US Vaccine Adverse Event Reporting Research Articles

Association rule mining in the US Vaccine Adverse Event Reporting System (VAERS).

Spontaneous adverse event reporting systems are critical tools for monitoring the safety of licensed medical products. Commonly used signal detection algorithms identify disproportionate product-adverse event pairs and may not be sensitive to more complex potential signals. We sought to develop a computationally tractable multivariate data-mining approach to identify product-multiple adverse event associations. We describe an application of stepwise association rule mining (Step-ARM) to detect potential vaccine-symptom group associations in the US Vaccine Adverse Event Reporting System. Step-ARM identifies strong associations between one vaccine and one or more adverse events. To reduce the number of redundant association rules found by Step-ARM, we also propose a clustering method for the post-processing of association rules. In sample applications to a trivalent intradermal inactivated influenza virus vaccine and to measles, mumps, rubella, and varicella (MMRV) vaccine and in simulation studies, we find that Step-ARM can detect a variety of medically coherent potential vaccine-symptom group signals efficiently. In the MMRV example, Step-ARM appears to outperform univariate methods in detecting a known safety signal. Our approach is sensitive to potentially complex signals, which may be particularly important when monitoring novel medical countermeasure products such as pandemic influenza vaccines. The post-processing clustering algorithm improves the applicability of the approach as a screening method to identify patterns that may merit further investigation.

Deaths Reported to the Vaccine Adverse Event Reporting System, United States, 1997-2013.

Vaccines are among the safest medical products in use today. Hundreds of millions of vaccinations are administered in the United States each year. Serious adverse reactions are uncommon. However, temporally associated deaths can occur following vaccination. Our aim was to characterize main causes of death among reports submitted to the US Vaccine Adverse Event Reporting System (VAERS), a spontaneous vaccine safety surveillance system. We searched VAERS for US reports of death after any vaccination from 1 July 1997 through 31 December 2013. Available medical records, autopsy reports, and death certificates were reviewed to identify cause of death. VAERS received 2149 death reports, most (n = 1469 [68.4%]) in children. Median age was 0.5 years (range, 0-100 years); males accounted for 1226 (57%) reports. The total annual number of death reports generally decreased during the latter part of the study period. Most common causes of death among 1244 child reports with available death certificates/autopsy reports included sudden infant death syndrome (n = 544 [44%]), asphyxia (n = 74 [6.0%]), septicemia (n = 61 [4.9%]), and pneumonia (n = 57 [4.6%]). Among 526 adult reports, most common causes of death included diseases of the circulatory (n = 247 [46.9%]) and respiratory systems (n = 77 [14.6%]), certain infections and parasitic diseases (n = 62 [11.8%]), and malignant neoplasms (n = 20 [3.8%]). For child death reports, 79.4% received >1 vaccine on the same day. Inactivated influenza vaccine given alone was most commonly associated with death reports in adults (51.4%). No concerning pattern was noted among death reports submitted to VAERS during 1997-2013. The main causes of death were consistent with the most common causes of death in the US population.

Adverse Events following Haemophilus influenzae Type b Vaccines in the Vaccine Adverse Event Reporting System, 1990-2013

To characterize adverse events (AEs) after Haemophilus influenzae type b (Hib) vaccines reported to the US Vaccine Adverse Event Reporting System (VAERS), a spontaneous reporting surveillance system. We searched VAERS for US reports after Hib vaccines among reports received from January 1, 1990, to December 1, 2013. We reviewed a random sample of reports and accompanying medical records for reports classified as serious. All reports of death were reviewed. Physicians assigned a primary clinical category to each reviewed report. We used empirical Bayesian data mining to identify AEs that were disproportionally reported after Hib vaccines. VAERS received 29,747 reports after Hib vaccines; 5179 (17%) were serious, including 896 reports of deaths. Median age was 6 months (range 0-1022 months). Sudden infant death syndrome was the stated cause of death in 384 (51%) of 749 death reports with autopsy/death certificate records. The most common nondeath serious AE categories were neurologic (80; 37%), other noninfectious (46; 22%) (comprising mainly constitutional signs and symptoms); and gastrointestinal (39; 18%) conditions. No new safety concerns were identified after clinical review of reports of AEs that exceeded the data mining statistical threshold. Review of VAERS reports did not identify any new or unexpected safety concerns for Hib vaccines.

Allergic reactions after egg-free recombinant influenza vaccine: reports to the US Vaccine Adverse Event Reporting System.

The Vaccine Adverse Event Reporting System has received reports of allergic reactions following immunization with egg-free recombinant influenza vaccine, among patients with a self-reported egg allergy or previous allergic reaction to inactivated influenza vaccine. These results suggest that allergic reactions following influenza vaccination are not necessarily related to egg proteins.

Novel algorithms for improved pattern recognition using the US FDA Adverse Event Network Analyzer.

The medical review of adverse event reports for medical products requires the processing of "big data" stored in spontaneous reporting systems, such as the US Vaccine Adverse Event Reporting System (VAERS). VAERS data are not well suited to traditional statistical analyses so we developed the FDA Adverse Event Network Analyzer (AENA) and three novel network analysis approaches to extract information from these data. Our new approaches include a weighting scheme based on co-occurring triplets in reports, a visualization layout inspired by the islands algorithm, and a network growth methodology for the detection of outliers. We explored and verified these approaches by analysing the historical signal of Intussusception (IS) after the administration of RotaShield vaccine (RV) in 1999. We believe that our study supports the use of AENA for pattern recognition in medical product safety and other clinical data.

Adverse events after Fluzone® Intradermal vaccine reported to the Vaccine Adverse Event Reporting System (VAERS), 2011–2013

BackgroundIn May 2011, the first trivalent inactivated influenza vaccine exclusively for intradermal administration (TIV-ID) was licensed in the US for adults aged 18–64 years. ObjectiveTo characterize adverse events (AEs) after TIV-ID reported to the US Vaccine Adverse Event Reporting System (VAERS), a spontaneous reporting surveillance system. MethodsWe searched VAERS for US reports after TIV-ID among persons vaccinated from July 1, 2011–February 28, 2013. Medical records were requested for reports coded as serious (death, hospitalization, prolonged hospitalization, disability, life-threatening-illness), and those suggesting anaphylaxis. Clinicians reviewed available information and assigned a primary clinical category to each report. Empirical Bayesian data mining was used to identify disproportional AE reporting following TIV-ID. Causality was not assessed. ResultsVAERS received 466 reports after TIV-ID; 9 (1.9%) were serious, including one reported fatality in an 88-year-old vaccinee. Median age was 43 years (range 4–88 years). The most common AE categories were: 218 (46.8%) injection site reactions; 89 (19.1%) other non-infectious (comprised mainly of constitutional signs and symptoms); and 74 (15.9%) allergy. Eight reports (1.7%) of anaphylaxis were verified by the Brighton criteria or a documented physician diagnosis. Disproportional reporting was identified for three AEs: ‘injection site nodule’, ‘injection site pruritus’, and ‘drug administered to patient of inappropriate age’. The findings for the first two AEs were expected. Twenty-four reports of vaccinees <18 years or ≥65 years were reported, and 14 of 24 were coded with the AE ‘drug administered to patient of inappropriate age’. ConclusionsReview of VAERS reports did not identify any new or unexpected safety concerns after TIV-ID. Injection site reactions were the most commonly reported AEs, similar to the pre-licensure clinical trials. Use of TIV-ID in younger and older individuals outside the approved age range highlights the need for education of healthcare providers regarding approved TIV-ID use.

Editorial Commentary: Intussusception and Rotavirus Vaccination--Balancing Risk Against Benefit

An association between intussusception, a form of bowel obstruction, and live oral rotavirus vaccines was first identified with Rotashield, a rhesus-human reassortant rotavirus vaccine that was recommended for routine immunization of US infants in 1998 [1]. During the first year after vaccine introduction, a cluster of intussusception cases temporally linked to Rotashield vaccination was reported to the US Vaccine Adverse Event Reporting System (VAERS), a national passive reporting system [2]. This prompted a national case-control study, which confirmed the association between Rotashield and intussusception [3], with the greatest risk (an approximately 37-fold increase) occurring 3–7 days after the first vaccine dose. A smaller increase was seen in the second week after dose 1 and during the first week after dose 2. The excess risk of approximately 1 intussusception case in 10 000 Rotashield recipients led to withdrawal of the vaccine from the US market in 1999 [4]. Because of the legacy of Rotashield, the 2 other live oral rotavirus vaccines in advanced stages of clinical testing at the time—a pentavalent bovine-human reassortant vaccine (RV5, RotaTeq, Merck.) and a monovalent human vaccine (RV1, Rotarix, GSK Biologicals)—each underwent large clinical trials of approximately 60 000–70 000 infants specifically to assess the risk of intussusception [5, 6]. No elevated risk was found 42 and 30 days after vaccination after any of the 3 doses of RV5 and either of the 2 doses of RV1, respectively, in these trials. This facilitated licensure of both products and a recommendation for universal use in the United States and around the world. The World Health Organization (WHO) recommends both RV5 and RV1 for global use and encourages postlicensure monitoring to further assess the intussusception risk during routine programmatic use [7]. In this issue, Carlin et al present an elegant analysis of postlicensure intussusception data from Australia that has several notable strengths [8]. First, given that different states in Australia exclusively implemented either RV5 or RV1 with a relatively equitable national distribution of the 2 vaccines, this evaluation was able to evaluate risk with both vaccines during contemporaneous use in demographically similar populations. Second, robust and nationally representative evidence could be generated because of a relatively comprehensive capture of intussusception cases through examination of hospital discharge databases (with review of case records to restrict analysis to cases that met the highest Brighton Collaboration level 1 diagnostic certainty) and because of the availability of immunization data though a national registry with a near-complete (>98%) capture of vaccines provided through the National Immunization Program. Third, both the case-series and case-control methods were used to assess intussusception, and the consistency of estimates from both approaches provides additional reassurance about the validity of the findings. Fourth, the authors present side-by-side data on both the excess number of intussusception cases that might be caused by vaccination against the expected reduction in rotavirus hospitalizations, so that the risks could be interpreted in the context of benefits. Last, a range of sensitivity analyses were conducted around various assumptions and parameters that informed the analysis, with none influencing the overall conclusions substantially. The results show that in Australia both rotavirus vaccines are associated with an increased risk of intussusception in the first 3 weeks after the first vaccine dose and the first week after the second dose, with the greatest risk in the first week after dose 1. An increased intussusception risk in the first week after dose 1 of RV1 was also documented in a previous smaller study from Australia and in 2 separate evaluations in Mexico [9–11]. In Received 1 July 2013; accepted 5 July 2013; electronically published 19 August 2013. Correspondence: Walter A. Orenstein, MD, Division of Infectious Diseases, Emory University School of Medicine, Atlanta, GA 30338 (dmill06@emory.edu). Clinical Infectious Diseases 2013;57(10):1435–7 © The Author 2013. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals. permissions@oup.com. DOI: 10.1093/cid/cit532

Application of Information Retrieval Approaches to Case Classification in the Vaccine Adverse Event Reporting System

Automating the classification of adverse event reports is an important step to improve the efficiency of vaccine safety surveillance. Previously we showed it was possible to classify reports using features extracted from the text of the reports. The aim of this study was to use the information encoded in the Medical Dictionary for Regulatory Activities (MedDRA(®)) in the US Vaccine Adverse Event Reporting System (VAERS) to support and evaluate two classification approaches: a multiple information retrieval strategy and a rule-based approach. To evaluate the performance of these approaches, we selected the conditions of anaphylaxis and Guillain-Barré syndrome (GBS). We used MedDRA(®) Preferred Terms stored in the VAERS, and two standardized medical terminologies: the Brighton Collaboration (BC) case definitions and Standardized MedDRA(®) Queries (SMQ) to classify two sets of reports for GBS and anaphylaxis. Two approaches were used: (i) the rule-based instruments that are available by the two terminologies (the Automatic Brighton Classification [ABC] tool and the SMQ algorithms); and (ii) the vector space model. We found that the rule-based instruments, particularly the SMQ algorithms, achieved a high degree of specificity; however, there was a cost in terms of sensitivity in all but the narrow GBS SMQ algorithm that outperformed the remaining approaches (sensitivity in the testing set was equal to 99.06% for this algorithm vs. 93.40% for the vector space model). In the case of anaphylaxis, the vector space model achieved higher sensitivity compared with the best values of both the ABC tool and the SMQ algorithms in the testing set (86.44% vs. 64.11% and 52.54%, respectively). Our results showed the superiority of the vector space model over the existing rule-based approaches irrespective of the standardized medical knowledge represented by either the SMQ or the BC case definition. The vector space model might make automation of case definitions for spontaneous report review more efficient than current rule-based approaches, allowing more time for critical assessment and decision making by pharmacovigilance experts.

Data mining for prospective early detection of safety signals in the Vaccine Adverse Event Reporting System (VAERS): a case study of febrile seizures after a 2010-2011 seasonal influenza virus vaccine.

Reports of data mining results as an initial indication of a prospectively detected safety signal in the US Vaccine Adverse Event Reporting System (VAERS) have been limited. In April 2010 a vaccine safety signal for febrile seizures after Fluvax(®) and Fluvax(®) Junior was identified in Australia without the aid of data mining. In order to refine Northern Hemisphere influenza vaccine safety surveillance, VAERS data mining analyses based on vaccine brand name were initiated during the 2010-2011 influenza season. We describe the strategies that led to the finding of a novel safety signal using empirical Bayesian data mining. The primary US VAERS analysis calculated an empirical Bayesian geometric mean (EBGM), which was adjusted for age group, sex and year received. A secondary age-stratified analysis calculated a separate EBGM for 11 pre-defined age subsets. These bi-weekly analyses were generated with database restrictions that separated live and inactivated vaccines as well as with the US VAERS database. A cutoff of 2.0 at the fifth percentile of the confidence interval (CI) for the EBGM, the EB05, was used to identify vaccine adverse event combinations for further evaluation. Examination of potential interactions among concomitantly administered vaccines is based on the Interaction Signal Score (INTSS), which is a relative measure of how much excess disproportionality is present in the three-dimensional combination of two vaccines and one adverse event term. An INTSS >1 indicates that the CI for the three-dimensional analysis is larger than and does not overlap with the CI from the highest two-dimensional analysis. We subsequently examined the possibility of masking by removing all 2,095 Fluzone(®) 2010-2011 reports from the 10 December 2010 version of the VAERS database. In addition, we calculated relative reporting ratios to observe the relative contribution of adjustment and the Multi-Item Gamma Poisson Shrinker (MGPS) algorithm to EBGM values. On 10 December 2010, US VAERS analyses we found an EB05 >2 for Fluzone(®) 2010-2011 and the Medical Dictionary for Regulatory Activities (MedDRA(®)) term "febrile seizure". MedDRA(®) terminology is the medical terminology developed under the auspices of the International Conference on Harmonization of technical requirements for Registration of Pharmaceuticals for Human Use (ICH). No other vaccine products had independent vaccine-febrile seizure combinations with an EB05 >2. Three-dimensional analyses to examine possible interactions among vaccine products concomitantly administered with Fluzone(®) 2010-2011 yielded Interaction Signal Score values <1. Removal of all Fluzone(®) 2010-2011 reports from the VAERS database failed to demonstrate a previously masked vaccine adverse event pair with an EB05 >2. The inactivated vaccine database restriction resulted in a 41% reduction in background VAERS reports and a 24% reduction in foreground VAERS reports. Empirical Bayesian data mining in VAERS prospectively detected the safety signal for febrile seizures after Fluzone(®) 2010-2011 in young children. The EB05 threshold, database restrictions, adjustment and baseline data mining were strategies adopted a priori to enhance the specificity of the 2010-2011 influenza vaccine data mining analyses. A database restriction used to separate live vaccines resulted in a reduced EB05. Adjustment of data mining analyses had a larger effect on estimates of disproportionality than the MGPS algorithm. Masking did not appear to influence our findings. This case study illustrates the value of VAERS data mining for vaccine safety monitoring.

Text mining for the Vaccine Adverse Event Reporting System: medical text classification using informative feature selection

The US Vaccine Adverse Event Reporting System (VAERS) collects spontaneous reports of adverse events following vaccination. Medical officers review the reports and often apply standardized case definitions, such as those developed by the Brighton Collaboration. Our objective was to demonstrate a multi-level text mining approach for automated text classification of VAERS reports that could potentially reduce human workload. We selected 6034 VAERS reports for H1N1 vaccine that were classified by medical officers as potentially positive (N(pos)=237) or negative for anaphylaxis. We created a categorized corpus of text files that included the class label and the symptom text field of each report. A validation set of 1100 labeled text files was also used. Text mining techniques were applied to extract three feature sets for important keywords, low- and high-level patterns. A rule-based classifier processed the high-level feature representation, while several machine learning classifiers were trained for the remaining two feature representations. Classifiers' performance was evaluated by macro-averaging recall, precision, and F-measure, and Friedman's test; misclassification error rate analysis was also performed. Rule-based classifier, boosted trees, and weighted support vector machines performed well in terms of macro-recall, however at the expense of a higher mean misclassification error rate. The rule-based classifier performed very well in terms of average sensitivity and specificity (79.05% and 94.80%, respectively). Our validated results showed the possibility of developing effective medical text classifiers for VAERS reports by combining text mining with informative feature selection; this strategy has the potential to reduce reviewer workload considerably.

Network analysis of possible anaphylaxis cases reported to the US vaccine adverse event reporting system after H1N1 influenza vaccine.

The identification of signals from spontaneous reporting systems plays an important role in monitoring the safety of medical products. Network analysis (NA) allows the representation of complex interactions among the key elements of such systems. We developed a network for a subset of the US Vaccine Adverse Event Reporting System (VAERS) by representing the vaccines/adverse events (AEs) and their interconnections as the nodes and the edges, respectively; this subset we focused upon included possible anaphylaxis reports that were submitted for the H1N1 influenza vaccine. Subsequently, we calculated the main metrics that characterize the connectivity of the nodes and applied the island algorithm to identify the densest region in the network and, thus, identify potential safety signals. AEs associated with anaphylaxis formed a dense region in the 'anaphylaxis' network demonstrating the strength of NA techniques for pattern recognition. Additional validation and development of this approach is needed to improve future pharmacovigilance efforts.

Thrombocytopenia after vaccination: Case reports to the US Vaccine Adverse Event Reporting System, 1990–2008

We reviewed thrombocytopenia (TP) reports to the US Vaccine Adverse Event Reporting System (VAERS). We examined TP patterns for differences in single versus multiple immunization reports, presence of a live viral vaccine, seriousness, age, and interval to symptom onset. We found 1510 reports of possible TP and after exclusions evaluated 1440 for possible causes. Most (1078; 75%) met the regulatory definition of a serious adverse event. TP was reported after inactivated and live viral vaccines. Platelet counts <10×109/L were reported. Identified vaccines could be prioritized for hypothesis-testing studies.

Preventable Mix-ups of Tuberculin and Vaccines

Errors involving the mix-up of tuberculin purified protein derivative (PPD) and vaccines leading to adverse reactions and unnecessary medical management have been reported previously. To determine the frequency of PPD-vaccine mix-ups reported to the US Vaccine Adverse Event Reporting System (VAERS) and the Adverse Event Reporting System (AERS), characterize adverse events and clusters involving mix-ups and describe reported contributory factors. We reviewed AERS reports from 1969 to 2005 and VAERS reports from 1990 to 2005. We defined a mix-up error event as an incident in which a single patient or a cluster of patients inadvertently received vaccine instead of a PPD product or received a PPD product instead of vaccine. We defined a cluster as inadvertent administration of PPD or vaccine products to more than one patient in the same facility within 1 month. Of 115 mix-up events identified, 101 involved inadvertent administration of vaccines instead of PPD. Product confusion involved PPD and multiple vaccines. The annual number of reported mix-ups increased from an average of one event per year in the early 1990s to an average of ten events per year in the early part of this decade. More than 240 adults and children were affected and the majority reported local injection site reactions. Four individuals were hospitalized (all recovered) after receiving the wrong products. Several patients were inappropriately started on tuberculosis prophylaxis as a result of a vaccine local reaction being interpreted as a positive tuberculin skin test. Reported potential contributory factors involved both system factors (e.g. similar packaging) and human errors (e.g. failure to read label before product administration). To prevent PPD-vaccine mix-ups, proper storage, handling and administration of vaccine and PPD products is necessary.

Developmental regression and autism reported to the Vaccine Adverse Event Reporting System

We report demographic and clinical characteristics of children reported to the US Vaccine Adverse Event Reporting System (VAERS) as having autism or another developmental disorder after vaccination. We completed 124 interviews with parents and reviewed medical records for 31 children whose records contained sufficient information to evaluate the child's developmental history. Medical record review indicated that 27 of 31 (87%) children had autism/ASD and 19 (61.3%) had evidence of developmental regression (loss of social, language, or motor skills). The proportion of VAERS cases of autism with regression was greater than that reported in population-based studies, based on the subset of VAERS cases with medical record confirmation. This difference may reflect preferential reporting to VAERS of autism with regression. In other respects, the children in this study appear to be similar to other children with autism. Further research might determine whether the pathogenesis of autism with developmental regression differs from that of autism without regression.

Vaccine Adverse Event Reporting System Reporting Source: A Possible Source of Bias in Longitudinal Studies

The US Vaccine Adverse Event Reporting System (VAERS) is a passive reporting system to which anyone can report an event. Publicity related to potential adverse events may change reporting patterns. The objective of this paper is to show how litigation-related reports have influenced the trends in possible adverse event reports to VAERS. The VAERS public-use data files were downloaded in July 2004 and translated into identical SAS data sets for analysis. Cases that were related to litigation were identified using a word search algorithm. All cases for the most frequently reported symptoms in litigation (overdose, neuropathy, autism, "mental retardation," arthralgia, and "speech disorder") were reviewed. In recent years, most case reports to VAERS that were related to overdose, neuropathy, and thimerosal were related to litigation. Many cases that were related to autism and mental retardation were as well. This review shows a previously undisclosed rise in the number of reports to the VAERS related to pending litigation for vaccine injury. The implications of this for understanding longitudinal reporting patterns are discussed.

Data mining in the US using the Vaccine Adverse Event Reporting System.

The US Vaccine Adverse Event Reporting System (VAERS), which is charged with vigilance for detecting vaccine-related safety issues, faces an increasingly complex immunisation environment. Since 1990, steady increases in vaccine licensing and distribution have resulted in increasing numbers of reports to VAERS. Prominent features of current reports include more routine vaccine co-administration and frequent reports of new postvaccination clinical syndromes. Data-mining methods, based on disproportionality analyses, are one strategy being pursued by VAERS researchers to increase the utility of its complex database. The types of analyses used include proportional reporting ratios, association rule discovery, and various 'historic limits' methods that compare observed versus expected event counts. The use of such strategies in VAERS has been primarily supplemental and retrospective. Signals for inactivated influenza, typhoid and tetanus toxoid-containing vaccines have been successfully identified. Concerns flagged through data mining should always be subject to clinical case review as a first evaluation step. Persistent issues should be subject to formal hypothesis testing in large linked databases or other controlled-study settings. Automated data-mining techniques for prospective use are currently undergoing development and evaluation within VAERS. Their use (as one signal-detection tool among many) by trained medical evaluators who are aware of system limitations is one legitimate approach to improving the ability of VAERS to generate vaccine-safety hypotheses. Such approaches are needed as more new vaccines continue to be licensed.

Adverse Events Reported Following Live, Cold-Adapted, Intranasal Influenza Vaccine

In June 2003, the US Food and Drug Administration licensed a trivalent live, attenuated influenza vaccine (LAIV-T) for intranasal administration to healthy persons 5 to 49 years of age. Although prelicensure testing involved 20 228 vaccinees, clinical trials were not of sufficient size to detect rare adverse events reliably. To identify adverse events reported following LAIV-T administration after licensure. All adverse events reported to the US Vaccine Adverse Event Reporting System (VAERS) during the 2003-2004 and the 2004-2005 influenza seasons. Numbers and proportions of reported adverse events and reporting rates of adverse events per 100,000 vaccinees. Approximately 2,500,000 persons received LAIV-T during the first 2 postlicensure seasons. As of August 16, 2005, VAERS received 460 adverse event reports for vaccinations received from August 2003 through July 2005. No fatalities were reported. There were 7 reports of possible anaphylaxis, 2 reports of Guillain-Barré syndrome, 1 report of Bell palsy, and 8 reports of asthma exacerbation among individuals with a prior asthma history. Events in individuals for whom the vaccine was not indicated accounted for 73 reports (16%). Reports to VAERS in the first 2 seasons of LAIV-T use did not identify any unexpected serious risks with this vaccine when used according to approved indications. Like many vaccines and other medical products, LAIV-T may rarely cause anaphylaxis. Secondary transmission of the vaccine virus merits further investigation. Reports of asthma exacerbations in vaccinees with prior asthma history highlight the risks of vaccine use inconsistent with approved labeling.

Vaccine misadventure: inadvertent administration of tetanus toxoid.

Background and epidemiology : A recent Morbidity and Mortality Weekly Report on inadvertent intradermal administration of tetanus toxoid[1][1] highlights the importance of reporting adverse events that arise from vaccine administration. The US Vaccine Adverse Event Reporting System (VAERS) has

Current Literature: 1

Objective Anaphylaxis after immunization, although rare, is serious and potentially life‐threatening. Understanding risk factors for this reaction is therefore important. Gelatin is added to many vaccines as a heat stabilizer. Japanese researchers have demonstrated a strong association between immediate hypersensitivity reactions to measles, mumps, rubella, varicella, and Japanese encephalitis immunizations and subsequent detection of antigelatin immunoglobulin E (IgE) antibodies. They suggested that previous receipt by these patients of diphtheria–tetanus–acellular pertussis vaccines with trace amounts of gelatin was responsible for the sensitization. We aimed to assess whether a similar association exists for vaccinees in the United States who reported anaphylaxis after receipt of measles–mumps–rubella (MMR) or measles vaccines and to review recent trends in reporting of hypersensitivity reactions.Methods We conducted a retrospective case–control study. Cases of anaphylaxis that met a predefined case definition were identified from the US Vaccine Adverse Event Reporting System (VAERS). Mayo Clinic patients who received MMR vaccine uneventfully served as controls. The study subjects were interviewed to obtain the history of allergies. Sera from study subjects and their matched controls were tested for IgE antibodies to gelatin, whole egg and vaccine viral antigens using solid‐phase radioimmunoassay. Data from the Biologics Surveillance System on annual numbers of doses of MMR and varicella vaccines distributed in the United States were used to evaluate possible changes in reporting of selected allergic adverse events.Results Fifty‐seven study subjects were recruited into the study and interviewed. Of these, 22 provided serum samples for IgE testing. Twenty‐seven subjects served as a comparison group and provided a sample for IgE testing; 21 of these completed an allergy history questionnaire. Self‐reported history of food allergies was present more frequently in the interviewed study subjects than in the controls, whereas the proportions of people with other characteristics were similar in both groups. None of the interviewed people had a history of food allergy to gelatin. The level of antigelatin IgE antibodies was significantly higher among study subjects than among controls, whereas the levels of IgE antibodies against egg and all three viral antigens did not differ significantly. Of 22 study subjects, six (27%) tested positive for antigelatin IgE, whereas none of the 27 controls did. The rate of anaphylactic reactions reported to VAERS after measles virus‐containing immunization in the United States between 1991 and 1997 is 1.8 per 1 million doses distributed. No substantial increase in the number of reported allergic events after frequently used gelatin containing MMR and varicella vaccines could be observed during the first 4 years (1997–2000) since the introduction of diphtheria–tetanus–acellular pertussis vaccines for use in infancy.Conclusion Anaphylactic reactions to MMR in the United States are rare. The reporting rate has the same order of magnitude as estimates from other countries. Almost one‐quarter of patients with reported anaphylaxis after MMR seem to have hypersensitivity to gelatin in the vaccine. They may be at higher risk of developing anaphylaxis to subsequent doses of other gelatin‐containing vaccines. These people should seek an allergy evaluation before such immunization.

Data mining in the US Vaccine Adverse Event Reporting System (VAERS): early detection of intussusception and other events after rotavirus vaccination

The Vaccine Adverse Event Reporting System (VAERS) is the US passive surveillance system monitoring vaccine safety. A major limitation of VAERS is the lack of denominator data (number of doses of administered vaccine), an element necessary for calculating reporting rates. Empirical Bayesian data mining, a data analysis method, utilizes the number of events reported for each vaccine and statistically screens the database for higher than expected vaccine-event combinations signaling a potential vaccine-associated event. This is the first study of data mining in VAERS designed to test the utility of this method to detect retrospectively a known side effect of vaccination–intussusception following rotavirus (RV) vaccine. From October 1998 to December 1999, 112 cases of intussusception were reported. The data mining method was able to detect a signal for RV-intussusception in February 1999 when only four cases were reported. These results demonstrate the utility of data mining to detect significant vaccine-associated events at early date. Data mining appears to be an efficient and effective computer-based program that may enhance early detection of adverse events in passive surveillance systems.