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Identifiability of Biologicals in Adverse Drug Reaction Reports Received From European Clinical Practice.

ABSTRACT: Biologicals are established treatment options that require pharmacovigilance adapted to their specific nature, including the need for products to be identifiable up to the specific manufacturer in reports of adverse drug reactions (ADRs). This study explored the identifiability of 10 classes of similar and related biologicals up to the level of the manufacturer in ADR reports received from European clinical practice between 2011 and June 2016. Adequate identifiers were reported for 96.7% of the suspected biologicals, ranging from 89.5% for filgrastim to 99.8% for interferon beta-1a. The product identifiability remained consistently high over time for classes of biologicals for which biosimilars were introduced during follow-up. The overall batch traceability was, however, only ensured for 20.5% of the suspected biologicals and needs further improvement. This study shows that the European system for identification of ADRs to the level of the manufacturer is robust, allowing for the timely detection of potential product-specific safety signals for biologicals.

SUBMITTER: Vermeer NS

PROVIDER: S-EPMC6590109 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Identifiability of Biologicals in Adverse Drug Reaction Reports Received From European Clinical Practice.

Vermeer Niels S NS Giezen Thijs J TJ Zastavnik Sofia S Wolff-Holz Elena E Hidalgo-Simon Ana A

Clinical pharmacology and therapeutics 20190111 4

Biologicals are established treatment options that require pharmacovigilance adapted to their specific nature, including the need for products to be identifiable up to the specific manufacturer in reports of adverse drug reactions (ADRs). This study explored the identifiability of 10 classes of similar and related biologicals up to the level of the manufacturer in ADR reports received from European clinical practice between 2011 and June 2016. Adequate identifiers were reported for 96.7% of the ...[more]

PMID: 30460997

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Project description:BackgroundThe prediction of the real-world cost of adverse drug reactions (ADRs) has historically relied on the data from randomized controlled trials (RCT). However, trial conditions do not always reflect the real-world applications of pharmaceutical products; hence, they may not accurately portray the actual risks of ADRs associated with them. The objective of this study is two-fold: (a) demonstrate whether and how post-market and RCT ADR data could lead to different conclusions for a set of drugs of interest, and (b) evaluate the potential economic impact of the post-market ADRs associated with those drugs.MethodsWe selected two TNF-α inhibitor biologics, infliximab and adalimumab, and used the Canada Vigilance Adverse Reaction (CVAR) online database as a source of post-market ADR data. Adverse reaction data from RCTs were obtained from ClinicalTrials.gov . Direct healthcare costs associated with adverse reactions were obtained from Canadian Institute for Health Information (CIHI) or Interactive Health Data Application, Alberta. We calculated post-market ADR rates and compared them with those found in the randomized controlled trials of these two drugs. Using the post-market data, we estimated the costs associated with serious ADRs from three perspectives: patient, health system, and societal.ResultsFor both drugs, the post-market and RCT data exhibited significantly different adverse reaction rates for several different clinical outcomes. As a general trend, more serious adverse reactions, such as death, appeared to have a higher rate in post-market applications compared to the clinical trials. The estimated average annual economic burden of the severe adverse reaction outcomes ranged from $10 million to $20 million for infliximab and $6 million to $19 million for adalimumab.ConclusionsThe frequency and severity of post-market adverse reactions associated with pharmaceutical products may significantly differ from those detected in the clinical trials. Despite possible methodological differences, this is due to the fact that post-market data reflect the externalities of the real-world that are absent in RCTs. The economic burden of adverse reactions can be substantial, and the cost calculated using post-market data is better reflective of the cost of ADRs in the real-world.

Project description:IntroductionAngioedema is a subcutaneous swelling typically affecting the face, larynx or pharynx. It is a known adverse drug reaction (ADR) of ACE inhibitors (ACEi), angiotensin-II-receptor blockers (ARBs) and aliskiren (renin inhibitor). Several studies have reported pathophysiological mechanisms and risk factors of ACEi-associated angioedemas, whereas little is known for ARBs and aliskiren. The aim of the study was to analyze comparatively ACEi versus ARBs and aliskiren angioedema reports contained in the European ADR database EudraVigilance with regard to reported risk factors and clinical phenotypes.MethodsAll spontaneous angioedema reports received between 01/2010-06/2017 reporting either an ACEi, ARB, or aliskiren as "suspected/interacting" drug were identified using the Standardized MedDRA Query "angioedema (narrow)". In order to perform a comparative analysis, odds ratios (ORs) were calculated for angioedema reports of ACEi (n = 3.194) versus ARBs (n = 687) and aliskiren (n = 162).ResultsMore patients with a history of allergy were included in angioedema reports of ARBs (6.8%) and aliskiren (13.6%) versus ACEi (4.3%). "Urticaria" as an ADR was reported more frequently in angioedema reports of ARBs (18.5%) and aliskiren (9.0%) versus ACEi (5.0%). ACEi-associated angioedemas were more often designated as "life-threatening" compared to ARBs (OR 2.2 [1.6-2.9]) and aliskiren-associated angioedemas (OR 14.2 (3.5-57.4). Concomitant therapy with mTOR inhibitors (OR 4.3 [1.0-17.9]) and fibrinolytics (OR 7.8 [1.1-57.2]) was reported more often in ACEi versus ARBs angioedema reports.ConclusionThe reported clinical phenotypes differed between ACEi versus ARBs and aliskiren angioedema reports. Differences between the patient populations as observed in our study or differences with regard to underlying pathomechanisms could account for this finding. Due to the methodological limitations of spontaneous reporting systems, we cannot draw a firm conclusion in this regard. Hence, further research is necessary to confirm our observation and elucidate the underyling causes.

Project description:Allergic reactions to medication range from mild to severe or even life-threatening. Proper documentation of patient allergy information is critical for safe prescription, avoiding drug interactions, and reducing healthcare costs. Allergy information is regularly obtained during the medical interview, but is often poorly documented in electronic health records (EHRs). While many EHRs allow for structured adverse drug reaction (ADR) reporting, a free-text entry is still common. The resulting information is neither interoperable nor easily reusable for other applications, such as clinical decision support systems and prescription alerts. Current approaches require pharmacists to review and code ADRs documented by healthcare professionals. Recently, the effectiveness of machine algorithms in natural language processing (NLP) has been widely demonstrated. Our study aims to develop and evaluate different NLP algorithms that can encode unstructured ADRs stored in EHRs into institutional symptom terms. Our dataset consists of 79,712 pharmacist-reviewed drug allergy records. We evaluated three NLP techniques: Naive Bayes—Support Vector Machine (NB-SVM), Universal Language Model Fine-tuning (ULMFiT), and Bidirectional Encoder Representations from Transformers (BERT). We tested different general-domain pre-trained BERT models, including mBERT, XLM-RoBERTa, and WanchanBERTa, as well as our domain-specific AllergyRoBERTa, which was pre-trained from scratch on our corpus. Overall, BERT models had the highest performance. NB-SVM outperformed ULMFiT and BERT for several symptom terms that are not frequently coded. The ensemble model achieved an exact match ratio of 95.33%, a F1 score of 98.88%, and a mean average precision of 97.07% for the 36 most frequently coded symptom terms. The model was then further developed into a symptom term suggestion system and achieved a Krippendorff’s alpha agreement coefficient of 0.7081 in prospective testing with pharmacists. Some degree of automation could both accelerate the availability of allergy information and reduce the efforts for human coding.

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Identifiability of Biologicals in Adverse Drug Reaction Reports Received From European Clinical Practice.

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Identifiability of Biologicals in Adverse Drug Reaction Reports Received From European Clinical Practice.

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