Niklas Norén

Uppsala Monitoring Centre · Research

Objective To describe and evaluate vigiGroup - a consensus clustering algorithm which can identify groups of individual case reports referring to similar suspected adverse drug reactions and describe associated adverse event profiles, accounting for co-reported adverse event terms. Materials and methods Consensus clustering is achieved by grouping...

Large collections of electronic patient records provide a vast but still underutilised source of information on the real world use of medicines. They are maintained primarily for the purpose of patient administration, but contain a broad range of clinical information highly relevant for data analysis. While they are a standard resource for epidemio...

The WHO Collaborating Centre for International Drug Monitoring in Uppsala, Sweden, maintains and analyses the world’s largest database of reports on suspected adverse drug reaction (ADR) incidents that occur after drugs are on the market. The presence of duplicate case reports is an important data quality problem and their detection remains a formi...

Large observational data sets are a great asset to better understand the effects of medicines in clinical practice and, ultimately, improve patient care. For an empirical pattern in observational data to be of practical relevance, it should represent a substantial deviation from the null model. For the purpose of identifying such deviations, statis...

On April 9, 2019, we searched the WHO database for reports of pneumonia related to clozapine and three other second-generation antipsychotics (SGAs), the most frequently used worldwide – risperidone, quetiapine and olanzapine. For clozapine we found 4,865 reports of pneumonia, which corresponds to 3.5% of all clozapine reports in the database and e...

Introduction and objective: Signals of adverse drug reactions (ADRs) can be supported by reports of ADRs and by interventional and non-interventional studies. The evidence base and features of ADR reports that are used to support signals remain to be comprehensively described. To this end, we have undertaken a scoping review. Methods: We searche...

IntroductionVortioxetine, a multimodal serotonergic drug, is widely used as treatment for major depressive disorder. Although on the market since late 2013, the data of the relative safety of vortioxetine, especially compared to selective serotonin reuptake inhibitors, are still scarce.Objective The aim of this study was to explore the adverse even...

IntroductionAdverse drug reactions related to drug–drug interactions cause harm to patients. There is a body of research on signal detection for drug interactions in collections of individual case reports, but limited use in regular pharmacovigilance.Objective The aim of this study was to evaluate the feasibility of signal detection of drug–drug in...

IntroductionIncreased post-marketing reports of interstitial lung disease in Japan have been recognized. An understanding of its regional groundings can be important for the global pharmacovigilance community.Objective The objective of this study was to explore the correlation between high rates of interstitial lung disease reporting and regulatory...

The article "Communicating Adverse Drug Reaction Insights Through Patient Organizations: Experiences from a Pilot Study in the Netherlands", written by Linda Härmark, Gerda Weits, Rietje Meijer, Federica Santoro, G. Niklas Norén, Florence van Hunsel, was originally published electronically on 16 May 2020 without open access.

IntroductionIn the treatment of the individual patient, a vision is to achieve the best possible balance between benefit and harm. Such tailored therapy relies upon the identification and characterisation of risk factors for adverse drug reactions. Information relevant to risk factor considerations can be captured in adverse event reports and could...

IntroductionTo improve therapeutic decision making, it is crucial that information regarding adverse drug reactions reaches patients. It is not enough to disseminate such findings through regulatory and scientific channels; targeted efforts to reach patients are necessary. One possible avenue is to collaborate with patient organizations.Objectives...

Introduction Adverse event reporting patterns vary between countries, reflecting differences in reporting culture, clinical practice and underlying patient populations. Japan collects about 60,000 domestic adverse event reports yearly and shares serious reports with the World Health Organization (WHO) Programme for International Drug Monitoring in...

Over a period of 3 years, the European Union’s Innovative Medicines Initiative WEB-RADR project has explored the value of social media (i.e., information exchanged through the internet, typically via online social networks) for identifying adverse events as well as for safety signal detection. Many patients and clinicians have taken to social media...

The article vigiGrade: A Tool to Identify Well-Documented Individual Case Reports and Highlight Systematic Data Quality Issues, written by Tomas Bergvall. G. Niklas Norén. Marie Lindquist, was originally published Online First without open access

The article “vigiGrade: A Tool to Identify Well-Documented Individual Case Reports and Highlight Systematic Data Quality Issues”.

Introduction and Objective Social media has been proposed as a possibly useful data source for pharmacovigilance signal detection. This study primarily aimed to evaluate the performance of established statistical signal detection algorithms in Twitter/Facebook for a broad range of drugs and adverse events. Methods Performance was assessed using a r...

Purpose: To develop a method for data-driven exploration in pharmacovigilance and illustrate its use by identifying the key features of individual case safety reports related to medication errors. Methods: We propose vigiPoint, a method that contrasts the relative frequency of covariate values in a data subset of interest to those within one or...

Purpose: vigiRank is a data-driven predictive model for emerging safety signals. In addition to disproportionate reporting patterns, it also accounts for the completeness, recency, and geographic spread of individual case reporting, as well as the availability of case narratives. Previous retrospective analysis suggested that vigiRank performed be...

IntroductionA number of safety signals—complex regional pain syndrome (CRPS), postural orthostatic tachycardia syndrome (POTS), and chronic fatigue syndrome (CFS)—have emerged with human papillomavirus (HPV) vaccines, which share a similar pattern of symptomatology. Previous signal evaluations and epidemiological studies have largely relied on trad...

Over a period of 5 years, the Innovative Medicines Initiative PROTECT (Pharmacoepidemiological Research on Outcomes of Therapeutics by a European ConsorTium) project has addressed key research questions relevant to the science of safety signal detection. The results of studies conducted into quantitative signal detection in spontaneous reporting, c...

Introduction Disproportionality analyses are used in many organisations to identify adverse drug reactions (ADRs) from spontaneous report data. Reporting patterns vary over time, with patient demographics, and between different geographical regions, and therefore subgroup analyses or adjustment by stratification may be beneficial. Objective The obj...

Objective Quantitative Structure-Activity Relationship (QSAR) models can predict adverse drug reactions (ADRs), and thus provide early warnings of potential hazards. Timely identification of potential safety concerns could protect patients and aid early diagnosis of ADRs among the exposed. Our objective was to determine whether global spontaneous r...

The vision of creating accessible, reliable clinical evidence by accessing the clincial experience of hundreds of millions of patients across the globe is a reality. Observational Health Data Sciences and Informatics (OHDSI) has built on learnings from the Observational Medical Outcomes Partnership to turn methods research and insights into a suite...

Substandard medicines, whether the result of intentional manipulation or lack of compliance with good manufacturing practice (GMP) or good distribution practice (GDP), pose a significant potential threat to patient safety. Spontaneous adverse drug reaction reporting systems can contribute to identification of quality problems that cause unwanted an...

Pharmacovigilance signal detection largely relies on individual case reports, but longitudinal health data are being explored as complementary information sources. Research to date has focused on the ability of epidemiological methods to distinguish established adverse drug reactions (ADRs) from unrelated adverse events. The aim of this study was t...

Background: Detection of unknown risks with marketed medicines is key to securing the optimal care of individual patients and to reducing the societal burden from adverse drug reactions. Large collections of individual case reports remain the primary source of information and require effective analytics to guide clinical assessors towards likely d...

Pharmacovigilance seeks to detect and describe adverse drug reactions early. Ideally, we would like to see objective evidence that a chosen signal detection approach can be expected to be effective. The development and evaluation of evidence-based methods require benchmarks for signal detection performance, and recent years have seen unprecedented...

The entire drug safety enterprise has a need to search, retrieve, evaluate, and synthesize scientific evidence more efficiently. This discovery and synthesis process would be greatly accelerated through access to a common framework that brings all relevant information sources together within a standardized structure. This presents an opportunity to...

Quantifying a medicine's risks for adverse effects is crucial in assessing its value as a therapeuticagent. Rare adverse effects are often not detected until after the medicine is marketed and used inlarge and heterogeneous patient populations, and risk quantification is even more difficult. Whileindividual case reports of suspected harm from medic...

Individual case reports of suspected harm from medicines are fundamental for signal detection in postmarketing surveillance. Their effective analysis requires reliable data and one challenge is report duplication. These are multiple unlinked records describing the same suspected adverse drug reaction (ADR) in a particular patient. They distort stat...

Background Individual case safety reports of suspected harm from medicines are fundamental to post-marketing surveillance. Their value is directly proportional to the amount of clinically relevant information they include. To improve the quality of the data, communication between stakeholders is essential and can be facilitated by a simple score an...

Background: Observational healthcare data offer the potential to identify adverse drug reactions that may be missed by spontaneous reporting. The self-controlled cohort analysis within the Temporal Pattern Discovery framework compares the observed-to-expected ratio of medical outcomes during post-exposure surveillance periods with those during a s...

Within pharmacovigilance, knowledge of time-to-onset (time from start of drug administration to onset of reaction) is important in causality assessment of drugs and suspected adverse drug reactions (ADRs) and may indicate pharmacological mechanisms involved. It has been suggested that time-to-onset from individual case reports can be used for detec...

MedDRA terms. List of Lower Level Terms (LLTs) for the two studied MedDRA Preferred Terms (PTs) Angioedema and Hepatitis included in the analysis. (DOCX)

Report demographics. Number of reports in the WHO global ICSR database VigiBase included for each studied drug-ADR pair. (DOCX)

This study aimed to develop an algorithm for uncovering associations masked by extreme reporting rates, characterize the occurrence of masking by influential outliers in two spontaneous reporting databases and evaluate the impact of outlier removal on disproportionality analysis. We propose an algorithm that identifies influential outliers and carr...

To the Editor: In their article, “Performance of Pharmacovigilance Signal-Detection Algorithms for the FDA Adverse Event Reporting System,” Harpaz et al.1 report an evaluation of signal-detection a ...

Background Around 20 % of all adverse drug reactions (ADRs) are due to drug interactions. Some of these will only be detected in the postmarketing setting. Effective screening in large collections of individual case safety reports (ICSRs) requires automated triages to identify signals of adverse drug interactions. Research so far has focused on sta...

A large proportion of potential drug interactions are known from pre-authorization studies, but adverse drug reactions (ADRs) due to interactions (adverse drug interactions) are often first detected through astute observation in clinical practice. Individual case safety reports (ICSRs) are collected from broad patient populations and allow for the...

Utilities of pertinent clinical outcomes are crucial variables for assessing the benefits and risks of drugs, but numerical data on utilities may be unreliable or altogether missing. We propose a method to incorporate qualitative information into a probabilistic decision analysis framework for quantitative benefit-risk assessment. : To investigate...

Background: Utilities of pertinent clinical outcomes are crucial variables for assessing the benefits and risks of drugs, but numerical data on utilities may be unreliable or altogether missing. We propose a method to incorporate qualitative information into a probabilistic decision analysis framework for quantitative benefit-risk assessment. Objec...

The identification of unanticipated statistical associations is a core activity in exploratory analysis of high-dimensional biomedical data. Specifically, post-marketing surveillance for harmful effects of medicines relies on effective algorithms to detect associations between drugs and suspected adverse drug reactions. The WHO global individual ca...

As a first step towards implementing routine screening of safety issues specifically related to children at the Uppsala Monitoring Centre, this study was performed to explore reporting patterns of adverse reactions in children. The first aim of this study was to characterize and contrast child reports against adult reports in an overall drug and ad...

Adverse drug interaction surveillance in collections of Individual Case Safety Reports (ICSRs) remains underdeveloped. Most efforts to date have focused on disproportionality analysis, but the empirical support for its value is based on isolated examples. Additionally, too little attention has been given to the potential value of the detailed conte...

Background: As a first step towards implementing routine screening of safety issues specifically related to children at the Uppsala Monitoring Centre, this study was performed to explore reporting patterns of adverse reactions in children. Objective: The first aim of this study was to characterize and contrast child reports against adult reports in...

Most measures of interestingness for patterns of co-occurring events are based on data projections onto contingency tables for the events of primary interest. As an alternative, this article presents the first implementation of shrinkage logistic regression for large-scale pattern discovery, with an evaluation of its usefulness in real-world binary...

Medicines improve health and the chances of survival in a wide variety of conditions. At the same time, no substance with pharmacological effects is without hazard. Adverse drug reactions (ADRs) can be associated with the intended pharmacological effect of the medicine (eg bleeding from warfarin), mediated by other mechanisms (eg anticholinergic ef...