agreement • 0.4 <k < 0.75 = good agreement • k> 0.75 = excellent agreement • Kraemer HC Stat Med 2002:21:2109-29

21. Validating Surrogates Perfect correlation slope = 1 80% 80% % clinical success % success with surrogate • Surrogate must measure effects similarly for • all drugs studied

22. Validating Surrogates Perfect correlation slope = 1 Acute otitis media = 0.37 Acute bacterial meningitis = 0.14 % clinical success % success with surrogate • Surrogate should accurately reflect clinical outcomes

23. Validating SurrogatesDouble-Tympanocentesis Trials in AOM Perfect correlation slope = 1 Surrogate and clinical on day 4-6 0.62 % clinical success 0.42 0.37 0.34 0.32 0.28 0.14 % success with surrogate • Surrogate must measure effects similarly for • all drugs studied

24. Validating Surrogates Perfect correlation slope = 1 Drug A Drug B % clinical success % success with surrogate • Surrogate must measure effects similarly for • all drugs studied

25. Validating Surrogates Perfect correlation slope = 1 Drug A Drug B A B A B % clinical success % success with surrogate • Surrogate must measure effects similarly for • all drugs studied

26. Regulatory Perspective • Traditional approval based on surrogate endpoints only in cases where endpoint already validated to predict clinical endpoint • Accelerated approval based on surrogate endpoints (Subpart H, 21 CFR 314.800) • serious and life threatening disease • requires confirmatory post-approval trial based on clinical endpoint • usually from a trial that is already ongoing

27. Regulatory Perspective HIV trial Surrogate endpoint Clinical endpoint Acute bacterial disease trial time • Trial complete so requires initiation of second trial

28. Conclusions • Surrogate endpoints can be useful in clinical trials in both early and later development • examine risk/benefit of use of surrogate e.g. long term illness, serious and life threatening disease • Use of surrogates requires validation prior to using as endpoint in clinical trial • validation specific for disease and population • Accelerated approval requires confirmatory trial • Validation of surrogate requires meta-analysis of correlation AND capture full treatment effect

29. “Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question, which can always be made precise.” John W. Tukey (1962) Annals of Mathematical Statistics 1962;33:1-67.

30. Questions • In what situations and in what kinds of diseases would surrogate endpoints be most useful? • How can one obtain the information necessary to validate surrogate markers? • What are the issues with obtaining the validation of a surrogate necessary for fulfillment of Subpart H in more acute diseases?