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52 result(s) for "Norén, G. Niklas"
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Risk Factor Considerations in Statistical Signal Detection: Using Subgroup Disproportionality to Uncover Risk Groups for Adverse Drug Reactions in VigiBase
Introduction In 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 be utilised in statistical signal detection. Objective The aim of this study was to explore whether statistical screening of a broad range of risk factors within a global database of adverse event reports could uncover signals of risk groups for adverse drug reactions. Methods Subgroup disproportionality analysis was applied to 15.4 million reports entered in VigiBase, the World Health Organization (WHO) global database of individual case safety reports, up to August 2017. Disproportionality analyses for drug–adverse event pairs were performed (1) in the full database and (2) across a range of subgroups defined by the following covariates: patient age, sex, body mass index, pregnancy, underlying condition, reporting country, and geographical region. Drug–adverse event pairs disproportionately over-reported in such subgroups, but not in the full database, and with a substantial difference between the two observed-to-expected ratios, were highlighted as statistical signals. These were further prioritised, through filtering and sorting, for clinical assessment, whereafter clinically relevant signals were communicated to the pharmacovigilance community and the public. Results Assessments were performed for 354 prioritised statistical signals, resulting in seven communicated signals describing previously unrecognised potential risk groups related to age (elderly), sex (male and female), body mass index (underweight and obese), and geographical region (Asia), all except one for already established adverse drug reactions. Important aspects considered in the assessments included an evaluation of the disproportionate over-reporting in the subgroup by reviewing alternative explanations and reporting patterns for similar drugs/adverse events/subgroups, and a search for plausible mechanisms to support the risk hypothesis. Conclusions This study reveals that it is possible to uncover signals of risk groups for adverse drug reactions through incorporation of broad risk factor screening into statistical signal detection in a global database of adverse event reports. Our findings suggest the potential to use such statistical methodologies for risk characterisation in subpopulations of concern.
The Reporting of a Disproportionality Analysis for Drug Safety Signal Detection Using Individual Case Safety Reports in PharmacoVigilance (READUS-PV): Development and Statement
Background and aim Disproportionality analyses using reports of suspected adverse drug reactions are the most commonly used quantitative methods for detecting safety signals in pharmacovigilance. However, their methods and results are generally poorly reported in published articles and existing guidelines do not capture the specific features of disproportionality analyses. We here describe the development of a guideline (REporting of A Disproportionality analysis for drUg Safety signal detection using individual case safety reports in PharmacoVigilance [READUS-PV]) for reporting the results of disproportionality analyses in articles and abstracts. Methods We established a group of 34 international experts from universities, the pharmaceutical industry, and regulatory agencies, with expertise in pharmacovigilance, disproportionality analyses, and assessment of safety signals. We followed a three-step process to develop the checklist: (1) an open-text survey to generate a first list of items; (2) an online Delphi method to select and rephrase the most important items; (3) a final online consensus meeting. Results Among the panel members, 33 experts responded to round 1 and 30 to round 2 of the Delphi and 25 participated to the consensus meeting. Overall, 60 recommendations for the main body of the manuscript and 13 recommendations for the abstracts were retained by participants after the Delphi method. After merging of some items together and the online consensus meeting, the READUS-PV guidelines comprise a checklist of 32 recommendations, in 14 items, for the reporting of disproportionality analyses in the main body text and four items, comprising 12 recommendations, for abstracts. Conclusions The READUS-PV guidelines will support authors, editors, peer-reviewers, and users of disproportionality analyses using individual case safety report databases. Adopting these guidelines will lead to more transparent, comprehensive, and accurate reporting and interpretation of disproportionality analyses, facilitating the integration with other sources of evidence.
Improved Statistical Signal Detection in Pharmacovigilance by Combining Multiple Strength-of-Evidence Aspects in vigiRank
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 drug safety signals. Disproportionality analysis is based solely on aggregate numbers of reports and naively disregards report quality and content. However, these latter features are the very fundament of the ensuing clinical assessment. Objective Our objective was to develop and evaluate a data-driven screening algorithm for emerging drug safety signals that accounts for report quality and content. Methods vigiRank is a predictive model for emerging safety signals, here implemented with shrinkage logistic regression to identify predictive variables and estimate their respective contributions. The variables considered for inclusion capture different aspects of strength of evidence, including quality and clinical content of individual reports, as well as trends in time and geographic spread. A reference set of 264 positive controls (historical safety signals from 2003 to 2007) and 5,280 negative controls (pairs of drugs and adverse events not listed in the Summary of Product Characteristics of that drug in 2012) was used for model fitting and evaluation; the latter used fivefold cross-validation to protect against over-fitting. All analyses were performed on a reconstructed version of VigiBase ® as of 31 December 2004, at around which time most safety signals in our reference set were emerging. Results The following aspects of strength of evidence were selected for inclusion into vigiRank: the numbers of informative and recent reports, respectively; disproportional reporting; the number of reports with free-text descriptions of the case; and the geographic spread of reporting. vigiRank offered a statistically significant improvement in area under the receiver operating characteristics curve (AUC) over screening based on the Information Component (IC) and raw numbers of reports, respectively (0.775 vs. 0.736 and 0.707, cross-validated). Conclusions Accounting for multiple aspects of strength of evidence has clear conceptual and empirical advantages over disproportionality analysis. vigiRank is a first-of-its-kind predictive model to factor in report quality and content in first-pass screening to better meet tomorrow’s post-marketing drug safety surveillance needs.
Data-Driven Identification of Adverse Event Reporting Patterns for Japan in VigiBase, the WHO Global Database of Individual Case Safety Reports
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 VigiBase, the WHO global database of individual case safety reports. Understanding these reports in the global context can be helpful for regulators worldwide and can aid hypothesis-generation for Japanese-specific vulnerabilities to adverse drug reactions. Objective The objective of this study was to explore differences in the reporting of adverse events between Japan and other countries. Methods vigiPoint is a method for data-driven exploration in pharmacovigilance. It outlines data subsets, pinpoints key features and facilitates expert review, using odds ratios subjected to statistical shrinkage to distinguish one data subset from another. Here, we compared 260,000 Japanese reports in E2B format classified as serious and received in VigiBase between 2013 and 2018 with 2.5 million reports from the rest of the world (of which 51% are from the USA). Reporting patterns for which the 99% credibility interval of the shrunk log-odds ratios were above 0.5 or below − 0.5 were flagged as key features. The shrinkage was set to the vigiPoint default corresponding to 1% of the size of the Japanese data subset. As a sensitivity analysis, additional vigiPoint comparisons were performed between Japan and, in turn, Africa, the Americas, the Americas except the USA and Canada, Asia and Europe. Results There were higher reporting rates in Japan from physicians (83% vs. 39%) and pharmacists (17% vs. 10%). It was also more common to see reports with more than five drugs per report (22% vs. 14%) and with a single adverse event (72% vs. 45%). More than half of the Japanese reports had a vigiGrade completeness score above 0.8 compared with about one in five from the rest of the world. There were more reports than expected for patients aged 70–89 years and fewer reports for adults aged 20–59 years. Adverse events reported more often in Japan included interstitial lung disease, abnormal hepatic function, decreased platelet count, decreased neutrophil count and drug eruption. Adverse events reported less often included death, fatigue, dyspnoea, pain and headache. Drugs reported more often in Japan included prednisolone, methotrexate and peginterferon alfa-2b. Drugs reported less often included rosiglitazone and adalimumab as well as blood substitutes and perfusion solutions. The findings were generally robust to the sensitivity analysis except for the less often reported drugs, many of which were rarely reported in most countries, except in the USA. Conclusion Analysis of Japanese adverse event reporting patterns in a global context has revealed key features that may reflect possible pharmaco-ethnic vulnerabilities in the Japanese, as well as differences in adverse event reporting and clinical practice. This knowledge is essential in the global collaboration of signal detection afforded by the WHO Programme for International Drug Monitoring.
Interstitial Lung Disease as an Adverse Drug Reaction in Japan: Exploration of Regulatory Actions as a Basis for High Reporting
Introduction Increased 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 actions in Japan. Methods Post-marketing interstitial lung disease-related label changes and interstitial lung disease reports were classified by the anatomical therapeutic chemical classification groups of the suspected drugs. Regulatory actions for the top interstitial lung disease-reporting drugs were compared. The interstitial lung disease reporting patterns of protein kinase inhibitors were compared to those of methotrexate. Results Interstitial lung disease-related label changes predominantly occurred for drugs in the anatomical therapeutic chemical classification groups L, J, C, and herbal medicines. Interstitial lung disease was reported most frequently for L group, especially for the protein kinase inhibitors. The regulatory actions for those drugs with the highest number of interstitial lung disease reports (methotrexate, protease kinase inhibitors, gemcitabine, docetaxel) plus monoclonal antibodies were analyzed. The ratio of interstitial lung disease reports to all reports over time was initially high in the re-examination period, while it was constantly low after the period expired. The increase in interstitial lung disease reporting was observed for the drugs for which interstitial lung disease was designated as a priority item in the use-results survey. Methotrexate had more interstitial lung disease reports with multiple suspected drugs and fewer reports with high completeness than the protease kinase inhibitors. Conclusions The high rates of interstitial lung disease reporting derived from mainly the anatomical therapeutic chemical classification group L drugs. Interstitial lung disease is the targeted adverse drug reaction in the use-results survey mandated in the re-examination of those drugs. This system provides at least one explanation for the high reporting of interstitial lung disease in Japan.
A Feasibility Study of Drug–Drug Interaction Signal Detection in Regular Pharmacovigilance
Introduction Adverse 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 interactions in collections of individual case reports of suspected adverse drug reactions. Methods This study was conducted in VigiBase, the WHO global database of individual case safety reports. The data lock point was 31 August 2016, which provided 13.6 million reports for analysis after deduplication. Statistical signal detection was performed using a previously developed predictive model for possible drug interactions. The model accounts for an interaction disproportionality measure, expressed suspicion of an interaction by the reporter, potential for interaction through cytochrome P450 activity of drugs, and reported information indicative of unexpected therapeutic response or altered therapeutic effect. Triage filters focused the preliminary signal assessment on combinations relating to serious adverse events with case series of no more than 30 reports from at least two countries, with at least one report during the previous 2 years. Additional filters sought to eliminate already known drug interactions through text mining of standard literature sources. Preliminary signal assessment was performed by a multidisciplinary group of pharmacovigilance professionals from Uppsala Monitoring Centre and collaborating organizations, whereas in-depth signal assessment was performed by experienced pharmacovigilance assessors. Results We performed preliminary signal assessment for 407 unique drug pairs. Of these, 157 drug pairs were considered already known to interact, whereas 232 were closed after preliminary assessment for other reasons. Ten drug pairs were subjected to in-depth signal assessment and an additional eight were decided to be kept under review awaiting additional reports. The triage filters had a major impact in focusing our preliminary signal assessment on just 14% of the statistical signals generated by the predictive model for drug interactions. In-depth assessment led to three signals communicated with the broader pharmacovigilance community, six closed signals and one to be kept under review. Conclusion This study shows that signals of adverse drug interactions can be detected through broad statistical screening of individual case reports. It further shows that signal assessment related to possible drug interactions requires more detailed information on the temporal relationship between different drugs and the adverse event. Future research may consider whether interaction signal detection should be performed not for individual adverse event terms but for pairs of drugs across a spectrum of adverse events.
Suspected Adverse Drug Reactions Reported For Children Worldwide
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 an overall drug and adverse reaction review. The second aim was to highlight increases in reporting of specific adverse reactions during recent years subdivided by age group. Study Design: This was an exploratory study of internationally compiled individual case safety reports (ICSRs). Setting: Reports were extracted from the WHO global ICSR database, VigiBase, up until 5 February 2010. The reports in VigiBase originate from 97 countries and the likelihood that a medicine caused the adverse effect may vary from case to case. Suspected duplicate and vaccine reports were excluded from the analysis, as were reports with age not specified. The Medical Dictionary for Regulatory Activities (MedDRA®) and the WHO Anatomical Therapeutic Chemical (ATC) classification were used to group adverse reactions and drugs. Patients: In the general review, reports from 1968 to 5 February 2010 were divided into child (aged 0–17 years) and adult (≥18 years) age groups. To highlight increases in reporting rates of specific adverse reactions during recent years, reports from 2005 to February 2010 were compared with reports from 1995 to 1999. The ten adverse reactions with the greatest difference in the proportion of reports between the two time periods were reviewed. In the latter analysis, the reports were subdivided into age groups: neonates ≤27 days; infants 28 days–23 months; children 2–11 years; and adolescents 12–17 years. Results: A total of 3 472 183 reports were included in the study, of which 7.7% (268 145) were reports for children (0–17 years). Fifty-three percent of the child reports were for males, whilst 39% of reports in the adult group were for males. The proportion of reports involving children among Asian reports was 14% and was 15% among reports from Africa and Latin America, including the Caribbean. Among reports from North America, Oceania and Europe, 7% of the reports involved children. For the ATC drug classification groups, the largest difference in percentage units between the child and adult groups was seen for the anti-infective (33 vs 15%), respiratory (11 vs 5%) and dermatological (12 vs 7%) drug groups. Skin reactions were most commonly reported for the children; these were recorded in 35% of all reports for children and 23% of all reports for adults. Medication error-related terms in the younger age groups were reported with an increased frequency during recent years. This was particularly noticeable for the infants aged 28 days–23 months, recorded with accidental overdose and drug toxicity. Reactions reported in suspected connection to medicines used for attention-deficit hyperactivity disorders (ADHD) completely dominated the 2-to 11-year age group and were also common for the adolescents. This study presents variations in the reporting pattern in different age groups in VigiBase which, in some cases, could be due to susceptibilities to specific drug-related problems in certain age groups. Other likely explanations might be common drug usage and childhood diseases in these age groups. Conclusions: Reports in VigiBase received internationally for more than 40 years reflect real concerns for children taking medicines. The study highlights adverse reactions with an increased reporting during recent years, particularly those connected to the introduction of ADHD medicines in the child population. To enhance patient safety, medication errors indicating administration and dosing difficulties of drugs, especially in the younger age groups, require further attention.
Automated redaction of names in adverse event reports using transformer-based neural networks
Background Automated recognition and redaction of personal identifiers in free text can enable organisations to share data while protecting privacy. This is important in the context of pharmacovigilance since relevant detailed information on the clinical course of events, differential diagnosis, and patient-reported reflections may often only be conveyed in narrative form. The aim of this study is to develop and evaluate a method for automated redaction of person names in English narrative text on adverse event reports. The target domain for this study was case narratives from the United Kingdom’s Yellow Card scheme, which collects and monitors information on suspected side effects to medicines and vaccines. Methods We finetuned BERT – a transformer-based neural network – for recognising names in case narratives. Training data consisted of newly annotated records from the Yellow Card data and of the i2b2 2014 deidentification challenge. Because the Yellow Card data contained few names, we used predictive models to select narratives for training. Performance was evaluated on a separate set of annotated narratives from the Yellow Card scheme. In-depth review determined whether (parts of) person names missed by the de-identification method could enable re-identification of the individual, and whether de-identification reduced the clinical utility of narratives by collaterally masking relevant information. Results Recall on held-out Yellow Card data was 87% (155/179) at a precision of 55% (155/282) and a false-positive rate of 0.05% (127/ 263,451). Considering tokens longer than three characters separately, recall was 94% (102/108) and precision 58% (102/175). For 13 of the 5,042 narratives in Yellow Card test data (71 with person names), the method failed to flag at least one name token. According to in-depth review, the leaked information could enable direct identification for one narrative and indirect identification for two narratives. Clinically relevant information was removed in less than 1% of the 5,042 processed narratives; 97% of the narratives were completely untouched. Conclusions Automated redaction of names in free-text narratives of adverse event reports can achieve sufficient recall including shorter tokens like patient initials. In-depth review shows that the rare leaks that occur tend not to compromise patient confidentiality. Precision and false positive rates are acceptable with almost all clinically relevant information retained.
Recommendations for the Use of Social Media in Pharmacovigilance: Lessons from IMI WEB-RADR
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 to discuss their positive and negative experiences of medications, creating a source of publicly available information that has the potential to provide insights into medicinal product safety concerns. The WEB-RADR project has developed a collaborative English language workspace for visualising and analysing social media data for a number of medicinal products. Further, novel text and data mining methods for social media analysis have been developed and evaluated. From this original research, several recommendations are presented with supporting rationale and consideration of the limitations. Recommendations for further research that extend beyond the scope of the current project are also presented.
vigiGrade: A Tool to Identify Well-Documented Individual Case Reports and Highlight Systematic Data Quality Issues
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 and visualisation of the results. Objective The objective of this study was to propose a measure of completeness and identify predictors of well-documented reports, globally. Methods The Uppsala Monitoring Centre has developed the vigiGrade completeness score to measure the amount of clinically relevant information in structured format, without reflecting whether the information establishes causality between the drug and adverse event. The vigiGrade completeness score ( C ) starts at 1 for reports with information on time-to-onset, age, sex, indication, outcome, report type, dose, country, primary reporter and comments. For each missing dimension, a penalty is detracted which varies with clinical relevance. We classified reports with C  > 0.8 as well-documented and identified all such reports in the WHO global individual case safety report database, VigiBase, from 2007 to January 2012. We utilised odds ratios with statistical shrinkage to identify subgroups with unexpectedly high proportions of well-documented reports. Results Altogether, 430,000 (13 %) of the studied reports achieved C  > 0.8 in VigiBase. For VigiBase as a whole, the median completeness was 0.41 with an interquartile range of 0.26–0.63. Two out of three well-documented reports come from Europe, and two out of three from physicians. Among the countries with more than 1,000 reports in total, the highest rate of well-documented reports is 65 % in Italy. Tunisia, Spain, Portugal, Croatia and Denmark each have rates above 50 %, and another 20 countries have rates above 30 %. On the whole, 24 % of the reports from physicians are well-documented compared with only 4 % for consumers/non-health professionals. Notably, Denmark and Norway have more than 50 % well-documented reports from consumers/non-health professionals and higher rates than for physicians. The rate of well-documented reports for the E2B format is 11 % compared with 22 % for the older INTDIS (International Drug Information System) format. However, for E2B reports entered via the WHO programme’s e-reporting system VigiFlow, the rate is 29 %. Conclusion Overall, only one report in eight provides the desired level of information, but much higher proportions are observed for individual countries. Physicians and e-reporting tools also generate greater proportions of well-documented reports overall. Reports from consumers/non-health professionals in specific regions have excellent quality, which illustrates their potential for the future. vigiGrade has already provided valuable information by highlighting data quality issues both in Italy and the USA.