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The use of antipsychotic medications (APMs) could be different among countries due to availability, approved indications, characteristics and clinical practice. However, there is limited literature providing comparisons of APMs use among countries. To examine trends in antipsychotic prescribing in Taiwan, Hong Kong, Japan, and the United States, we conducted a cross-national study from 2002 to 2014 b y using the distributed network approach with common data model. We included all patients who had at least a record of antipsychotic prescription in this study, and defined patients without previous exposure of antipsychotics for 6 months before the index date as new users for incidence estimation. We calculated the incidence, prevalence, and prescription rate of each medication by calendar year. Among older patients, sulpiride was the most incident [incidence rate (IR) 11.0–23.3) and prevalent [prevalence rate (PR) 11.9–14.3) APM in Taiwan, and most prevalent (PR 2.5–3.9) in Japan. Quetiapine and haloperidol were most common in the United States (IR 8.1–9.5; PR 18.0–18.4) and Hong Kong (PR 8.8–13.7; PR 10.6–12.7), respectively. The trend of quetiapine use was increasing in Taiwan, Hong Kong and the United States. As compared to older patients, the younger patients had more propensity to be prescribed second-generation APM for treatment in four countries. Trends in antipsychotic prescribing varied among countries. Quetiapine use was most prevalent in the United States and increasing in Taiwan and Hong Kong. The increasing use of quetiapine in the elderly patients might be due to its safety profile compared to other APMs.

Introduced in the 1950s, acetaminophen is one of the most widely used antipyretics and analgesics worldwide. In 1999, the International Agency for Research on Cancer (IARC) reviewed the epidemiologic studies of acetaminophen and the data were judged to be “inadequate” to conclude that it is carcinogenic. In 2019 the California Office of Environmental Health Hazard Assessment initiated a review process on the carcinogenic hazard potential of acetaminophen. To inform this review process, the authors performed a comprehensive literature search and identified 136 epidemiologic studies, which for most cancer types suggest no alteration in risk associated with acetaminophen use. For 3 cancer types, renal cell, liver, and some forms of lymphohematopoietic, some studies suggest an increased risk; however, multiple factors unique to acetaminophen need to be considered to determine if these results are real and clinically meaningful. The objective of this publication is to analyze the results of these epidemiologic studies using a framework that accounts for the inherent challenge of evaluating acetaminophen, including, broad population-wide use in multiple disease states, challenges with exposure measurement, protopathic bias, channeling bias, and recall bias. When evaluated using this framework, the data do not support a causal association between acetaminophen use and cancer.

Display Omitted Classifier to discern between drugs causing and not causing a condition.Evidence in classifier was highly predictive of reference sets.Method to integrate multiple sources of evidence about drugs and conditions.Two manually-created reference sets of drug-condition pairs trained an automated classifier. IntroductionDrug safety researchers seek to know the degree of certainty with which a particular drug is associated with an adverse drug reaction. There are different sources of information used in pharmacovigilance to identify, evaluate, and disseminate medical product safety evidence including spontaneous reports, published peer-reviewed literature, and product labels. Automated data processing and classification using these evidence sources can greatly reduce the manual curation currently required to develop reference sets of positive and negative controls (i.e. drugs that cause adverse drug events and those that do not) to be used in drug safety research. MethodsIn this paper we explore a method for automatically aggregating disparate sources of information together into a single repository, developing a predictive model to classify drug-adverse event relationships, and applying those predictions to a real world problem of identifying negative controls for statistical method calibration. ResultsOur results showed high predictive accuracy for the models combining all available evidence, with an area under the receiver-operator curve of 0.92 when tested on three manually generated lists of drugs and conditions that are known to either have or not have an association with an adverse drug event. ConclusionsResults from a pilot implementation of the method suggests that it is feasible to develop a scalable alternative to the time-and-resource-intensive, manual curation exercise previously applied to develop reference sets of positive and negative controls to be used in drug safety research.

Many observational studies explore the association between acetaminophen and cancer, but known limitations such as vulnerability to channeling, protopathic bias, and uncontrolled confounding hamper the interpretability of results. To help understand the potential magnitude of bias, we identify key design choices in these observational studies and specify 10 study design variants that represent different combinations of these design choices. We evaluate these variants by applying them to 37 negative controls - outcome presumed not to be caused by acetaminophen - as well as 4 cancer outcomes in the Clinical Practice Research Datalink (CPRD) database. The estimated odds and hazards ratios for the negative controls show substantial bias in the evaluated design variants, with far fewer of the 95% confidence intervals containing 1 than the nominal 95% expected for negative controls. The effect-size estimates for the cancer outcomes are comparable to those observed for the negative controls. A comparison of exposed and unexposed reveals many differences at baseline for which most studies do not correct. We observe that the design choices made in many of the published observational studies can lead to substantial bias. Thus, caution in the interpretation of published studies of acetaminophen and cancer is recommended.

Introduction Le projet ALCAPONE vise a evaluer et comparer les performances de l’approche cas-population au sein de la base du SNDS en vue de l’identification de methodes de reference pour la generation et la validation de signaux de pharmacovigilance. Avant son application au SNDS, la faisabilite du projet doit etre evaluee via l’Echantillon generaliste des beneficiaires (EGB). Methodes ALCAPONE se base sur des donnees retrospectives de la base du SNDS et de l’EGB ainsi que sur un set de reference compose de quatre evenements d’interet–insuffisance hepatique aigue (ALI), infarctus du myocarde (MI), insuffisance renale aigue (KI) et saignements des voies gastro-intestinales hautes (UGIB)–et de 165 medicaments temoins positifs et 235 negatifs. ALCAPONE compte trois etapes : (i) la selection, via une etude de faisabilite dans l’EGB, des temoins positifs et negatifs theoriquement detectables dans le SNDS ; (ii) la detection de ces medicaments temoins a travers trois methodes : series de cas autocontroles, schema cas-temoins et schema cas-population–declinees selon differents parametres (nombre de temoins, strategie d’ajustement, etc.) ; (iii) la validation et la comparaison des performances des differentes methodes et leurs variantes a partir du nombre de temoins positifs et negatifs effectivement detectes, de leurs sensibilite et specificite. Resultats Au total 40 ALI, 6334 MI, 758 KI et 1771 UGIB ont ete identifies dans l’EGB, rendant theoriquement possible la detection de 15 temoins positifs et 8 negatifs dans l’ensemble du set. Par extrapolation, le nombre de temoins positifs et negatifs theoriquement detectables dans le SNDS devrait etre au minimum de 72 et 86 respectivement. Discussion/Conclusion Le nombre de temoins detectables montre que la base du SNDS dispose de suffisamment de puissance pour mener a bien l’evaluation et la comparaison des differentes approches. Une fois selectionnees et calibrees, ces methodes pourront etre utilisees en vue de detecter des signaux de pharmacovigilance (application a un ensemble de medicaments suspects a travers differents evenements) ou de les valider (application a un medicament et un evenement d’interet).

Gene and protein name identification in text requires a dictionary approach to relate synonyms to the same gene or protein, and to link names to external databases. However, existing dictionaries are incomplete. We investigate two complementary methods for automatic generation of a comprehensive dictionary: combination of information from existing gene and protein databases and rule-based generation of spelling variations. Both methods have been reported in literature before, but have hitherto not been combined and evaluated systematically. We combined gene and protein names from several existing databases of four different organisms. The combined dictionaries showed a substantial increase in recall on three different test sets, as compared to any single database. Application of 23 spelling variation rules to the combined dictionaries further increased recall. However, many rules appeared to have no effect and some appear to have a detrimental effect on precision.

Objectifs Presenter la methodologie allant permettre l’evaluation, le calibrage et la comparaison des performances de l’approche cas–population dans la detection de signaux de pharmacovigilance au sein du Systeme national d’information interregimes de l’assurance maladie (Sniiram), dans le cadre du projet ALCAPONE. Evaluer la faisabilite du projet a partir de resultats preliminaires issus de l’echantillon generaliste de beneficiaires (EGB). Methodes La methodologie du projet ALCAPONE s’inspire de celle developpee par les consortiums internationaux Observational medical outcome partnership (« OMOP » ) et Observational health data sciences and informatics (« OHDSI » ). ALCAPONE se base sur des donnees retrospectives obtenues via le Sniiram et l’EGB ainsi que sur le set de reference d’OMOP. Ce set se compose de quatre evenements d’interet–insuffisance hepatique aigue (ALI), infarctus du myocarde (MI), insuffisance renale aigue (KI) et saignements des voies gastro-intestinales hautes (UGIB) – et de 165 medicaments temoins positifs et 235 negatifs. ALCAPONE compte trois etapes : – la selection, via une etude de faisabilite dans l’EGB, des temoins positifs et negatifs effectivement detectables dans le Sniiram (i.e. avec un risque relatif minimum detectable ≤ 1,25) ; – la detection des temoins retenus a travers trois designs : « self-controlled case series » (SCCS), approche cas–temoins (CC) et approche cas–population (CP) – plusieurs parametres etant testes pour chacun d’entre eux (nombre de temoins, strategie d’ajustement, etc . ) ; – comparaison des performances des differents designs et leurs variantes d’apres leurs sensibilite et specificite. Les cas ont ete identifies d’apres leur diagnostic principal entre le 01/01/2009 et le 31/12/2014. Deux definitions ont ete utilisees pour la selection des evenements d’interet : une « specifique » et une « sensible ». Pour chaque evenement d’interet, la precision des mesures d’association generees par chaque design et ses variantes sera calculee et utilisee pour calibrer les methodes. Resultats La definition « sensible » a permis d’identifier dans l’EGB 40 ALI, 6334 MI, 758 KI et 1771 UGIB contre 33 ALI, 3202 MI, 94 KI et 1390 UGIB pour la « specifique ». Sur l’ensemble du set, en se basant sur la definition « sensible » des quatre pathologies, 15 temoins positifs et 8 negatifs sont effectivement detectables dans l’EGB contre 9 et 3 respectivement pour la definition « specifique ». Par extrapolation, le nombre de temoins positifs et negatifs detectables dans le Sniiram devrait etre respectivement de 72 et 86 pour la definition « sensible » contre 67 et 71 pour la definition « specifique ». A titre de comparaison, 71 temoins positifs et 67 negatifs ont ete classifies comme effectivement detectables dans les travaux initiaux d’OMOP. Conclusions Le nombre de temoins effectivement detectable montre que le Sniiram dispose de suffisamment de puissance pour mener a bien l’evaluation, le calibrage et la comparaison de l’approche cas–population et des autres approches. Ces temoins serviront a l’identification des designs et parametres optimaux pour l’etude de chaque evenement d’interet au sein du Sniiram. Ces designs de reference seront par la suite utilises pour la generation et la validation de signaux de pharmacovigilance.

Aim: Concomitant use of non-steroidal anti-inflammatory drugs (NSAIDs) and low-dose aspirin (LDA) increases the risk of upper gastrointestinal bleeding (UGIB). Although clinical guidelines suggest to avoid certain drug combinations, little is known about the magnitude of interaction between different NSAIDs and specific drug groups. This is partly due to the need of a large sample for studying drug interactions. Understanding drug synergism is important to develop strategies to minimize the risk of UGIB. Design: A self-controlled case series analysis was performed using data from seven population-based healthcare databases located in three countries (Denmark, Italy, and the Netherlands). UGIB cases were identified based on disease classification codes. Drug exposure was classified into mutually exclusive groups. Interaction of the three main groups (non-selective (ns)NSAIDs, coxibs and LDA) with other drugs was examined. Incidence rate ratios (IRRs) of UGIB during exposure (and corresponding 95% CI) were obtained by Poisson regression modeling. Interaction was assessed on additive (with relative excess risk due to interaction, RERI) and multiplicative scale. Results: In total 114,835 UGIB cases, with corresponding follow-up of 930,888 personyears, were analyzed. Monotherapy with nsNSAIDs was associated with a higher IRR than monotherapy with coxibs or LDA (IRR 4.3; 2.9 and 3.1 respectively). The IRR was highest for concomitant use of nsNSAIDs and steroids (IRR 12.8; 95% CI: 11.2-14.7), which also demonstrated the highest additive interaction (RERI 5.5)(Figure 1). The IRR for nsNSAIDs and aldosterone antagonists was 11.0 (95%CI 8.6 -14.0) and RERI 4.5. Selective serotonin re-uptake inhibitors (SSRIs) and anticoagulants combined with either nsNSAIDs, coxibs or LDA increased the risk of UGIB significantly and also to a greater extent than expected based on the sum of the individual drugs (RERI 1.6;1.9 and 0.5 for SSRIs and 2.4;0.1 and 1.9 for anticoagulants, respectively). Only for the combination of LDA and antiplatelets was apart from additive, also multiplicative interaction observed (IRR 5.4; 95%CI: 4.7-6.4; RERI 1.7). Increasing age was associated with a higher IRR. Stratifying by age showed that for all drugs older persons (.60 years) had a higher IRR compared to younger persons ( ,60 years), except for combinations of nsNSAIDs+anticoagulants and coxibs+steroids. Conclusion: Concomitant use of SSRIs with nsNSAIDs, coxibs or LDA significantly increases the risk of UGIB up to seven-fold. Concomitant use of steroids, anticoagulants or antiplatelets with nsNSAIDs or LDA, but not with coxibs, showed an increased risk of UGIB, up to thirteen-fold. These increased risks were greater than the sum of the risks of individual drugs. This knowledge is of clinical relevance and can help clinicians in tailoring therapy to minimize UGI adverse events.