1. Statistical Issues and Challenges in Combination Vaccines
Ivan S. F. Chan, Ph.D. Merck Research Laboratories
Sang Ahnn, Ph.D.
CBER, FDA
2005 FDA/Industry Statistics Workshop
Washington D.C.
September 14-16, 2005
Note: Sang Ahnn's opinions are his own and do not
necessarily reflect FDA policy

2. Outline of Presentation
Introduction of vaccine development
Combination vaccines
Statistical considerations for combination vaccine studies
Special challenges
A recent example
Summary

3. The Ten Greatest Public Health Achievements of the 20th Century
Vaccination
Motor-vehicle safety
Safer workplaces
Control of infectious diseases
Decline in deaths from coronary heart disease and stroke
Safer and healthier foods
Healthier mothers and babies
Family planning
Fluoridation of drinking water
Recognition of tobacco use as a health hazard
MMWR (1999);48:1141

4. Vaccines Are Different From Drugs
Typically for prophylaxis, not treatment
Focus on vaccines for children traditionally, with recent shift to adult vaccines
Public health issues
Risk benefits at individual vs population level
Indirect vaccine effect (herd immunity)
Highly complex immunologic milieu
Array of humoral and cellular immune responses
Large, complex molecules of biological origin
Unique manufacturing and control issues

5. Clinical Development of Vaccines
Safety
Assess local (injection-site) and systemic adverse experiences
Need a large database, particularly because of giving vaccines to healthy subjects
Efficacy
Require a high level of evidence and precision
Success typically requires showing efficacy greater than a non-zero (e.g. 25% - 50%) lower bound

6. Clinical Development of Vaccines
Immunogenicity
Important in understanding the biology
Antibody responses – priming, first defense
T-cell responses – prevent virus reactivation, kill infected cells
Correlates of protection (“surrogate” endpoints) and immune markers used for
bridging studies (e.g., new vs. old formulations)
assessing consistency of vaccine manufacturing process
assessing combination vaccines or concomitant use of vaccines

7. Combination Vaccines
Offer multiple vaccines (or vaccines with multiple sero-type antigens) at one administration
Reduce the number of injections given to children (fear of injection “needle”)
Reduce infant crying time and cost associated with parental perceptions of pain and emotional distress
Reduce the frequency of clinic visits
Increase vaccination coverage and public health benefits

8. Examples of Combination Vaccine
Diphtheria/Tetanus/Pertussis (DTaP)
Hepatitis A/Hepatitis B
Hepatitis B/Haemophilus Influenza b
Measles/Mumps/Rubella (MMR)
Measles/Mumps/Rubella/Varicella (MMRV)

9. An Example of Combination Vaccine: MMRV (ProQuad™)
Combines two well-established vaccines
M-M-R™ II for measles, mumps, and rubella (licensed in 1978)
VARIVAX™ for chickenpox (licensed in 1995)
Clinical development of ProQuad starts in 1984
Includes over 5800 subjects
Provides similar immunogenicity and safety profiles compared with component vaccines
Licensed on Sept 6, 2005

10. Statistical Considerations for Combination Vaccine Studies
Noninferiority design
Analysis methods
Consistency lots study

11. Study Design of Combination Vaccines
Aim is to show non-inferiority of combination vaccine compared to separately administered components
Immune responses are the key measures
Percent of subjects achieving a response (definition depends on specific vaccines)
Geometric mean titer (or concentration)
Evaluate potential interactions on immune responses and safety among components

12. Typical Non-inferiority Analysis Setup in Combination Vaccine Trials
Hypothesis of response rate for each component:
H0: PT - PC  -  versus H1: PT - PC > - 
where >0 is a prespecified non-inferiority margin
Hypothesis of geometric mean titer for each component:
H0: GMTT/GMTC  R versus H1: GMTT/GMTC > R
where 0<R<1 is a prespecified non-inferiority margin
Rejection of H0 implies that the combination vaccine is not inferior to the control
Success requires demonstration of non-inferiority for all components regarding both endpoints

13. Selection of Non-inferiority Margin
Choice of margin depends on
Clinically meaningful difference
Regulatory standard
Statistical power/sample size considerations
For response rate,  may be a step-function
5 pct pts for responses ≥95%
10 pct pts for responses 90 to 95%
15 pct pts for responses 80 to 90%
For geometric mean titers, typical choices are 1.5-fold and 2-fold differences

14. Example of Non-inferiority Margins: MMRV Vaccine
Both antibody response rates and GMTs are co-primary endpoints
For measles, mumps, rubella, expected response rates are >95% and the noninferiority margins are 5 pct points
For varicella, the expected response rate is ~90% and the noninferiority margin is 10 pct points
For antibody titers, the margin is 1.5 fold-difference for the GMTs for each component

15. Analysis Approaches to Combination Vaccine Trials
Noninferiority analysis for response rates:
Asymptotic (e.g., Miettinen & Nurminen 1985)
Exact (e.g., Chan and Zhang 1999, Chan 2002, 2003)
Confidence interval (CI) for 
Test-based methods provide consistency with p-value
CI lower bound is > (-) if and only if the non-inferiority is demonstrated
Regression (ANCOVA) for GMT analysis

16. Power and Sample Size Determination
Asymptotic (Farrington and Manning 1990) or exact (Chan 2002) methods
Power is sensitive to the true responses
best case scenario is PT = PC (or GMTT = GMTC )
useful to assess power assuming PT (or GMTT) slightly less than PC (or GMTC)
Need to evaluate overall power for demonstrating success for all components

17. Consistency Lots Study
For licensure of a new vaccine, consistency of the manufacturing process must be supported by clinical trials using at least 3 lots of the vaccine
Objective of study is to show equivalence of clinical response among consistency lots
Evaluate both immune responses and safety
For combination vaccine, an active control may be included to demonstrate “assay sensitivity”
First demonstrate lot consistency
Then combine data from consistency lots to show noninferiority to active control

18. Analysis of Consistency Lots Study
Hypothesis of interest: H0: |Pi – Pj| ≥  for at least one pair (i, j) vs. H1: |Pi – Pj| <  for every pair
Same as testing 3 pairs of noninferiority hypotheses H0: |P1 – P2| ≥   H0A: P1 – P2 ≥  or H0B: P2 – P1 ≥ 
Test each hypothesis at one-sided 5% level
i.e., requiring 90% CI completely within [-, ]
Control overall type I error rate at 5%

19. Example: Consistency Lots Study for MMRV
Study enrolled ~4000 subjects
3 lots of MMRV and an active control (MMR+V)
1st step: showed consistency of 3 MMRV lots
Antibody response rates and GMTs for measles, mumps, rubella, and varicella
24 pairwise comparisons
2nd step: showed the combined responses of MMRV is noninferior to those of MMR + V
8 comparisons

20. Some Challenges of Developing Combination Vaccines
Statistical challenge with multiple endpoints
Clinical challenge with potential interaction among components on immunogenicity and safety
Formulation issues
Compatibility of components/Stability?

21. Multiplicity Challenge with Combination Vaccines
Major impact on power and sample size because of the need to show success on all components
Impact even more in consistency lots study
Accounting for correlation among components only increases power slightly
May consider multivariate analysis (e.g. T2 test)?

22. Multiplicity Hit on Power and Sample Size Combination Vaccine Studies
# of Vaccine Components ( = 0.1)
Power (%) with a fixed sample size
Sample Size Per Group Needed to Maintain 90% overall power for study 1 90
205 2 81
250 (22%↑) 4 66
293 (44%↑) 8 43
335 (63%↑) 12 28
357 (74%↑)

23. Challenges of Potential Interaction with Combination Vaccines
Potential interactions among components are difficult to predict
Immune responses may be lower
Safety concern may arise
A new dose-response study may be needed to re-establish the optimal dosing

24. Examples of Interactions: MMRV Vaccine
Interaction observed in early clinical studies
Suboptimal varicella responses
A new dose-response study (N>1500) established optimal potency range for varicella
Acceptable varicella responses
But more fever (≥102 F) and measles-like rash
A large database (N>5800) confirms that MMRV is well tolerated
Both fever and measles-like rash were transient and resolved with no long-term complications

25. Formulation Issues with ProQuadTM
M-M-R™ II is refrigerated product
VARIVAXTM is frozen product
European market needs refrigerated combination vaccine – how to develop?
First, develop frozen ProQuad to gain regulatory approval
Then, introduce refrigerated ProQuad via manufacturing supplement (a 4-6 months regulatory review time)

26. Summary
Combination vaccines provide substantial public health benefits
Immune marker and selection of endpoints and margins are important to the development of combination vaccines
Special considerations for studies of consistency lots
Potential interactions among components and multiplicity of endpoints pose special challenges

27. References
Blackwelder WC. Similarity/equivalence trials for combination vaccines. Combined Vaccines and Simultaneous Administration (ed by Williams JC,Goldenthal KL, Burns DL, Lewis BP), Ann New York Acad Sciences 1995;754:
Chan ISF and Zhang Z. Test-based exact confidence intervals for the difference of two binomial proportions. Biometrics 1999; 55:
Chan ISF. Power and sample size determination for non-inferiority trials using an exact method. Journal of Biopharmaceutical Statistics 2002; 12:
Chan ISF. Proving non-inferiority or equivalence of two treatments with dichotomous endpoints using exact methods. Statistical Methods in Medical Research 2003; 12 (1):
Chan ISF, Wang WWB, Heyse J. Vaccine clinical trials. Encyclopedia of Biopharmaceutical Statistics, 2nd Edition, 2003,
Farrington CP and Manning G. Test statistics and sample size formulae for comparative binomial trials with null hypothesis of non-zero risk difference or non-unity relative risk. Statistics in Medicine 1990; 9,
FDA: Guidance for industry for the evaluation of combination vaccines for preventable diseases: production, testing and clinical studies
Kuter B, Hartzel J, Schodel F. The Challenges of Developing a combination Measles, Mumps, Rubella & Varicella Vaccine (ProQuad™), ESPID symposium, Valencia, Spain, May 2005.
Miettinen O and Nurminen M. Comparative analysis of two rates. Statistics in Medicine 1985; 4,