Hypersensitivity Adverse Event Reporting in Clinical Cancer Trials: Barriers and Potential Solutions to Studying Severe Events on a Population Level

ABSTRACT HYPERSENSITIVITY ADVERSE EVENT REPORTING IN CLINICAL CANCER TRIALS: BARRIERS AND POTENTIAL SOLUTIONS TO STUDYING ALLERGIC EVENTS ON A POPULATION LEVEL by Christina Eldredge The University of Wisconsin-Milwaukee, 2020 Under the Supervision of Professor Timothy Patrick Clinical cancer trial interventions are associated with hypersensitivity events (HEs) which are recorded in the national clinical trial registry, ClinicalTrials.gov and publicly available. This data could potentially be leveraged to study predictors for HEs to identify at risk patients who may benefit from desensitization therapies to prevent these potentially life-threatening reactions. However, variation in investigator reporting methods is a barrier to leveraging this data for aggregation and analysis. The National Cancer Institute has developed the CTCAE classification system to address this barrier. This study analyzes the comprehensiveness of CTCAE to describe severe HEs in clinical cancer trials in comparison to other systems or terminologies. An XML parser was used to extract readable text from adverse event tables. Queries of the parsed data elements were performed to identify immune disorder events associated with biological and chemotherapy interventions. A data subset of severe anaphylactic and anaphylactoid events was created and analyzed. 1,331 clinical trials with 13088 immune disorder events occurred from September 20, 1999 to March 2018. 2409 (18.4%) of these were recorded as “serious” events. In the severe subset, MedDRA terminology, CTCAE or CTC classification systems were used to describe HEs, however, a large number of studies did not specify the system. The CTCAE term “anaphylaxis” was miscoded as “other (not including serious)” in 76.2% of events. The CTCAE classification system severity grades levels were not used to describe any of the severe events and the majority of terms did not include the allergen and therefore, in dual or multi- drug therapies, the etiologic agent was not identifiable. Furthermore, collection methods were not specified in 76% of events. Therefore, CTCAE was not found to improve the ability to capture event etiology or severity in anaphylaxis and anaphylactoid events in cancer clinical trials. Potential solutions to improving CTCAE HE description include adapting terms with a low percentage of HE severity miscoding (e.g. anaphylactic reaction) and terms which include drugs, biological agents and/or drug classes to improve study of anaphylaxis etiology and incidence in multi-drug cancer therapy, therefore, making a significant impact on patient safety

Developing Metadata Categories as a Strategy to Mobilize Computable Biomedical Knowledge

A work by a group of volunteer members drawn from the Mobilizing Computable Biomedical Knowledge community's Standards Workgroup. See mobilizecbk.org for more information about this community and workgroup.Computable biomedical knowledge artifacts (CBKs) are digital objects or entities representing biomedical knowledge as machine-independent data structures that can be parsed and processed by different information systems. The breadth of content represented in CBKs spans all biomedical knowledge related to human health and so it includes knowledge about molecules, cells, organs, individual people, human populations, and the environment. CBKs vary in their scope, purpose, and audience. Some CBKs support biomedical research. Other CBKs help improve health outcomes by enabling clinical decision support, health education, health promotion, and population health analytics. In some instances, CBKs have multiple uses that span research, education, clinical care, or population health. As the number of CBKs grows large, producers must describe them with structured, searchable metadata so that consumers can find, deploy, and use them properly. This report delineates categories of metadata for describing CBKs sufficiently to enable CBKs to be mobilized for various purposes.https://deepblue.lib.umich.edu/bitstream/2027.42/155655/1/MCBK.Metadata.Paper.June2020.f.pdfDescription of MCBK.Metadata.Paper.June2020.f.pdf : MCBK 2020 Virtual Meeting version of Standards Workgroup's Working Paper on CBK Metadat

Cheek Tooth Morphology and Ancient Mitochondrial DNA of Late Pleistocene Horses from the Western Interior of North America: Implications for the Taxonomy of North American Late Pleistocene Equus

Horses were a dominant component of North American Pleistocene land mammal communities and their remains are well represented in the fossil record. Despite the abundant material available for study, there is still considerable disagreement over the number of species of Equus that inhabited the different regions of the continent and on their taxonomic nomenclature. In this study, we investigated cheek tooth morphology and ancient mtDNA of late Pleistocene Equus specimens from the Western Interior of North America, with the objective of clarifying the species that lived in this region prior to the end-Pleistocene extinction. Based on the morphological and molecular data analyzed, a caballine (Equus ferus) and a non-caballine (E. conversidens) species were identified from different localities across most of the Western Interior. A second non-caballine species (E. cedralensis) was recognized from southern localities based exclusively on the morphological analyses of the cheek teeth. Notably the separation into caballine and non-caballine species was observed in the Bayesian phylogenetic analysis of ancient mtDNA as well as in the geometric morphometric analyses of the upper and lower premolars. Teeth morphologically identified as E. conversidens that yielded ancient mtDNA fall within the New World stilt-legged clade recognized in previous studies and this is the name we apply to this group. Geographic variation in morphology in the caballine species is indicated by statistically different occlusal enamel patterns in the specimens from Bluefish Caves, Yukon Territory, relative to the specimens from the other geographic regions. Whether this represents ecomorphological variation and/or a certain degree of geographic and genetic isolation of these Arctic populations requires further study

Health Information Seeking Behaviors on Social Media During the COVID-19 Pandemic Among American Social Networking Site Users: Survey Study

BackgroundIn recent years, medical journals have emphasized the increasingly critical role that social media plays in the dissemination of public health information and disease prevention guidelines. However, platforms such as Facebook and Twitter continue to pose unique challenges for clinical health care providers and public health officials alike. In order to effectively communicate during public health emergencies, such as the COVID-19 pandemic, it is increasingly critical for health care providers and public health officials to understand how patients gather health-related information on the internet and adjudicate the merits of such information. ObjectiveWith that goal in mind, we conducted a survey of 1003 US-based adults to better understand how health consumers have used social media to learn and stay informed about the COVID-19 pandemic, the extent to which they have relied on credible scientific information sources, and how they have gone about fact-checking pandemic-related information. MethodsA web-based survey was conducted with a sample that was purchased through an industry-leading market research provider. The results were reported with a 95% confidence level and a margin of error of 3. Participants included 1003 US-based adults (aged ≥18 years). Participants were selected via a stratified quota sampling approach to ensure that the sample was representative of the US population. Balanced quotas were determined (by region of the country) for gender, age, race, and ethnicity. ResultsThe results showed a heavy reliance on social media during the COVID-19 pandemic; more than three-quarters of respondents (762/1003, 76%) reported that they have relied on social media at least “a little,” and 59.2% (594/1003) of respondents indicated that they read information about COVID-19 on social media at least once per week. According to the findings, most social media users (638/1003, 63.6%) were unlikely to fact-check what they see on the internet with a health professional, despite the high levels of mistrust in the accuracy of COVID-19–related information on social media. We also found a greater likelihood of undergoing vaccination among those following more credible scientific sources on social media during the pandemic (χ216=50.790; φ=0.258; P<.001). ConclusionsThe findings suggest that health professionals will need to be both strategic and proactive when engaging with health consumers on social media if they hope to counteract the deleterious effects of misinformation and disinformation. Effective training, institutional support, and proactive collaboration can help health professionals adapt to the evolving patterns of health information seeking

Assessing the Readiness of a School System to Adopt Food Allergy Management Guidelines

IMPORTANCE: The prevalence of potentially fatal food allergies in school-aged children is rising. It is important for schools to have a food allergy management policy and an emergency action plan for each affected student. OBJECTIVE: To examine the current status of food allergy guideline and/or policy implementation and adoption in a large school system in southeastern Wisconsin. DESIGN: A 24-item anonymous electronic survey was developed and completed by school principals and administrators in the Archdiocese of Milwaukee School System (approximately 125 schools) in southeastern Wisconsin. RESULTS: One in 4 responding schools reported no guidelines or policy. Schools that reported having students with special needs due to food allergy were more likely to have a local food allergy policy compared to schools that did not report having students with food allergy special needs (OR 6.3, 1.5-26, P = 0.01). Schools with food allergy guidelines/policies were 3.5 times more likely to require student individual action plans than schools with no guidelines or policies (OR 3.5, 1.00-12.2, P = 0.05). CONCLUSIONS: Gaps in evidence-based food allergy policy implementation were found in this school system. Schools with food-allergic children with special needs were more likely to have guidelines/policy, however, they were not more likely to require emergency action plans. The majority of schools (66, 90%) reported interest in receiving further information or training on food allergy management

Population Analysis of Adverse Events in Different Age Groups Using Big Clinical Trials Data

BACKGROUND: Understanding adverse event patterns in clinical studies across populations is important for patient safety and protection in clinical trials as well as for developing appropriate drug therapies, procedures, and treatment plans. OBJECTIVES: The objective of our study was to conduct a data-driven population-based analysis to estimate the incidence, diversity, and association patterns of adverse events by age of the clinical trials patients and participants. METHODS: Two aspects of adverse event patterns were measured: (1) the adverse event incidence rate in each of the patient age groups and (2) the diversity of adverse events defined as distinct types of adverse events categorized by organ system. Statistical analysis was done on the summarized clinical trial data. The incident rate and diversity level in each of the age groups were compared with the lowest group (reference group) using t tests. Cohort data was obtained from ClinicalTrials.gov, and 186,339 clinical studies were analyzed; data were extracted from the 17,853 clinical trials that reported clinical outcomes. The total number of clinical trial participants was 6,808,619, and total number of participants affected by adverse events in these trials was 1,840,432. The trial participants were divided into eight different age groups to support cross-age group comparison. RESULTS: In general, children and older patients are more susceptible to adverse events in clinical trial studies. Using the lowest incidence age group as the reference group (20-29 years), the incidence rate of the 0-9 years-old group was 31.41%, approximately 1.51 times higher (P=.04) than the young adult group (20-29 years) at 20.76%. The second-highest group is the 50-59 years-old group with an incidence rate of 30.09%, significantly higher (P CONCLUSION: The results show that there is a significant adverse event variance at the population level between different age groups in clinical trials. The data suggest that age-associated adverse events should be considered in planning, monitoring, and regulating clinical trials

Big Data Analysis of Drug Induced Hypersensitivity and Anaphylaxis Reactions in Clinical Cancer Trials

The dataset, which included study name, medical condition, intervention, arm titles, and adverse drug reactions, was queried for drug hypersensitivity reactions using the key terms: hypersensitivity, allergic reaction, allergy, anaphylaxis, allergic dermatitis, and drug hypersensitivity. Results Preliminary population analysis of 425 of the 1605 qualifying clinical trials from this dataset revealed 3,013 adverse drug hypersensitivity reactions of 118,159 patients at risk for HSRs (2.5% incidence)

Development of an Adverse Drug Reaction Corpus from Consumer Health Posts

UWM-Adverse Drug Events Corpus (UWM-ADEC) is an annotated corpus that has been developed from consumer drug review posts in social media. In this corpus, we identified four types of Adverse Drug Reactions (ADRs) including physiological, psychological, cognitive, and functional problems. Additionally, we mapped the ADRs to corresponding concepts in Unified medical language Systems (UMLS). The quality of the corpus was measured using well-defined guidelines, double coding, high inter-annotator agreement, and final reviews by pharmacists and clinical terminologists. This corpus is a valuable source for research in the area of text mining and machine learning for ADRs identifications from consumer health posts, specifically for psychiatric medication