Ontological and Non-Ontological Resources for Associating Medical Dictionary for Regulatory Activities Terms to SNOMED Clinical Terms With Semantic Properties

Analysis of post-market adverse events of tafamidis base on the FDA adverse event reporting system

Tafamidis is the world's first and only oral drug approved to treat the rare disease transthyretin amyloid cardiomyopathy (ATTR-CM). Medicines are known to have different adverse reactions during the course of treatment. However, the current limited clinical studies did not identify significant adverse drug reactions to tafamidis. Tafamidis has been on the market for 5 years now, a large number of adverse drug event (ADE) reports with tafamidis as the primary suspected drug have been reported in the United Food and Drug Administration's adverse event reporting system (FAERS). We retrieved 8170 adverse event reports in FAERS with tafamidis as the first suspected drug, and mined these reports for positive signals to perform risk warnings for potentially possible adverse events with tafamidis. We found that a large number of adverse events associated with the primary disease were reported due to insufficient awareness of ATTR among the reporters, leading to a large number of positive signals reported in the cardiac disorders system. We also found that tafamidis has the potential to cause an adverse event risks of ear and labyrinth disorders system and urinary tract infection bacterial, which deserve continued clinical attention.

Evaluating MedDRA-to-ICD terminology mappings

BACKGROUND

In this era of big data, data harmonization is an important step to ensure reproducible, scalable, and collaborative research. Thus, terminology mapping is a necessary step to harmonize heterogeneous data. Take the Medical Dictionary for Regulatory Activities (MedDRA) and International Classification of Diseases (ICD) for example, the mapping between them is essential for drug safety and pharmacovigilance research. Our main objective is to provide a quantitative and qualitative analysis of the mapping status between MedDRA and ICD. We focus on evaluating the current mapping status between MedDRA and ICD through the Unified Medical Language System (UMLS) and Observational Medical Outcomes Partnership Common Data Model (OMOP CDM). We summarized the current mapping statistics and evaluated the quality of the current MedDRA-ICD mapping; for unmapped terms, we used our self-developed algorithm to rank the best possible mapping candidates for additional mapping coverage.

RESULTS

The identified MedDRA-ICD mapped pairs cover 27.23% of the overall MedDRA preferred terms (PT). The systematic quality analysis demonstrated that, among the mapped pairs provided by UMLS, only 51.44% are considered an exact match. For the 2400 sampled unmapped terms, 56 of the 2400 MedDRA Preferred Terms (PT) could have exact match terms from ICD.

CONCLUSION

Some of the mapped pairs between MedDRA and ICD are not exact matches due to differences in granularity and focus. For 72% of the unmapped PT terms, the identified exact match pairs illustrate the possibility of identifying additional mapped pairs. Referring to its own mapping standard, some of the unmapped terms should qualify for the expansion of MedDRA to ICD mapping in UMLS.

Understanding the Medical Dictionary for Regulatory Activities (MedDRA) reporting of herpes simplex virus (HSV) adverse events in atopic dermatitis clinical trials

Drug efficacy is best evaluated by randomized, controlled, double-blind clinical trials; however, safety is harder to assess. The Medical Dictionary for Regulatory Activities (MedDRA) is used to track and categorize adverse events (AE) during clinical trials. Recent atopic dermatitis (AD) clinical trials were reviewed to illustrate how an understanding of MedDRA may be helpful when evaluating the rates and nature of adverse events related to herpes simplex virus (HSV) infection. All completed AD clinical trials (excluding phase I studies) with results on clinicaltrials.gov (01/01/2018-01/31/2023) were queried in January 2023. MedDRA version, preferred term (PT) for AEs captured as "HSV", PTs for other AEs possibly related to HSV, frequency thresholds for reporting non-serious AEs, and route of treatment were recorded. Of the 46 clinical trials, 17 had PTs for AEs captured as "HSV". Among all studies, 11 different versions of MedDRA were utilized, from versions 10 to 24.1. In all studies, PTs for AEs captured as "HSV" were listed in the Infections and Infestations system organ class (SOC) classification of MedDRA. PTs varied from "herpes simplex", "herpes virus infection", "herpes ophthalmic", "ophthalmic herpes simplex", "nasal herpes", "oral herpes", "herpes dermatitis", "eczema herpeticum", "genital herpes simplex", and "genital herpes." While one clinical trial of dupilumab (NCT03359356) simply reported the PT "oral herpes" as an AE, a clinical trial of DS107 (NCT03817190) reported the PTs "oral herpes", "herpes simplex", and "herpes virus infection" separately. In the DS107 clinical trial, it is unclear if the same adverse event was reported under multiple PTs or if multiple HSV-related AEs occurred. Although the definition of HSV is unchanged from 2018 to 2023 and there are few changes between MedDRA versions, coding for HSV is complex. HSV events can be reported in different ways, which may impact the interpretation of a drug's safety profile.

Patient safety classification, taxonomy and ontology systems: A systematic review on development and evaluation methodologies

INTRODUCTION

Patient safety classifications/ontologies enable patient safety information systems to receive and analyze patient safety data to improve patient safety. Patient safety classifications/ontologies have been developed and evaluated using a variety of methods. The purpose of this review was to discuss and analyze the methodologies for developing and evaluating patient safety classifications/ontologies.

METHODS

Studies that developed or evaluated patient safety classifications, terminologies, taxonomies, or ontologies were searched through Google Scholar, Google search engines, National Center for Biomedical Ontology (NCBO) BioPortal, Open Biological and Biomedical Ontology (OBO) Foundry and World Health Organization (WHO) websites and Scopus, Web of Science, PubMed, and Science Direct. We updated our search on 30 February 2021 and included all studies published until the end of 2020. Studies that developed or evaluated classifications only for patient safety and provided information on how they were developed or evaluated were included. Systems with covered patient safety terms (such as ICD-10) but are not specifically developed for patient safety were excluded. The quality and the risk of bias of studies were not assessed because all methodologies and criteria were intended to be covered. In addition, we analyzed the data through descriptive narrative synthesis and compared and classified the development and evaluation methods and evaluation criteria according to available development and evaluation approaches for biomedical ontologies.

RESULTS

We identified 84 articles that met all of the inclusion criteria, resulting in 70 classifications/ontologies, nine of which were for the general medical domain. The most papers were published in 2010 and 2011, with 8 and 7 papers, respectively. The United States (50) and Australia (23) have the most studies. The most commonly used methods for developing classifications/ontologies included the use of existing systems (for expanding or mapping) (44) and qualitative analysis of event reports (39). The most common evaluation methods were coding or classifying some safety report samples (25), quantitative analysis of incidents based on the developed classification (24), and consensus among physicians (16). The most commonly applied evaluation criteria were reliability (27), content and face validity (9), comprehensiveness (6), usability (5), linguistic clarity (5), and impact (4), respectively.

CONCLUSIONS

Because of the weaknesses and strengths of the development/evaluation methods, it is advised that more than one method for development or evaluation, as well as evaluation criteria, should be used. To organize the processes of developing classification/ontologies, well-established approaches such as Methontology are recommended. The most prevalent evaluation methods applied in this domain are well fitted to the biomedical ontology evaluation methods, but it is also advised to apply some evaluation approaches such as logic, rules, and Natural language processing (NLP) based in combination with other evaluation approaches. This research can assist domain researchers in developing or evaluating domain ontologies using more complete methodologies. There is also a lack of reporting consistency in the literature and same methods or criteria were reported with different terminologies.