Methodologies for vaccine safety surveillance. Nick Andrews, Statistics Unit Public Health England October 2015

Transcription

1 Methodologies for vaccine safety surveillance Nick Andrews, Statistics Unit Public Health England October 2015

2 Some dramas of the past 20 years which do you think turned out to be real adverse reactions? Reduced Immunity / allergy Hep B vaccine MMR Type 1 Diabetes Chronic Fatigue Autism Aseptic Meningitis HPV vaccine Intussusception Convulsions Neurological problems Guillane Barre Syndrome Flu vaccine Rotavirus Vaccine Asthma Exacerbation Mercury in vaccines H1N1 Pandemic Vaccine Narcolepsy

3

4

5 Talk Overview The components of vaccine safety surveillance Epidemiological methods Example and comparisons Conclusions

6 Plausibility, other data/methods, experts, other risks, interval from vaccine,. Vaccine Safety Assessment Components Vaccine Trials reactogenicity Licensure and use Individual causality assessment Pharmacovigilance (passive/active): hypothesis generation, RAPID Epidemiological studies (hypothesis testing) Signal Strengthening/ assessment Priority?

7 Passive Surveillance systems Often part of Pharmacovigilance by regulatory authorities Many countries have a system in place (UK Yellow Card) Reports from health professionals / public are monitored. e.g. by comparing rates to historical rates or other vaccines (proportional reporting ratios). Some countries (e.g. US VAERS system) have stimulated passive reporting forms sent to all physicians for return

8 Active Surveillance example! Vaccine safety data link. Using data from US Health Maintenance Organisations! Rapid Cycle analysis e.g.comparing observed convulsions 0-1 days post trivalent influenza vaccine to expected numbers each week based on histyorcial data. Study by TSE et al, Vaccine Could look at many different outcomes this way

9 Signal strengthening Signals may come from many sources recent example HPV and Guillane Barre Syndome from a French cohort study What can be done to rapidly assess a signal? Go through the usual causality assessment steps but likely lots of missing information. WHO has guidelines. Look at pharmacovigilance data (if that was not the source of the signal). Ecological studies look in hospital / GP databases at disease rates over time. Observed v Expected studies within databases that contain vaccination data where reporting bias is less likely. Ideally already be looking at possible events of interest in rapid cycle analysis.

10 Rapid Ecological study of Guillane Barre Syndome and HPV vaccine (done in a few days) Hospitalisations for GBS by age and period and whether vaccine scheduled that year (red) No increased risk seen

11 Epidemiological studies for Investigating adverse events Design issues Exact question/vaccine/population, case definition, timing relative to vaccination, confounders, how rare. Data sources For cases, vaccination, confounders (?linkage) Methods Cohort, case-control, case-coverage, case-only (self controlled case series) BEST ONE OFTEN DEPENDS ON DATA SOURCES AND DESIGN ISSUES

12 Comparing designs: Example1: Rotavirus and Intussusception October 1998: an anti-rotavirus vaccine is launched in the USA for use in infants (3 doses). May 1999: the vaccination programme is suspended following 9 reports of intussusception temporally associated with vaccination. An epidemiological investigation is launched.

13 Main design was a case-control study 382 cases and 1657 controls, matched/controlled for sex, age, hospital of birth, proxies for socio-economic position. But control selection difficult could there be residual confounding. So also considered just looking at all the cases (432 could be used) for the timing of any vaccines using self controlled case series.

14 Self Controlled Cases-Series (SCCS) Just obtain data on cases Design For each individual each day and event in the study period will fall inside or outside the risk period. vaccination Event Jan 01 Dec 01 risk period Relative incidence calculated in a similar way to a cohort study but analysis is conditional Poisson regression i.e. data are not aggregated across individuals so each individual has a set of exposure periods and events

15 Interval between vaccination and intussusception in 74 vaccinated cases Murphy et al (2001) NEJM

16 Results for the first dose Risk period (days) Case-control SCCS (12.6, 110) 58.9 (31.7, 110) (2.4, 27.6) 9.4 (3.9, 22.3) (0.2, 5.4) 2.3 (0.5, 10.2) Conclusion: Possibly some residual confounding in the case-control design Almost all studies of intussusception since this have used the SCCS design you only need the cases. SCCS implicitly controls for non-time varying confounders.

17 Example2: MMR and Autism studies Study Sample size RI / OR SCCS (UK 1999) Cohort (Denmark -2002) Case-control (UK 2004) 95% CI 357 cases 0.88 (0.40, 1.95) children 316 cases 1294 cases 4469 controls 0.92 (0.68, 1.24) 0.86 (0.68, 1.09) In this case SCCS worked well, although it is more suited to clearer acute onsets.

18 Example3: Asthma exacerbation and flu vaccine Kramarz et al, Arch. Fam. Med. 2000, 9: Cohort and case series studies in asthmatic children aged 1 6 years in 1995/6. Risk period: 2 weeks after flu vaccine. Method Sample size RI 95% CI Cohort, unadjusted (2.55, 4.15) Cohort, adjusted (1.08, 1.77) Case series 2075 cases 0.98 (0.76, 1.27) The cohort results are subject to indication bias. The case series results are unaffected by this bias.

19 Example4: GBS, flu vaccine and flulike illness Stowe et al, Am. J. Epidemiol. 2008, 169: Observation period: all time within GPRD in Two types of exposures: flu vaccination and flu-like illness. Risk periods: 0-30, 31-60, days after vaccine/onset Pre-exposure risk period: 2 weeks Age groups: 12 periods over years Seasonal groups: calendar month Repeat episodes: included if > 6 months separation

20 Results 775 distinct episodes in 690 individuals Flu vaccine: 0 30 days: RI = 0.58 (0.18, 1.86) 0 90 days: RI = 0.76 (0.41, 1.40) Influenza-like illness: 0 30 days: RI = (9.37, 29.54) 0 90 days: RI = 7.35 (4.36, 12.38)

21 Interval between influenza-like illness and GBS From: Stowe et al, Am. J. Epidemiol. 2008, 169:

22 Example 5: Pandemrix vaccine and Narcolepsy Miller et al, BMJ 2013 Pandemrix (AS03 adjuvanted H1N1 vaccine) used widely in Europe Signal of possible narcolepsy association from Sweden / Denmark Epi studies to date have been cohort, case-control, casecoverage and SCCS.

23 Choice of study design (UK) SAMPLE SIZE calculations suggested we needed to cover a large proportion of cases in England. Cohort > No national database for vaccinations. Case-control> Possible but control selection and cost/ ethical permissions issues with getting controls. SCCS> Yes although potential problems with defining risk interval and having enough follow up time for power. Case-coverage>Yes since we have good coverage data in GP databases such as RCGP.

24 Study Design Age: 4 to 18 year olds at diagnosis Period: Onset from Jan 2008 and diagnosed by the time of the visit. Case finding: 23 sleep centres Validation: of cases using ICSD-2 criteria by 3 experts using notes obtained at centre visits. Key index date: Onset of excessive daytime sleepiness (EDS) / cataplexy as reported in case notes or by a GP Vaccination history: obtained from a letter to the GP. Details of being in a risk group targeted for vaccination were also obtained from GPs. Case - coverage compares odds of vaccination in cases to the age and risk group matched population

25 Non risk group RCGP Coverage data for casecoverage design Risk group

26 Cases by EDS date and vaccination status

27 Results vaccine association OR = 14.4, 95% CI( ) for vaccinated at any time prior to onset. Attributable risk: 1.9 per 100,000 doses. Other designs (results here based on first symptoms for children and Pandemrix): France case matched to hospital controls OR = 21.5 ( ) Finland retrospective cohort design RI ~ 25 (8-80) UK SCCS did not work well because no clear risk window, lack of control unexposed time and correlation of period effects and vaccine effects as all vaccine given over a few months.

28 Design Pros and Cons Case Control Pros can get detailed information on cases and controls Cons control selection may lead to bias Cohort Pros direct estimates of risks, high power Cons may be limited data on possible confounders, may be difficult to construct the cohort (linkage). Self Controlled Case Series Pros just need cases so cheaper. Automatic adjustment for nontime varying confounders Cons usually need a risk window to be specified, sometimes colinearity of vaccine and age/time effects. Case-Coverage Pros simple to use with routine data without linkage. Cons usually limited matching to confounders

29 Conclusions Post licensure vaccine safety surveillance is an important component of a vaccine programme It is important to be able to perform controlled epidemiological studies rapidly and to be aware of potentially confounding / bias Record linkage and the SCCS method has proved an excellent tool for such studies. Cohort and other designs such as case-coverage are also required for some events where SCCS is not ideal. NEW QUESTIONS KEEP ARISING!

30 Acknowledgements! PHE: Liz Miller, Julia Stowe, Pauline Kaye! Royal Free: Brent Taylor! Open University: Paddy Farrington, Heather Whitaker

31 EXTRA SLIDES: Useful resources WHO Global Vaccine Safety Initiative: vaccine_safety/en/ FDA: Guidance for Industry Good Pharmacovigilance Practices and Pharmacoepidemiologic Assessment index.htm ADVANCE consortium looking at vaccine benefit risk SCCS Website: Created by Heather Whitaker to be updated in the next year or so Tutorial paper: Whitaker et al., Statist. Med. 2006, 25: Useful overview of case-only methods: Farrington, Vaccine 2005, Control without separate controls:

32 Comparing designs