Four different study designs to evaluate vaccine safety were equally validated with contrasting limitations (original) (raw)
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Comparison of epidemiologic methods for active surveillance of vaccine safety
Vaccine, 2008
We performed a simulation study to compare four study designs [(matched-cohort, vaccinated-only (risk-interval) cohort, case-control, and self-controlled case-series (SCCS)] in the context of vaccine safety active surveillance. For each combination of various incidence levels (3, 30, 300 per 10(5) person-years) and relative risks (RR 1.5-18), 100 case sets were infused into the cohort, matching 10(5) vaccinated to 10(5) unvaccinated on age and gender. The matched-cohort was converted into weekly accumulated data intervals with the other three study design samples drawn from each. Analyses were with appropriate regression models. The signal detection time was the first week where the log likelihood ratio (LLR) exceeded the upper boundary from the MaxSPRT sequential analysis method. Empirical type I (false positive) and type II (power) error rates and risk estimate bias were also calculated. The matched-cohort design exhibited the shortest detection time, lowest false positive rate and highest empirical power followed by the risk-interval cohort, SCCS, and case-control. In most monitoring weeks, the risk estimate bias was smallest for the cohort, followed by the risk-interval, SCCS and case-control designs. The cohort study design performed the best in the sequential analysis of active surveillance for vaccine safety. The risk-interval cohort and SCCS designs offer reasonable and efficient alternatives, especially if selection bias is a concern. Future research should address seasonality or age effects.
Case-Cohort Analysis of Case-Coverage Studies of Vaccine Effectiveness
American Journal of Epidemiology, 1995
Evaluation of vaccine field effectiveness may be performed by combining surveillance data on incident cases with an immunization coverage survey. Although many methods have been used for the analysis of studies of similar design, they are not always desirable or optimal. The authors discuss these approaches and propose use of a case-cohort analysis for such a study design when appropriate. The case-cohort analytic approach is illustrated with data from studies of a vaccine for Haemophilus influenzae type b (Hib) disease in children living on a southwestern Native American reservation during 1988-1993. Am J Epidemiol 1995; 142: 1000-6. biometry; epidemiologic methods; follow-up studies; research design; statistics; vaccination Postlicensure or postcampaign evaluation of vaccine is often undertaken to measure vaccine effectiveness under field conditions. There are several observational study designs that may be used to perform such evaluations, including retrospective cohort studies, "screening" investigations, case-control studies, and case-exposure studies (1). The latter design, when applied to vaccine evaluation, has been given the term "case-coverage" design (Brogan et al., unpublished manuscript) since it combines case ascertainment with coverage survey results. The basic structure of the case-coverage design is much like that of a case-control study. In a specified geographic area and time period, cases of a disease are identified through a surveillance and reporting system. The vaccination status of each case at the time of disease onset is determined through inspection of vaccination records. The coverage survey consists of determining the vaccination status of a group of subjects
Case-control vaccine effectiveness studies: Data collection, analysis and reporting results
Vaccine, 2017
The case-control methodology is frequently used to evaluate vaccine effectiveness post-licensure. The results of such studies provide important insight into the level of protection afforded by vaccines in a 'real world' context, and are commonly used to guide vaccine policy decisions. However, the potential for bias and confounding are important limitations to this method, and the results of a poorly conducted or incorrectly interpreted case-control study can mislead policies. In 2012, a group of experts met to review recent experience with case-control studies evaluating vaccine effectiveness; we summarize the recommendations of that group regarding best practices for data collection, analysis, and presentation of the results of case-control vaccine effectiveness studies. Vaccination status is the primary exposure of interest, but can be challenging to assess accurately and with minimal bias. Investigators should understand factors associated with vaccination as well as the...
Vaccine, 2017
Case-control studies are commonly used to evaluate effectiveness of licensed vaccines after deployment in public health programs. Such studies can provide policy-relevant data on vaccine performance under 'real world' conditions, contributing to the evidence base to support and sustain introduction of new vaccines. However, case-control studies do not measure the impact of vaccine introduction on disease at a population level, and are subject to bias and confounding, which may lead to inaccurate results that can misinform policy decisions. In 2012, a group of experts met to review recent experience with case-control studies evaluating the effectiveness of several vaccines; here we summarize the recommendations of that group regarding best practices for planning, design and enrollment of cases and controls. Rigorous planning and preparation should focus on understanding the study context including healthcare-seeking and vaccination practices. Case-control vaccine effectivenes...
International Journal of Epidemiology, 1984
Fine P E M. Assessment of the protective efficacy of vaccines against common diseases using case-control and cohort studies. Internationa/Journal of Epidemiology 1984,13:87-93. Case-control and cohort studies may be employed to assess the protective efficacy of vaccines. The appropriate measure of vaccine efficacy is shown to depend upon the mode of action of the vaccination. Two models of vaccine action are considered. In the first, vaccination is assumed to reduce the instantaneous disease-rate in the total vaccinated population by a constant proportion and, in the second, vaccination is assumed to render a constant proportion of individuals totally immune from the disease. The implications of these two models on the behaviour of different measures of vaccine efficacy in cohort studies is explored. It is shown that the design of case-control studies to measure vaccine efficacy is dependent upon which model is considered appropriate. In particular, under the second model, individuals who have already had the disease under study should not be excluded from the control group.
Use of Fixed Effects Models to Analyze Self-Controlled Case Series Data in Vaccine Safety Studies
Journal of Biometrics & Biostatistics, 2012
Conditional Poisson models have been used to analyze vaccine safety data from self-controlled case series (SCCS) design. In this paper, we derived the likelihood function of fixed effects models in analyzing SCCS data and showed that the likelihoods from fixed effects models and conditional Poisson models were proportional. Thus, the maximum likelihood estimates (MLEs) of time-varying variables including vaccination effect from fixed effects model and conditional Poisson model were equal. We performed a simulation study to compare empirical type I errors, means and standard errors of vaccination effect coefficient, and empirical powers among conditional Poisson models, fixed effects models, and generalized estimating equations (GEE), which has been commonly used for analyzing longitudinal data. Simulation study showed that both fixed effect models and conditional Poisson models generated the same estimates and standard errors for time-varying variables while GEE approach produced different results for some data sets. We also analyzed SCCS data from a vaccine safety study examining the association between measles mumps-rubella (MMR) vaccination and idiopathic thrombocytopenic purpura (ITP). In analyzing MMR-ITP data, likelihood-based statistical tests were employed to test the impact of time-invariant variable on vaccination effect. In addition a complex semi-parametric model was fitted by simply treating unique event days as indicator variables in the fixed effects model. We conclude that theoretically fixed effects models provide identical MLEs as conditional Poisson models. Because fixed effect models are likelihood based, they have potentials to address methodological issues in vaccine safety studies such as how to identify optimal risk window and how to analyze SCCS data with misclassification of adverse events
Observational methods in epidemiologic assessment of vaccine effectiveness
Communicable diseases intelligence quarterly report, 2002
Observational methods are important in the measurement of vaccine effectiveness (VE) as experimental designs cannot be used for measurement of vaccines already on the vaccination schedule. Furthermore, efficacy measured in clinical trials under ideal conditions may differ to effectiveness in the field under non-ideal conditions and in different populations. In addition to post-licensure surveillance, observational VE studies are particularly important when disease incidence does not predictably decrease with increased vaccine coverage, when high proportions of vaccine failure among reported cases suggest a problem with the vaccine or when issues arise that were not predicted in pre-licensure evaluations. Commonly used study types for evaluating VE include cohort studies, household contact studies, case-control studies, the screening method and case-cohort studies. There are many potential biases in all observational VE studies which should be considered in the study design and analy...
Vaccine, 2019
Background: Summary measures such as number of vaccine antigens, number of vaccines, and vaccine aluminum exposure by the 2 nd birth day are directly related to parents' concerns that children receive too many vaccines over a brief period. High correlation among summary measures could cause problems in regression models that examine their associations with outcomes. Objectives: to evaluate the performance of multiple regression models using summary measures as risk factors to simulated binary outcomes. Methods: We calculated summary measures for a cohort of 232,627 children born between 1/1/2003 and 9/31/2013. Correlation and variance inflation factors (VIFs) were calculated. We conducted simulations 1) to examine the extent to which a signal can be detected using a summary measure other than the true risk factor; 2) to evaluate the performance of multiple regression models including true and redundant risk factors; 3) to evaluate the performance of multiple regression models when all three were risk factors; 4) to examine the performance of multiple regression models with incorrect relationship between risk factors and outcome. Results: These summary measures were highly correlated. VIFs were 7.14, 6.25 and 2.17 for number of vaccine antigens, number of vaccines, and vaccine aluminum exposure, respectively. In
American journal of epidemiology, 2015
The Postlicensure Rapid Immunization Safety Monitoring Program, the vaccination safety monitoring component of the US Food and Drug Administration's Mini-Sentinel project, is currently the largest cohort in the US general population for vaccine safety surveillance. We developed a study design selection framework to provide a roadmap and description of methods that may be utilized to evaluate potential associations between vaccines and health outcomes of interest in the Postlicensure Rapid Immunization Safety Monitoring Program and other systems using administrative data. The strengths and weaknesses of designs for vaccine safety monitoring, including the cohort design, the case-centered design, the risk interval design, the case-control design, the self-controlled risk interval design, the self-controlled case series method, and the case-crossover design, are described and summarized in tabular form. A structured decision table is provided to aid in planning of future vaccine sa...
Methods for addressing “innocent bystanders” when evaluating safety of concomitant vaccines
Pharmacoepidemiology and Drug Safety, 2018
The need to develop methods for studying the safety of childhood immunization schedules has been recognized by the Institute of Medicine and Department of Health and Human Services. The recommended immunization schedule includes multiple vaccines in a visit. A key concern is safety of concomitant (same day) versus separate day vaccination. This paper addresses a methodological challenge for observational studies of the safety of concomitant vaccination. We propose a process for distinguishing which of several concomitantly administered vaccines is responsible for increased risk of an adverse event while adjusting for confounding due to relationships between effect modifying risk factors and concomitant vaccine combinations. We illustrate the approach by reexamining the known increase in risk of seizure 7-10 days after measles-mumps-rubella (MMR) vaccination and evaluating potential independent or modifying effects of other vaccines. Initial analyses suggested DTaP had an independent and potentiating effect on seizure. After accounting for the relationship between age and vaccine combination, there was no evidence for increased risk of seizure with same day administration; incidence rate ratio, 95% confidence interval 1.2 (0.9, 1.6), p-value = 0.226. We have shown that when investigating safety of concomitant vaccination, it can be critically important to adjust for relationships between effect modifying risk factors and vaccine combination.