The Experts below are selected from a list of 536571 Experts worldwide ranked by ideXlab platform
Robert Ball - One of the best experts on this subject based on the ideXlab platform.
-
Can Natural Language Processing Improve the Efficiency of Vaccine Adverse Event Report Review
Methods of Information in Medicine, 2015Co-Authors: Bethany Baer, Scott Winiecki, J. Scott, Taxiarchis Botsis, Michael D. Nguyen, D. Martin, Robert BallAbstract:Background: Individual case review of spontaneous Adverse Event (AE) reports remains a cornerstone of medical product safety surveillance for industry and regulators. Previously we developed the Vaccine Adverse Event Text Miner (VaeTM) to offer automated information extraction and potentially accelerate the evaluation of large volumes of unstructured data and facilitate signal detection. Objective: To assess how the information extraction performed by VaeTM impacts the accuracy of a medical expert’s review of the vaccine Adverse Event report. Methods: The “outcome of interest” (diagnosis, cause of death, second level diagnosis), “onset time,” and “alternative explanations” (drug, medical and family history) for the Adverse Event were extracted from 1000 reports from the Vaccine Adverse Event Reporting System (VAERS) using the VaeTM system. We compared the human interpretation, by medical experts, of the VaeTM extracted data with their interpretation of the traditional full text reports for these three variables. Two experienced clinicians alternately reviewed text miner output and full text. A third clinician scored the match rate using a predefined algorithm; the proportion of matches and 95% confidence intervals (CI) were calculated. Review time per report was analyzed. Results: Proportion of matches between the interpretation of the VaeTM extracted data, compared to the interpretation of the full text: 93% for outcome of interest (95% CI: 91– 94%) and 78% for alternative explanation (95% CI: 75 – 81%). Extracted data on the time to onset was used in 14% of cases and was a match in 54% (95% CI: 46 – 63%) of those cases. When supported by structured time data from reports, the match for time to onset was 79% (95% CI: 76 – 81%). The extracted text averaged 136 (74%) fewer words, resulting in a mean reduction in review time of 50 (58%) seconds per report. Conclusion: Despite a 74% reduction in words, the clinical conclusion from VaeTM extracted data agreed with the full text in 93% and 78% of reports for the outcome of interest and alternative explanation, respectively. The limited amount of extracted time interval data indicates the need for further development of this feature. VaeTM may improve review efficiency, but further study is needed to determine if this level of agreement is sufficient for routine use.
-
Vaccine Adverse Event text mining system for extracting features from vaccine safety reports
Journal of the American Medical Informatics Association, 2012Co-Authors: Taxiarchis Botsis, Thomas Buttolph, Scott Winiecki, E. J. Woo, Michael D. Nguyen, Robert BallAbstract:OBJECTIVE: To develop and evaluate a text mining system for extracting key clinical features from vaccine Adverse Event reporting system (VAERS) narratives to aid in the automated review of Adverse Event reports.\n\nDESIGN: Based upon clinical significance to VAERS reviewing physicians, we defined the primary (diagnosis and cause of death) and secondary features (eg, symptoms) for extraction. We built a novel vaccine Adverse Event text mining (VaeTM) system based on a semantic text mining strategy. The performance of VaeTM was evaluated using a total of 300 VAERS reports in three sequential evaluations of 100 reports each. Moreover, we evaluated the VaeTM contribution to case classification; an information retrieval-based approach was used for the identification of anaphylaxis cases in a set of reports and was compared with two other methods: a dedicated text classifier and an online tool.\n\nMEASUREMENTS: The performance metrics of VaeTM were text mining metrics: recall, precision and F-measure. We also conducted a qualitative difference analysis and calculated sensitivity and specificity for classification of anaphylaxis cases based on the above three approaches.\n\nRESULTS: VaeTM performed best in extracting diagnosis, second level diagnosis, drug, vaccine, and lot number features (lenient F-measure in the third evaluation: 0.897, 0.817, 0.858, 0.874, and 0.914, respectively). In terms of case classification, high sensitivity was achieved (83.1%); this was equal and better compared to the text classifier (83.1%) and the online tool (40.7%), respectively.\n\nCONCLUSION: Our VaeTM implementation of a semantic text mining strategy shows promise in providing accurate and efficient extraction of key features from VAERS narratives.
-
text mining for the vaccine Adverse Event reporting system medical text classification using informative feature selection
Journal of the American Medical Informatics Association, 2011Co-Authors: Taxiarchis Botsis, Michael D. Nguyen, Marianthi Markatou, Robert BallAbstract:Objective 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. Design We selected 6034 VAERS reports for H1N1 vaccine that were classified by medical officers as potentially positive (Npos=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. Measurements Classifiers' performance was evaluated by macro-averaging recall, precision, and F-measure, and Friedman's test; misclassification error rate analysis was also performed. Results 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). Conclusion 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.
-
Adverse Events after anthrax vaccination reported to the vaccine Adverse Event reporting system vaers 1990 2007
Vaccine, 2009Co-Authors: Robert Ball, Dale R Burwen, Maureen Knippen, Miles M BraunAbstract:Abstract During the period March 1, 1998 to January 14, 2007, approximately 6 million doses of Anthrax vaccine adsorbed (AVA) vaccine were administered. As of January 16, 2007, 4753 reports of Adverse Events following receipt of AVA vaccination had been submitted to the Vaccine Adverse Event Reporting System (VAERS). Taken together, reports to VAERS did not definitively link any serious unexpected risk to this vaccine, and review of death and serious reports did not show a distinctive pattern indicative of a causal relationship to AVA vaccination. Continued monitoring of VAERS and analysis of potential associations between AVA vaccination and rare, serious Events is warranted.
-
Effects of Stratification on Data Mining in the US Vaccine Adverse Event Reporting System (VAERS)
Drug Safety, 2008Co-Authors: Robert Ball, Dale R Burwen, M. Miles BraunAbstract:Background: Vaccines are administered differentially according to age and sex, and disease patterns also vary among people of different age and sex groups. Estimates of disproportionality should be calculated based on comparisons of groups that have a similar likelihood of receiving similar vaccines and experiencing similar Adverse Events, to prEvent false disproportionality from occurring. Stratified empirical Bayesian (EB) methods have been compared with crude, but not stratified, proportional reporting ratios (PRRs) in their performance on Adverse Event data. Objectives: (i) to implement stratification of PRR; (ii) to quantify and compare vaccine-Event pairs that are highlighted by PRR and EB05 (the lower bound of the 90% CI of the EB geometric mean), for both crude and stratified; and (iii) to evaluate the effects of stratification by age and sex, in identifying Adverse Events that are accepted to be caused by vaccines. Methods: We applied EB and PRR data mining methods to data from the US Vaccine Adverse Event Reporting System (VAERS). We stratified PRR and EB05 by age and sex. To study the effects of stratification, we compared the crude PRR and stratified PRR. We also assessed the crude EB05 and stratified EB05, and then compared the effects of stratification on EB05 and PRR. Results: Stratification not only changed the number of vaccine-Event pairs that were highlighted, but also changed which pairs were highlighted. There were 283 vaccine-Event pairs that were highlighted by the crude EB05, but not the stratified; 12 that were highlighted by the stratified EB05, but not the crude; and 162 that were highlighted by both. Similarly, there were 701 vaccine-Event pairs that were highlighted by the crude PRR, but not the stratified; 139 that were highlighted by the stratified PRR, but not the crude; and 895 that were highlighted by both. There were 1466 vaccine-Event pairs in which the effect of stratification was different for EB05 and PRR. Conclusion: To our knowledge, this is the first published analysis using stratified PRRs. In this analysis of passive surveillance data, stratification revealed and reduced confounding in EB and PRR, and also unmasked some vaccine-Event pairs that the crude values did not highlight. Stratification should be applied if confounding is suspected. By decreasing the total number of highlighted vaccine-Event pairs, stratification is likely to increase efficiency and therefore might reduce workload.
Robert T. Chen - One of the best experts on this subject based on the ideXlab platform.
-
understanding vaccine safety information from the vaccine Adverse Event reporting system
Pediatric Infectious Disease Journal, 2004Co-Authors: Frederick Varricchio, Frank Destefano, John Iskander, M. Miles Braun, Robert Pless, Robert Ball, Robert T. ChenAbstract:The Vaccine Adverse Event Reporting System (VAERS) is administered by the Food and Drug Administration and CDC and is a key component of postlicensure vaccine safety surveillance. Its primary function is to detect early warning signals and generate hypotheses about possible new vaccine Adverse Event
-
Understanding vaccine safety information from the Vaccine Adverse Event Reporting System
Pediatric Infectious Disease Journal, 2004Co-Authors: Frederick Varricchio, Frank Destefano, John Iskander, M. Miles Braun, Robert Pless, Robert Ball, Robert T. ChenAbstract:The Vaccine Adverse Event Reporting System (VAERS) is administered by the Food and Drug Administration and CDC and is a key component of postlicensure vaccine safety surveillance. Its primary function is to detect early warning signals and generate hypotheses about possible new vaccine Adverse Events or changes in frequency of known ones. VAERS is a passive surveillance system that relies on physicians and others to voluntarily submit reports of illness after vaccination. Manufacturers are required to report all Adverse Events of which they become aware. There are a number of well-described limitations of such reporting systems. These include, for example, variability in report quality, biased reporting, underreporting and the inability to determine whether a vaccine caused the Adverse Event in any individual report. Strengths of VAERS are that it is national in scope and timely. The information in VAERS reports is not necessarily complete nor is it verified systematically. Reports are classified as serious or nonserious based on regulatory criteria. Reports are coded by VAERS in a uniform way with a limited number of terms using a terminology called COSTART. Coding is useful for search purposes but is necessarily imprecise. VAERS is useful in detecting Adverse Events related to vaccines and most recently was used for enhanced reporting of Adverse Events in the national smallpox immunization campaign. VAERS data have always been publicly available. However, it is essential for users of VAERS data to be fully aware of the strengths and weaknesses of the system. VAERS data contain strong biases. Incidence rates and relative risks of specific Adverse Events cannot be calculated. Statistical significance tests and confidence intervals should be used with great caution and not routinely. Signals detected in VAERS should be subjected to further clinical and descriptive epidemiologic analysis. Confirmation in a controlled study is usually required. An understanding of the system's defined objectives and inherent drawbacks is vital to the effective use of VAERS data in vaccine safety investigations.
-
an overview of the vaccine Adverse Event reporting system vaers as a surveillance system
Vaccine, 1999Co-Authors: James A Singleton, Gina T Mootrey, Jenifer C Lloyd, Marcel E Salive, Robert T. ChenAbstract:We evaluated the Vaccine Adverse Event Reporting System (VAERS), the spontaneous reporting system for vaccine-associated Adverse Events in the United States, as a public health surveillance system, using evaluation guidelines from the Centers for Disease Control and PrEvention. We found that VAERS is simple for reporters to use, flexible by design and its data are available in a timely fashion. The predictive value positive for one severe Event is known to be high, but for most Events is unknown. The acceptability, sensitivity and representativeness of VAERS are unknown. The study of vaccine safety is complicated by underreporting, erroneous reporting, frequent multiple exposures and multiple outcomes.
Miles M Braun - One of the best experts on this subject based on the ideXlab platform.
-
Adverse Events after anthrax vaccination reported to the vaccine Adverse Event reporting system vaers 1990 2007
Vaccine, 2009Co-Authors: Robert Ball, Dale R Burwen, Maureen Knippen, Miles M BraunAbstract:Abstract During the period March 1, 1998 to January 14, 2007, approximately 6 million doses of Anthrax vaccine adsorbed (AVA) vaccine were administered. As of January 16, 2007, 4753 reports of Adverse Events following receipt of AVA vaccination had been submitted to the Vaccine Adverse Event Reporting System (VAERS). Taken together, reports to VAERS did not definitively link any serious unexpected risk to this vaccine, and review of death and serious reports did not show a distinctive pattern indicative of a causal relationship to AVA vaccination. Continued monitoring of VAERS and analysis of potential associations between AVA vaccination and rare, serious Events is warranted.
-
Adverse Event reports following yellow fever vaccination
Vaccine, 2008Co-Authors: Nicole P Lindsey, Betsy A Schroeder, Elaine R Miller, Miles M Braun, Alison F Hinckley, Nina Marano, Barbara A Slade, Elizabeth D Barnett, Gary W Brunette, Katherine HoranAbstract:Abstract Yellow fever (YF) vaccine has been used for prEvention of YF since 1937 with over 500 million doses administered. However, rare reports of severe Adverse Events following vaccination have raised concerns about the vaccine’s safety. We reviewed reports of Adverse Events following YF vaccination reported to the U.S. Vaccine Adverse Event Reporting System (VAERS) from 2000 to 2006. We used estimates of age and sex distribution of administered doses obtained from a 2006 survey of authorized vaccine providers to calculate age- and sex-specific reporting rates of all serious Adverse Events (SAE), anaphylaxis, YF vaccine-associated neurotropic disease, and YF vaccine-associated viscerotropic disease. Reporting rates of SAEs were substantially higher in males and in persons aged ≥60 years. These findings reinforce the generally acceptable safety profile of YF vaccine, but highlight the importance of physician and traveler education regarding the risks and benefits of YF vaccination, particularly for travelers ≥60 years of age. Vaccination should be limited to persons traveling to areas where the risk of YF is expected to exceed the risk of serious Adverse Events after vaccination, or if not medically contraindicated, where national regulations require proof of vaccination to prEvent introduction of YF.
-
data mining in the us vaccine Adverse Event reporting system vaers early detection of intussusception and other Events after rotavirus vaccination
Vaccine, 2001Co-Authors: Diane E Erwin, Miles M BraunAbstract:Abstract 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.
David Martin - One of the best experts on this subject based on the ideXlab platform.
-
Safety monitoring in the Vaccine Adverse Event Reporting System (VAERS)
Vaccine, 2015Co-Authors: Tom T. Shimabukuro, Michael Nguyen, David Martin, Frank DestefanoAbstract:The Centers for Disease Control and PrEvention (CDC) and the U.S. Food and Drug Administration (FDA) conduct post-licensure vaccine safety monitoring using the Vaccine Adverse Event Reporting System (VAERS), a spontaneous (or passive) reporting system. This means that after a vaccine is approved, CDC and FDA continue to monitor safety while it is distributed in the marketplace for use by collecting and analyzing spontaneous reports of Adverse Events that occur in persons following vaccination. Various methods and statistical techniques are used to analyze VAERS data, which CDC and FDA use to guide further safety evaluations and inform decisions around vaccine recommendations and regulatory action. VAERS data must be interpreted with caution due to the inherent limitations of passive surveillance. VAERS is primarily a safety signal detection and hypothesis generating system. Generally, VAERS data cannot be used to determine if a vaccine caused an Adverse Event. VAERS data interpreted alone or out of context can lead to erroneous conclusions about cause and effect as well as the risk of Adverse Events occurring following vaccination. CDC makes VAERS data available to the public and readily accessible online.We describe fundamental vaccine safety concepts, provide an overview of VAERS for healthcare professionals who provide vaccinations and might want to report or better understand a vaccine Adverse Event, and explain how CDC and FDA analyze VAERS data. We also describe strengths and limitations, and address common misconceptions about VAERS. Information in this review will be helpful for healthcare professionals counseling patients, parents, and others on vaccine safety and benefit-risk balance of vaccination.
-
Adverse Events following influenza a h1n1 2009 monovalent vaccines reported to the vaccine Adverse Event reporting system united states october 1 2009 january 31 2010
Vaccine, 2010Co-Authors: Claudia Vellozzi, Michael Nguyen, Penina Haber, Paige Lewis, Karen R Broder, Maria Cano, Michael M Mcneil, Marthe Bryant, James A Singleton, David MartinAbstract:The United States (US) influenza A (H1N1) 2009 monovalent (2009-H1N1) vaccination program began in October 2009. Reports to the vaccine Adverse Event reporting system (VAERS), a US spontaneous reporting system, were reviewed to identify potential rare Events or unusual Adverse Event (AE) patterns after 2009-H1N1 vaccination. The Adverse Event profile after 2009-H1N1 vaccine in VAERS (∼10,000 reports) was consistent with that of seasonal influenza vaccines, although the reporting rate was higher after 2009-H1N1 than seasonal influenza vaccines, this may be, at least in part, a reflection of stimulated reporting. Death, Guillain–Barre syndrome and anaphylaxis reports after 2009-H1N1 vaccination were rare (each <2 per million doses administered).
Penina Haber - One of the best experts on this subject based on the ideXlab platform.
-
Adverse Event reports after tetanus toxoid reduced diphtheria toxoid and acellular pertussis vaccines in pregnant women
American Journal of Obstetrics and Gynecology, 2012Co-Authors: Yenlik Zheteyeva, Penina Haber, Pedro L Moro, Naomi K Tepper, Sonja A Rasmussen, Faith Barash, Natalia V Revzina, Dmitry M Kissin, Paige Lewis, Jerome I TokarsAbstract:Objective We sought to characterize reports to the Vaccine Adverse Event Reporting System (VAERS) of pregnant women who received tetanus toxoid, reduced diphtheria toxoid, and acellular pertussis vaccine (Tdap). Study Design We searched VAERS for reports of pregnant women who received Tdap from Jan. 1, 2005, through June 30, 2010. We conducted a clinical review of reports and available medical records. Results We identified 132 reports of Tdap administered to pregnant women; 55 (42%) described no Adverse Event (AE). No maternal or infant deaths were reported. The most frequent pregnancy-specific AE was spontaneous abortion in 22 (16.7%) reports. Injection site reactions were the most frequent non-pregnancy–specific AE found in 6 (4.5%) reports. One report with a major congenital anomaly (gastroschisis) was identified. Conclusion During a time when Tdap was not routinely recommended in pregnancy, review of reports to VAERS in pregnant women after Tdap did not identify any concerning patterns in maternal, infant, or fetal outcomes.
-
Adverse Events following influenza a h1n1 2009 monovalent vaccines reported to the vaccine Adverse Event reporting system united states october 1 2009 january 31 2010
Vaccine, 2010Co-Authors: Claudia Vellozzi, Michael Nguyen, Penina Haber, Paige Lewis, Karen R Broder, Maria Cano, Michael M Mcneil, Marthe Bryant, James A Singleton, David MartinAbstract:The United States (US) influenza A (H1N1) 2009 monovalent (2009-H1N1) vaccination program began in October 2009. Reports to the vaccine Adverse Event reporting system (VAERS), a US spontaneous reporting system, were reviewed to identify potential rare Events or unusual Adverse Event (AE) patterns after 2009-H1N1 vaccination. The Adverse Event profile after 2009-H1N1 vaccine in VAERS (∼10,000 reports) was consistent with that of seasonal influenza vaccines, although the reporting rate was higher after 2009-H1N1 than seasonal influenza vaccines, this may be, at least in part, a reflection of stimulated reporting. Death, Guillain–Barre syndrome and anaphylaxis reports after 2009-H1N1 vaccination were rare (each <2 per million doses administered).
-
safety of varicella vaccine after licensure in the united states experience from reports to the vaccine Adverse Event reporting system 1995 2005
The Journal of Infectious Diseases, 2008Co-Authors: Sandra S Chaves, Penina Haber, Kimp Walton, Robert P Wise, Hector S Izurieta, Scott D Schmid, Jane F SewardAbstract:Widespread use of varicella vaccine in the United States could enable detection of rare Adverse Events not identified previously. We reviewed data from 1995 to 2005 from the Vaccine Adverse Event Reporting System, including data from laboratory analyses, to distinguish Adverse Events associated with wild-type varicella-zoster virus (VZV) versus those associated with vaccine strain. Almost 48 million doses of varicella vaccine were distributed between 1995 and 2005. There were 25,306 Adverse Events reported (52.7/100,000 doses distributed); 5.0% were classified as serious (2.6/100,000 doses distributed). Adverse Events associated with evidence of vaccine-strain VZV included meningitis in patients with concurrent herpes zoster. Patients with genetic predispositions may rarely have disease triggered by receipt of varicella vaccine. Overall, serious Adverse Events reported after varicella vaccination continue to be rare and must be considered relative to the substantial benefits of varicella vaccination. Ongoing safety surveillance and further studies may shed light on some of the hypothesized associations.
-
intussusception among recipients of rotavirus vaccine reports to the vaccine Adverse Event reporting system
Pediatrics, 2001Co-Authors: Lynn Zanardi, Penina Haber, Gina T Mootrey, Melinda WhartonAbstract:Background. Rotavirus vaccine was li- censed on August 31, 1998, and subsequently recom- mended for routine use among infants. To assess rare Adverse Events, postlicensure surveillance was con- ducted. Objective. To describe the cases of intussusception among rotavirus vaccine recipients reported to the Vac- cine Adverse Event Reporting System from October 1998 through December 1999. Setting and Participants. Infants vaccinated with ro- tavirus vaccine in the United States. Outcome Measures. Intussusception confirmed by ra- diology, surgery, or autopsy report with medical record documentation or confirmed by a primary health care provider. Results. There were 98 confirmed cases of intussus- ception after vaccination with rotavirus vaccine reported to the Vaccine Adverse Event Reporting System; 60 of these developed intussusception within 1 week after vac- cination. Based on calculations using vaccine distribu- tion data and intussusception incidence rates from 2 sep- arate databases, an estimated 7 to 16 cases would have been expected to occur in the week after vaccination by chance alone. Conclusion. Using a passive surveillance system for vaccine Adverse Events, we observed at least a fourfold increase over the expected number of intussusception cases occurring within 1 week of receipt of rotavirus vaccine. Other studies were initiated to further define the relationship between rotavirus vaccine and intussuscep- tion. In light of these and other data, the rotavirus vac- cine manufacturer voluntarily removed its product from the market, and the recommendation for routine use of rotavirus vaccine among US infants has been withdrawn. Pediatrics 2001;107(6). URL: http://www.pediatrics.org/ cgi/content/full/107/6/e97; intussusception, rotavirus vac- cine, Vaccine Adverse Event Reporting System, vaccine safety.