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Surrogate Endpoints in Infectious Diseases Trials: FDA Perspective Surrogate Endpoints in Infectious Diseases Trials: FDA Perspective John H. Powers, MD.

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Presentation on theme: "Surrogate Endpoints in Infectious Diseases Trials: FDA Perspective Surrogate Endpoints in Infectious Diseases Trials: FDA Perspective John H. Powers, MD."— Presentation transcript:

1 Surrogate Endpoints in Infectious Diseases Trials: FDA Perspective 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 2Introduction  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 3 What’s Important to Patients?

4 4Definitions  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 5Definitions  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 6Definitions  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 7 Biomarkers as Prognostic Indicators CS = clinical success, CF = clinical failure Microbiological Success CS CS CS CS CS CS CS CS CS CS CS CS CS CF CF CS CS CS CS CS Microbiological Failure CS CS CS CS CS CS CS CS CS CS CS CS CF CF CF CF CF CF CF CF

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

9 9 Biomarkers as Surrogate Endpoints MicroOutcomes ClinicalOutcomes MicroOutcomes ClinicalOutcomes GoodOverlap Not-So-GoodOverlap

10 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 11 Sample Size per Arm - 80% power 

12 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 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 14 Surrogate Endpoints Surrogate endpoints must be on causal path of disease Surrogate endpoints must be on causal path of disease Surrogate must capture full benefit of treatment effect Surrogate must capture full benefit of treatment effect Assumes no other pathway of mechanism of drug effect Assumes no other pathway of mechanism of drug effect Mechanism of action different from effect of drug Mechanism of action different from effect of drug Intervention SurrogateEndpointClinicalEndpoint

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

16 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 17 Surrogate Endpoints Issues with accuracy of how surrogate is measured Issues with accuracy of how surrogate is measured it may be reproducible (precision) but is it tellingit may be reproducible (precision) but is it telling us the correct inference (accuracy) Unmeasured benefits Unmeasured harm Intervention SurrogateEndpoint ClinicalEndpoint

18 18 Limitations of Surrogate Endpoints Reasons why Surrogates Fail Unmeasured benefits Unmeasured harm Intervention SurrogateEndpoint ClinicalEndpoint Measurement of clinical endpoint may not Measurement of clinical endpoint may not be relevant based on natural history of disease fixed time points beyond time of natural resolution fixed time points beyond time of natural resolution

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

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

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

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

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

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

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

26 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 27 Regulatory Perspective HIV trial Surrogateendpoint Clinicalendpoint Acute bacterial disease trial time Trial complete so requires initiation of second trialTrial complete so requires initiation of second trial

28 28Conclusions  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 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 30Questions  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?


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