Immunological Correlates of Protection: Statistical Perspectives and Methods

Transcription

1 Immunological Correlates of Protection: Statistical Perspectives and Methods Andrew J Dunning Sanofi Pasteur Fondation Mérieux 21 September

2 Correlate of Protection Immunological assay whose values correlate with protection from disease Become established, i.e. generally accepted, by references in standard texts (e.g. Plotkin/Vaccines; WHO Immunological Basis for Immunization Series) regulatory guidance (e.g. FDA/diphtheria, tetanus; FDA/influenza; WHO/pneumococcal) statements in vaccine package inserts/summary of product characteristics (regulatory approval) 2

3 Correlate of Protection Questions Is a correlate of protection a level at which all individuals are protected? or 90% are protected? or a population average (50% protected)? Is it level to be achieved post-vaccination, when immune response is at its highest (possibly more relevant in vaccines research) or pre-exposure (possibly more relevant in general scientific terms)? If an individual achieves a protective level, are they protected at the time the sample is taken for 1 year, 2 years, 5 years, 10 years for life 3

4 Correlate of Protection - Questions Is the threshold required for protection the same for infants, children, adolescents, adults, elderly? Does protective level depend on etiology of immune response being measured? natural infection killed vaccine live attenuated vaccine asymptomatic carriage How may these questions be answered in a quantitative sense? 4

5 Ppn. Developing Disease Björkholm/diphtheria (1986) / IU/mL 0.1 IU/mL 1.0 IU/mL 0.2 1/7? 0.0 0/6 0/21 <= Diphtheria antitoxin IU/mL 5

6 Titer-Specific Rates of Disease Similar methods inspection of titer-specific rates of disease: Ipsen/diphtheria 1946 Goulon/tetanus 1972 Neumann/measles 1985 Chen/measles 1990 White/varicella 1992 See discussion in Siber 1997 Selected level not necessarily predictive of vaccine efficacy 6

7 Ppn. Developing Disease Logistic regression: e.g. White/varicella / /55 16/186 16/ / < / Six-week gpelisa Titer / /988 >=20 7

8 Logistic regression - limitations Conclusion depends on length of surveillance and prevalence of disease Limited interpretability for every increase of 1 in log e (gp ELISA) the risk of disease decreased by 51.7% Models rate of disease, but interest is in protection Examples: Piedra (2003); Stehr (1998); Cherry (1998) Gustafsson (1996); Storsaeter (1998); Dagan (2005); Rapola (2003) see also Chan (2002) 8

9 7-valent Pneumococcal Conjugate 7-valent pneumococcal conjugate vaccine efficacy trial (Black 2000) 38,000 infant subjects, randomized 1:1 to 7-valent pneumococcal conjugate vaccine or placebo subsets of 75 vaccinees and placebo recipients provided samples for assay 40 cases of invasive pneumococcal disease (none among assay subset) Titer-specific rates of disease cannot be used titers of cases not known Logistic regression cannot be used no cases in immunogenicity subset 9

10 7v-PVC: Method of Chang & Kohberger Protective threshold is assay value at which relative risk of being below the value equals relative risk of disease (Jódar 2003) i.e. find t P such that: where t t P t P P t : P t t P tp vaccinated not vaccinated assay value (titer) protective threshold P Disease vaccinated P Disease not vaccinated 10

11 Distribution 7v-PVC: Method of Chang & Kohberger Susceptible Protective threshold = 0.18 Protected VE = 97.4% Cases = 39 Cases = 1 RR = = % 2.3% Pneumococcal IgG ELISA Non-vaccinees Vaccinees 11

12 7v-PVC: Method of Chang & Kohberger Lead to adoption by WHO of 0.35 g/ml IgG reference level after pneumococcal conjugate vaccination (WHO 2005) Method also used for 1:8 SBA titer following meningococcal C conjugate vaccination (see Andrews 2003) Samples from subset of subjects sufficient Predictive of vaccine efficacy Population average measure Assumes same threshold for vaccinees and non-vaccinees 12

13 Scaled logit model Bridges from disease to protection Incorporates exposure into logistic regression Useful paradigm: Both exposure and susceptibility (i.e. lack of protection) are necessary for disease to occur, and together they are sufficient P Disease P Exposure 1 P Protected (same paradigm applied in previous method) Refs./examples: Dunning 2006, Forrest 2008, Nauta 2009, Coudeville

14 Ppn. Developing Disease Scaled Logit Model (varicella data) /113 exposure parameter = /55 16/186 logistic regression scaled logit model 16/ / < / Six-week gpelisa Titer / /988 >=20 14

15 Protection Scaled Logit Protection Curve % C.I 0.6 t_ % C.I 0.2 t_ Six-week gpelisa Titer 15

16 Scaled logit model Corresponds more closely to expectations in many cases Estimates protection rather than rate of disease Estimate of protection independent of length of surveillance or disease incidence Requires rich dataset; model fit not always achieved Protection curve conditional on exposure parameter; reliability of protection curve depends on small variance of estimated exposure parameter 16

17 Principal Surrogate method Experimental method Because a subject cannot be assigned to an assay value, a designed experiment to test the relationship between assay value and disease cannot be devised Principal surrogate method applies causal inference methods Special study design or additional data needed Applied to consistency question see Gilbert 2007, Follmann 2006 (and next slide) 17

18 Classification scheme Correlate of Risk (weak) high and low assay values associated with low and high risk of disease Specific Surrogate of Protection (medium) reliably predicts vaccine efficacy from assay values in similar setting relationship between assay value and protection consistent for vaccinees and placebo recipients General Surrogate of Protection (strong) reliably predicts vaccine efficacy from assay values in different settings consistent for any immunological history e.g. different kinds of vaccine, immunity from natural infection, asymptomatic carriage, etc. see Qin 2007, Sadoff

19 Challenges: Statistical Methods Method for finding threshold in homogenous subjects (i.e. no vaccinee/non-vaccinee distinction) (see illustration next slide) Extension of exposure-based, continuous models (e.g. scaled logit) test for consistency; case-cohort design (see Qin 2008); direct method for CI for t 50 and t 90 ; tractable form of Nauta Integral (see Nauta 2009); more flexible/non-parametric models; goodness of fit 19

20 Ppn. Developing Disease e.g. Swedish Pertussis Pertactin data /18 8/ /53 16/27 13/ / /15 2/15 2/ /6 0/1 0/ Pertussis PRN (Swedish) 20

21 Challenges: Statistical Methods Two threshold method of Chang & Kohberger without same threshold assumption Principal surrogate methodology applied to homogenous subjects (i.e. no vaccinee/ placebo recipient distinction) Link post-vaccination protection to preexposure protection (see illustration in following slide) 21

22 Assay Value Challenges: Post-vaccination/pre-exposure post-vaccination assay disease pre-exposure assay 0 0 Time 22

23 Challenges: Technical Protection is mediated through multiple immunological mechanisms of action, but assays only measure a single characteristic (see illustration next slide) Kinetics of immune response poorly understood (see illustration next slide) Despite efforts to standardize assays, differences in immune responses to same vaccine observed in different trials Lack of cases among vaccinees, and lack of immune response among placebo recipients renders demonstration of consistency problematic 23

24 Assay Value Challenges: Mechanisms of action/kinetics 0 0 Time 24

25 Challenges: Data Limited opportunities to collect data Both immunogenicity and disease occurrence data needed Vaccine licensure efficacy trial one chance only? may be unethical to conduct placebocontrolled trial post-licensure incentivize sponsor to look for correlate Observational study cost reliable surveillance Challenge study ethical issues Acute-phase study only certain diseases timing problematic 25

26 Challenges: What s possible? Sufficient assays cannot be conducted to fully describe immune response Specific correlates should be sought, specific to and assay timing (post-vaccination, pre-exposure) stimulus (type of vaccine, etc.) population (infants, adults, elderly, etc.) case definition surveillance period (for post-vaccination assays) as well as the assay itself 26

27 Questions? 27

28 Acknowledgements/Collaboration Dr. Lennart Gustafsson, for making available the Swedish pertussis datasets Dr. Jo White, for assistance with the varicella dataset Cindy Chen, Hexin Zhang, Li Qin, Kamal Desai and Fabrice Bailleux - Threshold Methods for Immunological Correlates of Protection Research Group Jennifer Kensler, Laurent Coudeville, Amit Bhaumik and Fabrice Bailleux - Extensions to the Scaled Logit Model for Immunological Correlates of Protection Research Group 28

29 References Plotkin SA, Orenstein WA, Offit PA. Vaccines (5th edition). Elsevier World Health Organization, Department of Immunization, Vaccines and Biologicals. Immunological basis for immunization series; accessed at U.S. Department of Health and Human Services, Food and Drug Administration. Biological Products; Bacterial Vaccines and Toxoids; Implementation of Efficacy Review; Proposed Rule. Federal Register 1985; 50(240): U.S. Department of Health and Human Services, Food and Drug Administration, Center for Biologics Evaluation and Research. Clinical Data Needed to Support the Licensure of Seasonal Inactivated Influenza Vaccines, May 2007 World Health Organization. Recommendations for the production and control of pneumococcal conjugate vaccines. Published as Annex 2 to WHO Technical Report Series, No ;

30 References Björkholm B, Böttiger M, Christenson B, Hagberg L. Antitoxin antibody levels and the outcome of illness during an outbreak of diphtheria among alcoholics. Scandinavian Journal of Infectious Diseases 1986; 18(3):235-9 Ipsen J. Circulating antitoxin at the onset of diphtheria in 425 patients. Journal of Immunology 1946; 54: Goulon M, Girard O, Grosbuis S, Desormeau JP, Capponi MF. Antitetanus antibodies: Assay before anatoxinotherapy in 64 tetanus patients. Nouveau Presse Medicin 1972; 1(45): Neumann PW, Weber JM, Jessamine AG, O'Shaughnessy MV. Comparison of measles antihemolysin test, enzyme-linked immunosorbent assay, and hemagglutination inhibition test with neutralization test for determination of immune status. Journal of Clinical Microbiology 1985; 22(2):296-8 Chen RT, Markowitz LE, Albrecht P, Stewart JA, Mofenson LM, Preblud SR, Orenstein WA. Measles antibody: reevaluation of protective titers. Journal of Infectious Diseases 1990; 162(5):

31 References White CJ, Kuter BJ, Ngai A, Hildebrand CS, Isganitis KL, Patterson CM,Capra A, Miller WJ, Krah DL, Provost PJ, Ellis RW, Calandra GB. Modified cases of chickenpox after varicella vaccination: correlation of protection with antibody response. Pediatric Infectious Disease Journal 1992; 11:19-23 Siber GR. Methods for estimating serological correlates of protection. Developments in Biological Standardization 1997; 89: Piedra PA, Jewell AM, Cron SG, Atmar RL, Glezen WP. Correlates of immunity to respiratory syncytial virus (RSV) associated-hospitalization: establishment of minimum protective threshold levels of serum neutralizing antibodies. Vaccine 2003; 21(24): Stehr K, Cherry JD, Heininger U, Schmitt-Grohé S, Überall M, Laussucq S, Eckhardt T, Meyer M, Engelhardt R, Christenson P, the Pertussis Vaccine Study Group. A comparative efficacy trial in Germany in infants who received either the Lederle/Takeda acellular pertussis component DTP (DTaP) vaccine, the Lederle whole-cell component DTP vaccine, or DT vaccine. Pediatrics 1998; 101(1):

32 References Cherry JD, Gornbein J, Heininger U, Stehr K. A search for serologic correlates of immunity to Bordetella pertussis cough illnesses. Vaccine 1998; 16(20): Gustafsson L, Hallander HO, Olin P, Reizenstein E, Storsaeter J. A controlled trial of a two-component acellular, a fivecomponent acellular, and a whole-cell pertussis vaccine. New England Journal of Medicine 1996; 334(6): Storsaeter J, Hallander HO, Gustafsson L, Olin P. Levels of anti-pertussis antibodies related to protection after household exposure to Bordetella pertussis. Vaccine 1998; 16: Dagan R, Givon-Lavi N, Fraser D, Lipsitch M, Siber GR, Kohberger R. Serum serotype-specific pneumococcal anticapsular immunoglobulin g concentrations after immunization with a 9-valent conjugate pneumococcal vaccine correlate with nasopharyngeal acquisition of pneumococcus. Journal of Infectious Diseases 2005; 192(3): Rapola S, Jäntti V, Eerola M, Mäkelä PH, Käyhty H, Kilpi T. Anti-PsaA and the risk of pneumococcal AOM and carriage. Vaccine 2003; 21:

33 References Black S, Shinefield H, Fireman B, Lewis E, Ray P, Hansen JR, Elvin L, Ensor KM, Hackell J, Siber G, Malinoski F, Madore D, Chang I, Kohberger R, Watson W, Austrian R, Edwards K. Efficacy, safety and immunogenicity of heptavalent pneumococcal conjugate vaccine in children. Pediatric Infectious Disease Journal 2000; 19(3): Jódar L, Butler J, Carlone G, Dagan R, Goldblatt D, Käyhty H, Klugman K, Plikaytis B, Siber G, Kohberger R, Chang I, Cherian T. Serological criteria for evaluation and licensure of new pneumococcal conjugate vaccine formulations for use in infants. Vaccine 2003; 21(23): Andrews N, Borrow R, Miller E. Validation of serological correlate of protection for meningococcal C conjugate vaccine by using efficacy estimates from postlicensure surveillance in England. Clinical & Diagnostic Laboratory Immunology 2003; 10(5):

34 References Dunning AJ. A model for immunological correlates of protection. Statistics in Medicine 2006; 25: Forrest BD, Pride MW, Dunning AJ, Capeding MR, Chotpitayasunondh T, Tam JS, Rappaport R, Eldridge JH, Gruber WC. Correlation of cellular immune responses with protection against culture-confirmed influenza virus in young children. Clinical and Vaccine Immunology 2008 Jul;15(7): Nauta JJ, Beyer WE, Osterhaus AD. On the relationship between mean antibody level, seroprotection and clinical protection from influenza. Biologicals 2009; 37(4): Coudeville L, Bailleux F, Riche B, Megas F, André P, Ecochard R. Relationship between haemagglutination-inhibiting antibody titres and clinical protection against influenza: development and application of a bayesian random-effects model. BMC Medical Research Methodoogy 2010; 10(1):18 34

35 References Follmann D. Augmented designs to assess immune response in vaccine trials. Biometrics 2006; 62(4): Gilbert PB, Qin L, Self SG. Evaluating a surrogate endpoint at three levels, with application to vaccine development. Statistics in Medicine 2008; 27(23): Qin L, Gilbert PB, Corey L, McElrath MJ, Self SG. A framework for assessing immunological correlates of protection in vaccine trials. Journal of Infectious Diseases 2007; 196(9): Sadoff JC, Wittes J. Correlates, surrogates, and vaccines. Journal of Infectious Diseases 2007; 196(9):

36 Backup slides 36

37 Correlate of Protection Uses Protective thresholds used for assessment of individual protection as alternative to vaccine efficacy trial as means of quantifying response to new vaccine candidate to compare immunogenicity of two vaccines noninferiority trial vaccine non-interference trial vaccine lot consistency trial estimation of duration of protection 37

38 Surrogate endpoint Other approaches Surrogate endpoint (Prentice criteria) Diagnostic testing (sensitivity and specificity) Surrogate Endpoint Correlate of Protection True endpoint + + Disease + 0 t < t P 0 t t P 0 38

39 log-odds ratio Interpretation: Stephen Senn 31 Placebo-Controlled Trials of Cimetidine Significant (Yates) Not-significant Upper control limit Lower control limit significance boundary standard error 39