Validation study in four health-care databases: upper gastrointestinal bleeding misclassification affects precision but not magnitude of drug-related upper gastrointestinal bleeding risk

Valkhoff, Vera E.; Coloma, Preciosa M.; Masclee, Gwen; Gini, Rosa; Innocenti, Francesco; Lapi, Francesco; Molokhia, Mariam; Mosseveld, Mees; Nielsson, Malene Schou; Schuemie, Martijn J.; Thiessard, Frantz; Lei, Johan van der; Sturkenboom, Miriam; Trifirò, Gianluca

doi:10.1016/j.jclinepi.2014.02.020

Cited by 50 publications

(45 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Despite having 59,594,132 person-years of follow-up in the EU-ADR, it was estimated that it would be possible to detect relative risks for two outcomes of interest for commonly used medications: a relative risk of 2 for only 23 % of available medications for outcomes as frequent as myocardial infarction (an association that would not be detectable from spontaneous reports alone) and for only 1 % for events as rare as rhabdomyolysis [102]. Similar challenges have been observed for studies on non-steroidal anti-inflammatory drugs in pediatric populations in a multi-database project in Europe and studies of asthma mortality in users of long-acting β-agonists in chronic asthma in nine US databases [77,103].…”

Section: Resultsmentioning

confidence: 72%

See 1 more Smart Citation

Opportunities and Challenges in Using Epidemiologic Methods to Monitor Drug Safety in the Era of Large Automated Health Databases

Andrews

Margulis²,

Tennis

et al. 2014

Curr Epidemiol Rep

View full text Add to dashboard Cite

Healthcare databases have been used in the past four decades to identify, refine, and evaluate potential safety signals of marketed medical products. Critics have challenged this research because data are from secondary sources and because some published studies have lacked robust methods for exposure and outcome definition and failed to adequately control for biases. We review the history of healthcare databases used in pharmacovigilance for quantifying adverse outcomes associated with therapeutics, methods to improve the quality of this research, and best practices for pharmacoepidemiologic studies. Drug and vaccine safety studies increasingly use information from multiple healthcare databases, with analyses that aim to keep patient-level identifying data with local research custodians. Analytic methods, including high-dimensional exposure propensity scores, use large numbers of variables to reduce confounding and further anonymize patient data. However, due to gaps in and complexities of the available databases, the value of the research depends on experts with knowledge about the clinical context (e.g., how products are prescribed and taken, how outcomes are diagnosed and recorded, what risk factors must be considered), understanding the nuances of individual databases and the clinical practice patterns they represent, and utilizing study designs that minimize bias, particularly confounding by medication indication.

show abstract

Section: Resultsmentioning

confidence: 72%

“…The EU-ADR Alliance also relies on Jerboa software to create an ongoing platform that maintains the ability to study a wide scope of associations [41]. Methods developments within the EU-ADR include the harmonization of event definition and validation across databases [75][76][77].…”

Section: Methods Appropriate For Multiple Data Sourcesmentioning

confidence: 99%

Opportunities and Challenges in Using Epidemiologic Methods to Monitor Drug Safety in the Era of Large Automated Health Databases

Andrews

Margulis²,

Tennis

et al. 2014

Curr Epidemiol Rep

View full text Add to dashboard Cite

show abstract

“…Three were primary care data sources (PCDs), three were record linkage systems of different registries (RLDs), one was a hospital data source (HD) and one was a biobank (BD). In specific, the three primary care data sources were the Health Search IMS Health LPD database (HSD, Italy),[9, 15] the Integrated Primary Care Information database (IPCI, The Netherlands)[16] and The Health Improvement Network database (THIN, UK), in which the general practitioners (GPs) function as data keeper of all patient’s medical information. [17] The three record linkage data sources were the Aarhus University Hospital (AUH, Aarhus, Denmark),[18, 19] PHARMO (PHARMO, The Netherlands)[20] and the Regional Health Authority of Tuscany (ARS, Italy),[9, 15] which collect data from different sources (e.g.…”

Section: Methodsmentioning

confidence: 99%

“…In multi-data source studies, tailored choices may be necessary [6–8], and the diversity of local case-identification algorithms may increase along with the heterogeneity of the data sources involved [6, 9, 10]. A transparent process of documentation and evaluation of local case-finding algorithms becomes paramount for the correct interpretation of study results as well as for the discussion of possible inter-data source inconsistency of study findings [10–12].…”

Section: Introductionmentioning

confidence: 99%

“…It must be noted that data sources available to study European populations are much more heterogeneous than data sources from a single country, such as the United States [10]. Therefore, in order to address this issue, the EMIF-Platform designed a novel standard procedure for data derivation which leverages the experience gained from previous European multi-national, multi-data source studies [2, 3, 9, 13]. In this proof-of-concept study, the identification of type 2 diabetes mellitus (T2DM), a common chronic condition with important implications for future health[14], was used as a test case.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Identifying Cases of Type 2 Diabetes in Heterogeneous Data Sources: Strategy from the EMIF Project

et al. 2016

Self Cite

View full text Add to dashboard Cite

Due to the heterogeneity of existing European sources of observational healthcare data, data source-tailored choices are needed to execute multi-data source, multi-national epidemiological studies. This makes transparent documentation paramount. In this proof-of-concept study, a novel standard data derivation procedure was tested in a set of heterogeneous data sources. Identification of subjects with type 2 diabetes (T2DM) was the test case. We included three primary care data sources (PCDs), three record linkage of administrative and/or registry data sources (RLDs), one hospital and one biobank. Overall, data from 12 million subjects from six European countries were extracted. Based on a shared event definition, sixteeen standard algorithms (components) useful to identify T2DM cases were generated through a top-down/bottom-up iterative approach. Each component was based on one single data domain among diagnoses, drugs, diagnostic test utilization and laboratory results. Diagnoses-based components were subclassified considering the healthcare setting (primary, secondary, inpatient care). The Unified Medical Language System was used for semantic harmonization within data domains. Individual components were extracted and proportion of population identified was compared across data sources. Drug-based components performed similarly in RLDs and PCDs, unlike diagnoses-based components. Using components as building blocks, logical combinations with AND, OR, AND NOT were tested and local experts recommended their preferred data source-tailored combination. The population identified per data sources by resulting algorithms varied from 3.5% to 15.7%, however, age-specific results were fairly comparable. The impact of individual components was assessed: diagnoses-based components identified the majority of cases in PCDs (93–100%), while drug-based components were the main contributors in RLDs (81–100%). The proposed data derivation procedure allowed the generation of data source-tailored case-finding algorithms in a standardized fashion, facilitated transparent documentation of the process and benchmarking of data sources, and provided bases for interpretation of possible inter-data source inconsistency of findings in future studies.

show abstract

Risk and Outcome of Venous and Arterial Thrombosis in Patients With Cirrhosis: A Danish Nation‐wide Cohort Study

et al. 2021

View full text Add to dashboard Cite

BaCKgRoUND aND aIMS:Cirrhosis affects hemostasis, but its effects across the spectrum of thromboses remain poorly understood. We examined risks and outcomes of venous and arterial thrombosis.appRoaCH aND ReSUltS: We used nation-wide Danish health care registries to identify outpatients with cirrhosis and a sex-and age-matched comparison cohort without cirrhosis from the general population. Patients with cirrhosis and comparators were followed until they had a venous thromboembolism (VTE), acute myocardial infarction (AMI), or ischemic stroke (IS) or died. We computed absolute risks and HRs of thrombosis and compared outcomes after thrombosis. We included 5,854 patients with cirrhosis (median Model for End-Stage Liver Disease score, 9; interquartile range, 7-13), and their risk of any of the thrombotic events was 0.8% after 1 year and 6.3% after 10 years. They were more likely than the 23,870 matched comparators to have a VTE (adjusted hazard ratio [aHR], 2.0; 95% CI, 1.5-2.6) or IS (aHR, 1.7; 95% CI, 1.3-2.3), but not AMI (aHR, 0.7; 95% CI, 0.5-0.9). Among patients with cirrhosis, decompensation increased the risk of AMI, but not the other thromboses. Following thrombosis, patients with cirrhosis had higher 90-day mortality than comparators (after VTE: 17% vs. 7%; after AMI: 27% vs. 5%; after IS: 10% vs. 7%) and were less likely to receive antithrombotic treatment. CoNClUSIoNS:Patients with cirrhosis had an increased risk of VTE and IS, but not AMI. Among patients with cirrhosis, decompensation increased the risk of AMI, exclusively. Mortality after thrombosis was higher in patients with cirrhosis than in other patients. These findings are relevant for decisions about antithrombotic prophylaxis in patients with cirrhosis. (Hepatology 2021;74:2725-2734). P atients with cirrhosis are at increased risk of venous thromboembolism (VTE), comprising deep vein thrombosis (DVT) and pulmonary embolism (PE), (1)(2)(3)(4)(5) possibly attributable to an imbalance in pro-and anticoagulant factors. (5)(6)(7) Although existing studies provide estimates of the relative risk of venous thrombosis for patients with cirrhosis, the absolute risk, which is a key metric for informing the need for intervention, is open for study.We have found that patients with cirrhosis have more severe and extensive coronary artery disease than controls, (8) yet they do not have an increased risk of acute myocardial infarction (AMI). (9) In addition, a recent meta-analysis found no apparent association between cirrhosis and risk of ischemic stroke (IS), but all five meta-analyzed studies were from Asia,

show abstract

Validation study in four health-care databases: upper gastrointestinal bleeding misclassification affects precision but not magnitude of drug-related upper gastrointestinal bleeding risk

Cited by 50 publications

References 29 publications

Opportunities and Challenges in Using Epidemiologic Methods to Monitor Drug Safety in the Era of Large Automated Health Databases

Opportunities and Challenges in Using Epidemiologic Methods to Monitor Drug Safety in the Era of Large Automated Health Databases

Identifying Cases of Type 2 Diabetes in Heterogeneous Data Sources: Strategy from the EMIF Project

Risk and Outcome of Venous and Arterial Thrombosis in Patients With Cirrhosis: A Danish Nation‐wide Cohort Study

Contact Info

Product

Resources

About