Monitoring signals for vaccine safety: the assessment of individual adverse event reports by an expert advisory committee. Advisory Committee on Causality Assessment (original) (raw)
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Serious illnesses or even deaths may rarely occur after childhood vaccinations. Public health programs are faced with great challenges to establish if the events presenting after the administration of a vaccine are due to other conditions, and hence a coincidental presentation, rather than caused by the administered vaccines. Given its priority, the Global Advisory Committee for Vaccine Safety (GACVS) commissioned a group of experts to review the previously published World Health Organization (WHO) Adverse Event Following Immunization (AEFI) causality assessment methodology and aide-memoire, and to develop a standardized and user friendly tool to assist health care personnel in the processing and interpretation of data on individual events, and to assess the causality after AEFIs. We describe a tool developed for causality assessment of individual AEFIs that includes: (a) an eligibility component for the assessment that reviews the diagnosis associated with the event and identifies the administered vaccines; (b) a checklist that systematically guides users to gather available information to feed a decision algorithm; and (c) a decision support algorithm that assists the assessors to come to a classification of the individual AEFI. Final classification generated by the process includes four categories in which the event is either: (1) consistent; (2) inconsistent; or (3) indeterminate with respect of causal association; or (4) unclassifiable. Subcategories are identified to assist assessors in resulting public health decisions that can be used for action. This proposed tool should support the classification of AEFI cases in a standardized, transparent manner and to collect essential information during AEFI investigation. The algorithm should provide countries and health officials at the global level with an instrument to respond to vaccine safety alerts, and support the education, research and policy decisions on immunization safety.
F1000Research
The World Health Organisation (WHO) has recently revised how adverse events after immunization (AEFI) are classified. Only reactions that have previously been acknowledged in epidemiological studies to be caused by the vaccine are classified as a vaccine-product–related-reaction. Deaths observed during post-marketing surveillance are not considered as ‘consistent with causal association with vaccine’, if there was no statistically significant increase in deaths recorded during the small Phase 3 trials that preceded it. Of course, vaccines noted to have caused a significant increase in deaths in the control-trials stage would probably not be licensed. After licensure, deaths and all new serious adverse reactions are labelled as ‘coincidental deaths/events’ or ‘unclassifiable’, and the association with vaccine is not acknowledged. The resulting paradox is evident. The definition of causal association has also been changed. It is now used only if there is ‘no other factor intervening ...
Evaluation of adverse effects of vaccines: the case-control approach
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When the hypothesis of a link between vaccination and a possible adverse outcome arises, further investigation is required to confirm or refute the suspicion. Given the rarity of most serious adverse effects, a case-control approach will often be chosen. This paper discusses aspects of the design, analysis and interpretation of case-control studies to evaluate vaccine adverse effects. Potential biases (and how to minimise such biases) in the selection of cases and assessment of vaccine exposure and the potential for confounding are discussed. Finally the increasing use of electronic databases in the evaluation of vaccine adverse effects is considered.
Algorithm to assess causality after individual adverse events following immunizations
Vaccine, 2012
Assessing individual reports of adverse events following immunizations (AEFI) can be challenging. Most published reviews are based on expert opinions, but the methods and logic used to arrive at these opinions are neither well described nor understood by many health care providers and scientists. We developed a standardized algorithm to assist in collecting and interpreting data, and to help assess causality after individual AEFI. Key questions that should be asked during the assessment of AEFI include: Is the diagnosis of the AEFI correct? Does clinical or laboratory evidence exist that supports possible causes for the AEFI other than the vaccine in the affected individual? Is there a known causal association between the AEFI and the vaccine? Is there strong evidence against a causal association? Is there a specific laboratory test implicating the vaccine in the pathogenesis? An algorithm can assist with addressing these questions in a standardized, transparent manner which can be tracked and reassessed if additional information becomes available. Examples in this document illustrate the process of using the algorithm to determine causality. As new epidemiologic and clinical data become available, the algorithm and guidelines will need to be modified. Feedback from users of the algorithm will be invaluable in this process. We hope that this algorithm approach can assist with educational efforts to improve the collection of key information on AEFI and provide a platform for teaching about causality assessment.
Field evaluation of vaccine safety
Vaccine, 2004
Surveillance of adverse events in the field represents an essential part of vaccination strategies. Safety studies conducted before vaccine licensure have often not enough power to detect rare or long-term adverse events. Furthermore, adverse events may be caused by incorrect procedures of storage or administration. Conducting surveillance of adverse events in the field is necessary for detecting unexpected increases in incidence of adverse events, for continuing education of health personnel involved in vaccine programs, for providing appropriate information to the public, and for supporting interventions to prevent further adverse events. Signals generated by surveillance systems may stimulate to conduct formal studies to assess causality.
Science, Public Health Policy & the Law, 2021
There are two messages from those who hold appointed offices or other influential positions in Public Health on long-term vaccine safety. The first message is that long-term randomized doubleblinded placebo-controlled clinical trials are not necessary for the long-term study of vaccine safety because we have "pharmacovigilance"; i.e. longterm post-market safety surveillance that is supported by widely accessible, passive vaccine adverse events tracking systems.
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.
Chapter 18: Surveillance for Adverse Events Following Vaccination
I. Public health importance Immunizations have reduced the incidence of many vaccine-preventable diseases in the United States (and many other countries) by more than 95% compared with the prevaccine era (Table 1). For example, paralytic poliomyelitis has been eliminated from the Western Hemisphere and there has been cessation of indigenous measles virus transmission in the U.S. As the proportion of the vaccinated population increases, however, the number of persons who experience an adverse event following vaccination also increases—due either to reactions caused by the vaccination or coincidental events not caused by the vaccination (e.g., sudden infant death syndrome after diphtheria-tetanus-pertussis [DTP] vaccination). In recent years, the annual number of reports to the national adverse event reporting system has exceeded the total number of reports of routine childhood vaccine-preventable diseases, excluding varicella (Table 1). In the absence of disease, benefits of vaccinat...