Incidence Rates of Autoimmune Diseases in European Healthcare Databases: A Contribution of the ADVANCE Project.

INTRODUCTION: The public-private ADVANCE collaboration developed and tested a system to generate evidence on vaccine benefits and risks using European electronic healthcare databases. In the safety of vaccines, background incidence rates are key to allow proper monitoring and assessment. The goals of this study were to compute age-, sex-, and calendar-year stratified incidence rates of nine autoimmune diseases in seven European healthcare databases from four countries and to assess validity by comparing with published data. METHODS: Event rates were calculated for the following outcomes: acute disseminated encephalomyelitis, Bell's palsy, Guillain-Barré syndrome, immune thrombocytopenia purpura, Kawasaki disease, optic neuritis, narcolepsy, systemic lupus erythematosus, and transverse myelitis. Cases were identified by diagnosis codes. Participating organizations/databases originated from Denmark, Italy, Spain, and the UK. The source population comprised all persons registered, with at least 1 year of data prior to the study start, or follow-up from birth. Stratified incidence rates were computed per database over the period 2003 to 2014. RESULTS: Between 2003 and 2014, 148,947 incident cases of nine autoimmune diseases were identified. Crude incidence rates were highest for Bell's palsy [23.8/100,000 person-years (PYs), 95% confidence interval (CI) 23.6-24.1] and lowest for Kawasaki disease (0.7/100,000 PYs, 95% CI 0.6-0.7). Specific patterns were observed by sex, age, calendar time, and data sources. Rates were comparable with published estimates. CONCLUSION: A range of autoimmune events could be identified in the ADVANCE system. Estimation of rates indicated consistency across selected European healthcare databases, as well as consistency with US published data.

ADVANCE system testing: Estimating the incidence of adverse events following pertussis vaccination in healthcare databases with incomplete exposure data.

The Accelerated Development of VAccine beNefit-risk Collaboration in Europe (ADVANCE) is a public-private collaboration aiming to develop and test a system for rapid vaccine benefit-risk monitoring using existing European healthcare databases. Incidence rate (IR) estimates of vaccination-associated adverse events that are needed to model vaccination risks can be calculated from existing healthcare databases when vaccination (exposure) data are available. We assessed different methods to derive IRs in risk periods following vaccination when exposure data are missing in one database, using estimated IRs and IRRs from other databases for febrile seizures, fever and persistent crying. IRs were estimated for children aged 0-5 years in outcome-specific risk and non-risk periods following the first dose of acellular pertussis (aP) vaccination in four primary care databases and one hospital database. We compared derived and observed IRs in each database using three methods: 1) multiplication of non-risk period IR for database i by IR ratio (IRR) obtained from meta-analysis of IRRs estimated using the self-controlled case-series method, from databases other than i; 2) same method as 1, but multiplying with background IR; and 3) meta-analyses of observed IRs from databases other than i. IRs for febrile seizures were lower in primary care databases than the hospital database. The derived IR for febrile seizures using data from primary care databases was lower than that observed in the hospital database, and using data from the hospital database gave a higher derived IR than that observed in the primary care database. For fever and persistent crying the opposite was observed. We demonstrated that missing IRs for a post-vaccination period can be derived but that the type of database and the method of event data capture can have an impact on potential bias. We recommend IRs are derived using data from similar database types (hospital or primary care) with caution as even this can give heterogeneous results.

Incidence, risk factors and re-exacerbation rate of severe asthma exacerbations in a multinational, multidatabase pediatric cohort study.

BACKGROUND: There are sparse real-world data on severe asthma exacerbations (SAE) in children. This multinational cohort study assessed the incidence of and risk factors for SAE and the incidence of asthma-related rehospitalization in children with asthma. METHODS: Asthma patients 5-17 years old with ≥1 year of follow-up were identified in six European electronic databases from the Netherlands, Italy, the UK, Denmark and Spain in 2008-2013. Asthma was defined as ≥1 asthma-specific disease code within 3 months of prescriptions/dispensing of asthma medication. Severe asthma was defined as high-dosed inhaled corticosteroids plus a second controller. SAE was defined by systemic corticosteroids, emergency department visit and/or hospitalization all for reason of asthma. Risk factors for SAE were estimated by Poisson regression analyses. RESULTS: The cohort consisted of 212 060 paediatric asthma patients contributing to 678 625 patient-years (PY). SAE rates ranged between 17 and 198/1000 PY and were higher in severe asthma and highest in severe asthma patients with a history of exacerbations. Prior SAE (incidence rate ratio 3-45) and younger age increased the SAE risk in all countries, whereas obesity, atopy and GERD were a risk factor in some but not all countries. Rehospitalization rates were up to 79% within 1 year. CONCLUSIONS: In a real-world setting, SAE rates were highest in children with severe asthma with a history of exacerbations. Many severe asthma patients were rehospitalized within 1 year. Asthma management focusing on prevention of SAE is important to reduce the burden of asthma.

Multinational cohort study of mortality in patients with asthma and severe asthma.

BACKGROUND: Data on the risk of death following an asthma exacerbation are scarce. With this multinational cohort study, we assessed all-cause mortality rates, mortality rates following an exacerbation, and patient characteristics associated with all-cause mortality in asthma. METHODS: Asthma patients aged ≥18 years and with ≥1 year of follow-up were identified in 5 European electronic databases from the Netherlands, Italy, UK, Denmark and Spain during the study period January 1, 2008-December 31, 2013. Patients with asthma-COPD overlap were excluded. Severe asthma was defined as use of high dose ICS + use of a second controller. Severe asthma exacerbations were defined as emergency department visits, hospitalizations or systemic corticosteroid use, all for reason of asthma. RESULTS: The cohort consisted of 586,436 asthma patients of which 42,611 patients (7.3%) had severe asthma. The age and sex standardized all-cause mortality rates ranged between databases from 5.2 to 9.5/1000 person-years (PY) in asthma, and between 11.3 and 14.8/1000 PY in severe asthma. The all-cause mortality rate in the first week following a severe asthma exacerbation ranged between 14.1 and 59.9/1000 PY. Mortality rates remained high in the first month following a severe asthma exacerbation and decreased thereafter. Higher age, male gender, comorbidity, smoking, and previous severe asthma exacerbations were associated with mortality. CONCLUSION: All-cause mortality following a severe exacerbation is high, especially in the first month following the event. Smoking cessation, comorbidity-management and asthma-treatment focusing on the prevention of exacerbations might reduce associated mortality.

ADVANCE database characterisation and fit for purpose assessment for multi-country studies on the coverage, benefits and risks of pertussis vaccinations.

INTRODUCTION: The public-private ADVANCE consortium (Accelerated development of vaccine benefit-risk collaboration in Europe) aimed to assess if electronic healthcare databases can provide fit-for purpose data for collaborative, distributed studies and monitoring of vaccine coverage, benefits and risks of vaccines. OBJECTIVE: To evaluate if European healthcare databases can be used to estimate vaccine coverage, benefit and/or risk using pertussis-containing vaccines as an example. METHODS: Characterisation was conducted using open-source Java-based (Jerboa) software and R scripts. We obtained: (i) The general characteristics of the database and data source (meta-data) and (ii) a detailed description of the database population (size, representatively of age/sex of national population, rounding of birth dates, delay between birth and database entry), vaccinations (number of vaccine doses, recording of doses, pattern of doses by age and coverage) and events of interest (diagnosis codes, incidence rates). A total of nine databases (primary care, regional/national record linkage) provided data on events (pertussis, pneumonia, death, fever, convulsions, injection site reactions, hypotonic hypo-responsive episode, persistent crying) and vaccines (acellular pertussis and whole cell pertussis) related to the pertussis proof of concept studies. RESULTS: The databases contained data for a total population of 44 million individuals. Seven databases had recorded doses of vaccines. The pertussis coverage estimates were similar to those reported by the World Health Organisation (WHO). Incidence rates of events were comparable in magnitude and age-distribution between databases with the same characteristics. Several conditions (persistent crying and somnolence) were not captured by the databases for which outcomes were restricted to hospital discharge diagnoses. CONCLUSION: The database characterisation programs and workflows allowed for an efficient, transparent and standardised description and verification of electronic healthcare databases which may participate in pertussis vaccine coverage, benefit and risk studies. This approach is ready to be used for other vaccines/events to create readiness for participation in other vaccine related studies.

ADVANCE system testing: Can safety studies be conducted using electronic healthcare data? An example using pertussis vaccination.

INTRODUCTION: The Accelerated Development of Vaccine benefit-risk Collaboration in Europe (ADVANCE) public-private collaboration, aimed to develop and test a system for rapid benefit-risk monitoring of vaccines using healthcare databases in Europe. The objective of this proof-of-concept (POC) study was to test the feasibility of the ADVANCE system to generate incidence rates (IRs) per 1000 person-years and incidence rate ratios (IRRs) for risks associated with whole cell- (wP) and acellular- (aP) pertussis vaccines, occurring in event-specific risk windows in children prior to their pre-school-entry booster. METHODS: The study population comprised almost 5.1 million children aged 1 month to <6 years vaccinated with wP or aP vaccines during the study period from 1 January 1990 to 31 December 2015. Data from two Danish hospital (H) databases (AUH and SSI) and five primary care (PC) databases from, UK (THIN and RCGP RSC), Spain (SIDIAP and BIFAP) and Italy (Pedianet) were analysed. Database-specific IRRs between risk vs. non-risk periods were estimated in a self-controlled case series study and pooled using random-effects meta-analyses. RESULTS: The overall IRs were: fever, 58.2 (95% CI: 58.1; 58.3), 96.9 (96.7; 97.1) for PC DBs and 8.56 (8.5; 8.6) for H DBs; convulsions, 7.6 (95% CI: 7.6; 7.7), 3.55 (3.5; 3.6) for PC and 12.87 (12.8; 13) for H; persistent crying, 3.9 (95% CI: 3.8; 3.9) for PC, injection-site reactions, 2.2 (95% CI 2.1; 2.2) for PC, hypotonic hypo-responsive episode (HHE), 0.4 (95% CI: 0.4; 0.4), 0.6 (0.6; 0.6) for PC and 0.2 (0.2; 0.3) for H; and somnolence: 0.3 (95% CI: 0.3; 0.3) for PC. The pooled IRRs for persistent crying, fever, and ISR, adjusted for age and healthy vaccinee period were higher after wP vs. aP vaccination, and lower for convulsions, for all doses. The IRR for HHE was slightly lower for wP than aP, while wP was associated with somnolence only for dose 1 and dose 3 compared with aP. CONCLUSIONS: The estimated IRs and IRRs were comparable with published data, therefore demonstrating that the ADVANCE system was able to combine several European healthcare databases to assess vaccine safety data for wP and aP vaccination.

ADVANCE system testing: Benefit-risk analysis of a marketed vaccine using multi-criteria decision analysis and individual-level state transition modelling.

BACKGROUND: The Accelerated Development of VAccine beNefit-risk Collaboration in Europe (ADVANCE) is a public-private collaboration aiming to develop and test a system for rapid benefit-risk (B/R) monitoring of vaccines using electronic health record (eHR) databases in Europe. Proof-of-concept studies were designed to assess the proposed processes and system for generating the required evidence to perform B/R assessment and near-real time monitoring of vaccines. We aimed to test B/R methodologies for vaccines, using the comparison of the B/R profiles of whole-cell (wP) and acellular pertussis (aP) vaccine formulations in children as an example. METHODS: We used multi-criteria decision analysis (MCDA) to structure the B/R assessment combined with individual-level state transition modelling to build the B/R effects table. In the state transition model, we simulated the number of events in two hypothetical cohorts of 1 million children followed from first pertussis dose till pre-school-entry booster (or six years of age, whichever occurred first), with one cohort receiving wP, and the other aP. The benefits were reductions in pertussis incidence and complications. The risks were increased incidences of febrile convulsions, fever, hypotonic-hyporesponsive episodes, injection-site reactions and persistent crying. Most model parameters were informed by estimates (coverage, background incidences, relative risks) from eHR databases from Denmark (SSI), Spain (BIFAP and SIDIAP), Italy (Pedianet) and the UK (RCGP-RSC and THIN). Preferences were elicited from clinical and epidemiological experts. RESULTS: Using state transition modelling to build the B/R effects table facilitated the comparison of different vaccine effects (e.g. immediate vaccine risks vs long-term vaccine benefits). Estimates from eHR databases could be used to inform the simulation model. The model results could be easily combined with preference weights to obtain B/R scores. CONCLUSION: Existing B/R methodology, modelling and estimates from eHR databases can be successfully used for B/R assessment of vaccines.

Advance system testing: Vaccine benefit studies using multi-country electronic health data - The example of pertussis vaccination.

The Accelerated Development of VAccine benefit-risk Collaboration in Europe (ADVANCE), a public-private consortium, implemented and tested a distributed network system for the generation of evidence on the benefits-risks of marketed vaccines in Europe. We tested the system by estimating the incidence rate (IR) of pertussis and pertussis-related complications in children vaccinated with acellular (aP) and whole-cell (wP) pertussis vaccine. Data from seven electronic databases from four countries (Denmark: AUH and SSI, Spain: SIDIAP and BIFAP, UK: THIN and RCGP RSC and Italy: Pedianet) were included in a retrospective cohort analysis. Exposure was defined as any pertussis vaccination (aP or wP). The follow-up time started 14 days after the first dose. Children who had received any pertussis vaccine from January 1990 to December 2015 were included (those who switched type, or had unknown type were excluded). The outcomes of interest were confirmed or suspected pertussis and pertussis-related pneumonia and generalised convulsions within one month of pertussis diagnosis and death within three months of pertussis diagnosis. The cohort comprised 2,886,367 children ≤5 years of age. Data on wP and aP vaccination were available in three and seven databases, respectively. The IRs (per 100,000 person-years) for pertussis varied largely and ranged between 0.15 (95% CI: 0.12; 0.19) and 1.15 (95% CI: 1.07; 1.23), and the trends over time was consistent with those observed from national surveillance databases for confirmed pertussis. The pertussis IRs decreased as the number of wP and aP vaccine doses increased. Pertussis-related complications were rare (89 pneumonia, 7 generalised convulsions and no deaths) and their relative risk (vs. non-pertussis) could not be reliably estimated. The study demonstrated the feasibility of the ADVANCE system to estimate the change in pertussis IRs following pertussis vaccination. Larger sample sizes would provide additional power to compare the risk for complications between children with and without pertussis. The feasibility of vaccine-type specific effectiveness studies may be considered in the future.

Quantifying outcome misclassification in multi-database studies: The case study of pertussis in the ADVANCE project.

BACKGROUND: The Accelerated Development of VAccine beNefit-risk Collaboration in Europe (ADVANCE) is a public-private collaboration aiming to develop and test a system for rapid benefit-risk (B/R) monitoring of vaccines using European healthcare databases. Event misclassification can result in biased estimates. Using different algorithms for identifying cases of Bordetella pertussis (BorPer) infection as a test case, we aimed to describe a strategy to quantify event misclassification, when manual chart review is not feasible. METHODS: Four participating databases retrieved data from primary care (PC) setting: BIFAP: (Spain), THIN and RCGP RSC (UK) and PEDIANET (Italy); SIDIAP (Spain) retrieved data from both PC and hospital settings. BorPer algorithms were defined by healthcare setting, data domain (diagnoses, drugs, or laboratory tests) and concept sets (specific or unspecified pertussis). Algorithm- and database-specific BorPer incidence rates (IRs) were estimated in children aged 0-14 years enrolled in 2012 and 2014 and followed up until the end of each calendar year and compared with IRs of confirmed pertussis from the ECDC surveillance system (TESSy). Novel formulas were used to approximate validity indices, based on a small set of assumptions. They were applied to approximately estimate positive predictive value (PPV) and sensitivity in SIDIAP. RESULTS: The number of cases and the estimated BorPer IRs per 100,000 person-years in PC, using data representing 3,173,268 person-years, were 0 (IR = 0.0), 21 (IR = 4.3), 21 (IR = 5.1), 79 (IR = 5.7), and 2 (IR = 2.3) in BIFAP, SIDIAP, THIN, RCGP RSC and PEDIANET respectively. The IRs for combined specific/unspecified pertussis were higher than TESSy, suggesting that some false positives had been included. In SIDIAP the estimated IR was 45.0 when discharge diagnoses were included. The sensitivity and PPV of combined PC specific and unspecific diagnoses for BorPer cases in SIDIAP were approximately 85% and 72%, respectively. CONCLUSION: Retrieving BorPer cases using only specific concepts has low sensitivity in PC databases, while including cases retrieved by unspecified concepts introduces false positives, which were approximately estimated to be 28% in one database. The share of cases that cannot be retrieved from a PC database because they are only seen in hospital was approximately estimated to be 15% in one database. This study demonstrated that quantifying the impact of different event-finding algorithms across databases and benchmarking with disease surveillance data can provide approximate estimates of algorithm validity.

Antibiotic-Induced Liver Injury in Paediatric Outpatients: A Case-Control Study in Primary Care Databases.

INTRODUCTION: Antibiotics are the most commonly prescribed drug class in children. Real-world data mining on the paediatric population showed potential associations between antibiotic use and acute liver injury. OBJECTIVE: We assessed risk estimates of liver injury associated with antibiotic use in children and adolescent outpatients. METHODS: A large, multi-database, population-based, case-control study was performed in people <18 years of age from two European countries (Italy and The Netherlands) during the period 2000-2008. All potential cases of liver injury were automatically extracted from three databases and then manually validated based on Council for International Organizations of Medical Sciences (CIOMS) criteria and by exclusion of all competing causes for liver injury. Up to 100 control participants were sampled for each case and were matched on index date of the event, age, sex and database. Based on prescription data, antibiotic exposure was categorized as current, recent or past use by calculating the time period between the end of prescription and the index date. Multivariate conditional logistic regression analyses were applied to calculate odds ratios (ORs) as a measure of the association (with 95% confidence interval [CI]). RESULTS: We identified 938 cases of liver injury and matched to 93,665 controls. Current use of overall antibiotics is associated with a threefold increased risk of liver injury compared with past use (adjusted OR [ORadj] 3.22, 95% CI 2.57-4.03). With regard to individual antibiotics, the risk is significantly increased for current use of each antibiotic (p < 0.005), except for azithromycin. Risk estimates vary from the lowest ORadj of 1.86 (95% CI 1.08-3.21) for amoxicillin to the highest ORadj of 24.16 (95% CI 11.78-49.54) for cotrimoxazole (i.e. sulphamethoxazole/trimethoprim) and 26.70 (95% CI 12.09-58.96) for ceftriaxone. Sensitivity analyses confirm the associations for ceftriaxone, cotrimoxazole, and clarithromycin. CONCLUSION: Antibiotic-induced liver injury in children is heterogeneous across the use of individual antibiotics. When prescribing ceftriaxone, cotrimoxazole and clarithromycin in children, paediatricians should definitely be aware of their potential risk of liver injury, even if for short periods.

Using Prescription Patterns in Primary Care to Derive New Quality Indicators for Childhood Community Antibiotic Prescribing.

BACKGROUND: To describe patterns of antibiotic outpatient use in 3 European countries, including 2 new pediatric-specific quality indicators (QIs). METHODS: A cohort study was conducted, 2001-2010, using electronic primary care records of 2,196,312 children up to 14 (Pedianet, Italy) or 18 years (The Health Improvement Network, United Kingdom; Integrated Primary Care Information database, The Netherlands) contributing 12,079,620 person-years. Prevalence rates of antibiotic prescribing per year were calculated and antibiotics accounting (drug utilization) for 90% of all antibiotic prescriptions were identified (drug utilization 90% method). The ratio between users of broad to narrow-spectrum penicillins, cephalosporins and macrolides (B/N ratio) and 2 pediatric-specific QIs: the proportion of amoxicillin users (amoxicillin index) and the ratio between users of amoxicillin to broad-spectrum penicillins, cephalosporins and macrolides (A/B ratio) were determined. RESULTS: The overall annual prevalence of antibiotic prescriptions was 18.0% in the Netherlands, 36.2% in the United Kingdom and 52.0% in Italy. Use was maximal in the first years of life. The number of antibiotics accounting for the drug utilization 90% was comparable. The B/N ratio varied widely from 0.3 to 74.7. The amoxicillin index was highest in the Netherlands and the United Kingdom (50-60%), lowest in Italy (30%) and worsened over time in the United Kingdom and Italy. The A/B ratio in 2010 was 0.3 in Italy, 1.7 in the Netherlands and 5.4 in the United Kingdom. CONCLUSIONS: The patterns of antibiotic prescribing varied highly with age and country. The pediatric-specific QIs combined with the total prevalence rate of use provide a clear picture of the trends of community childhood antibiotic prescribing, allowing monitoring of the impact of policy interventions.

Useful Interplay Between Spontaneous ADR Reports and Electronic Healthcare Records in Signal Detection.

BACKGROUND AND OBJECTIVE: Spontaneous reporting systems (SRSs) remain the cornerstone of post-marketing drug safety surveillance despite their well-known limitations. Judicious use of other available data sources is essential to enable better detection, strengthening and validation of signals. In this study, we investigated the potential of electronic healthcare records (EHRs) to be used alongside an SRS as an independent system, with the aim of improving signal detection. METHODS: A signal detection strategy, focused on a limited set of adverse events deemed important in pharmacovigilance, was performed retrospectively in two data sources-(1) the Exploring and Understanding Adverse Drug Reactions (EU-ADR) database network and (2) the EudraVigilance database-using data between 2000 and 2010. Five events were considered for analysis: (1) acute myocardial infarction (AMI); (2) bullous eruption; (3) hip fracture; (4) acute pancreatitis; and (5) upper gastrointestinal bleeding (UGIB). Potential signals identified in each system were verified using the current published literature. The complementarity of the two systems to detect signals was expressed as the percentage of the unilaterally identified signals out of the total number of confirmed signals. As a proxy for the associated costs, the number of signals that needed to be reviewed to detect one true signal (number needed to detect [NND]) was calculated. The relationship between the background frequency of the events and the capability of each system to detect signals was also investigated. RESULTS: The contribution of each system to signal detection appeared to be correlated with the background incidence of the events, being directly proportional to the incidence in EU-ADR and inversely proportional in EudraVigilance. EudraVigilance was particularly valuable in identifying bullous eruption and acute pancreatitis (71 and 42 % of signals were correctly identified from the total pool of known associations, respectively), while EU-ADR was most useful in identifying hip fractures (60 %). Both systems contributed reasonably well to identification of signals related to UGIB (45 % in EudraVigilance, 40 % in EU-ADR) but only fairly for signals related to AMI (25 % in EU-ADR, 20 % in EudraVigilance). The costs associated with detection of signals were variable across events; however, it was often more costly to detect safety signals in EU-ADR than in EudraVigilance (median NNDs: 7 versus 5). CONCLUSION: An EHR-based system may have additional value for signal detection, alongside already established systems, especially in the presence of adverse events with a high background incidence. While the SRS appeared to be more cost effective overall, for some events the costs associated with signal detection in the EHR might be justifiable.

The role of electronic healthcare record databases in paediatric drug safety surveillance: a retrospective cohort study.

AIM: Electronic healthcare record (EHR)-based surveillance systems are increasingly being developed to support early detection of safety signals. It is unknown what the power of such a system is for surveillance among children and adolescents. In this paper we provide estimates of the number and classes of drugs, and incidence rates (IRs) of events, that can be monitored in children and adolescents (0-18 years). METHODS: Data were obtained from seven population-based EHR databases in Denmark, Italy, and the Netherlands during the period 1996-2010. We estimated the number of drugs for which specific adverse events can be monitored as a function of actual drug use, minimally detectable relative risk (RR) and IRs for 10 events. RESULTS: The population comprised 4 838 146 individuals (25 575 132 person years (PYs)), who were prescribed 2170 drugs (1 610 631 PYs drug-exposure). Half of the total drug-exposure in PYs was covered by only 18 drugs (0.8%). For a relatively frequent event like upper gastrointestinal bleeding there were 39 drugs for which an association with a RR ≥4, if present, could be investigated. The corresponding number of drugs was eight for a rare event like anaphylactic shock. CONCLUSION: Drug use in children is rare and shows little variation. The number of drugs with enough exposure to detect rare adverse events in children and adolescents within an EHR-based surveillance system such as EU-ADR is limited. Use of additional sources of paediatric drug exposure information and global collaboration are imperative in order to optimize EHR data for paediatric safety surveillance.

Using real-world healthcare data for pharmacovigilance signal detection - the experience of the EU-ADR project.

A prospective pharmacovigilance signal detection study, comparing the real-world healthcare data (EU-ADR) and two spontaneous reporting system (SRS) databases, US FDA's Adverse Event Reporting System and WHO's Vigibase is reported. The study compared drug safety signals found in the EU-ADR and SRS databases. The potential for signal detection in the EU-ADR system was found to be dependent on frequency of the event and utilization of drugs in the general population. The EU-ADR system may have a greater potential for detecting signals for events occurring at higher frequency in general population and those that are commonly not considered as potentially a drug-induced event. Factors influencing various differences between the datasets are discussed along with potential limitations and applications to pharmacovigilance practice.

Risk of upper gastrointestinal bleeding from different drug combinations.

BACKGROUND & AIMS: Concomitant use of nonsteroidal anti-inflammatory drugs (NSAIDs) and low-dose aspirin increases the risk of upper gastrointestinal bleeding (UGIB). Guidelines suggest avoiding certain drug combinations, yet little is known about the magnitude of their interactions. We estimated the risk of UGIB during concomitant use of nonselective (ns)NSAIDs, cyclooxygenase -2 selective inhibitors (COX-2 inhibitors), and low-dose aspirin with other drugs. METHODS: We performed a case series analysis of data from 114,835 patients with UGIB (930,888 person-years of follow-up) identified from 7 population-based health care databases (approximately 20 million subjects). Each patient served as his or her own control. Drug exposure was determined based on prescriptions of nsNSAIDs, COX-2 inhibitors, or low-dose aspirin, alone and in combination with other drugs that affect the risk of UGIB. We measured relative risk (incidence rate ratio [IRR] during drug exposure vs nonexposure) and excess risk due to concomitant drug exposure (relative excess risk due to interaction [RERI]). RESULTS: Monotherapy with nsNSAIDs increased the risk of diagnosis of UGIB (IRR, 4.3) to a greater extent than monotherapy with COX-2 inhibitors (IRR, 2.9) or low-dose aspirin (IRR, 3.1). Combination therapy generally increased the risk of UGIB; concomitant nsNSAID and corticosteroid therapies increased the IRR to the greatest extent (12.8) and also produced the greatest excess risk (RERI, 5.5). Concomitant use of nsNSAIDs and aldosterone antagonists produced an IRR for UGIB of 11.0 (RERI, 4.5). Excess risk from concomitant use of nsNSAIDs with selective serotonin reuptake inhibitors (SSRIs) was 1.6, whereas that from use of COX-2 inhibitors with SSRIs was 1.9 and that for use of low-dose aspirin with SSRIs was 0.5. Excess risk of concomitant use of nsNSAIDs with anticoagulants was 2.4, of COX-2 inhibitors with anticoagulants was 0.1, and of low-dose aspirin with anticoagulants was 1.9. CONCLUSIONS: Based on a case series analysis, concomitant use of nsNSAIDs, COX-2 inhibitors, or low-dose aspirin with SSRIs significantly increases the risk of UGIB. Concomitant use of nsNSAIDs or low-dose aspirin, but not COX-2 inhibitors, with corticosteroids, aldosterone antagonists, or anticoagulants produces significant excess risk of UGIB.

Signal detection of potentially drug-induced acute liver injury in children using a multi-country healthcare database network.

BACKGROUND: Data mining in spontaneous reporting databases has shown that drug-induced liver injury is infrequently reported in children. OBJECTIVES: Our objectives were to (i) identify drugs potentially associated with acute liver injury (ALI) in children and adolescents using electronic healthcare record (EHR) data; and (ii) to evaluate the significance and novelty of these associations. METHODS: We identified potential cases of ALI during exposure to any prescribed/dispensed drug for individuals <18 years old from the EU-ADR network, which includes seven databases from three countries, covering the years 1996-2010. Several new methods for signal detection were applied to identify all statistically significant associations between drugs and ALI. A drug was considered statistically significantly associated with ALI, using all other time as a reference category, if the 95% CI lower band of the relative risk was >1 and in the presence of at least three exposed cases of ALI. Potentially new signals were distinguished from already known associations concerning ALI (whether in adults and/or in the paediatric population) through manual review of published literature and drug product labels. RESULTS: The study population comprised 4,838,146 individuals aged <18 years, who contributed an overall 25,575,132 person-years of follow-up. Within this population, we identified 1,015 potential cases of ALI. Overall, 20 positive drug-ALI associations were detected. The associations between ALI and domperidone, flunisolide and human insulin were considered as potentially new signals. Citalopram and cetirizine have been previously described as hepatotoxic in adults but not in children, while all remaining associations were already known in both adults and children. CONCLUSIONS: Data mining of multiple EHR databases for signal detection confirmed known associations between ALI and several drugs, and identified some potentially new signals in children that require further investigation through formal epidemiologic studies. This study shows that EHRs may complement traditional spontaneous reporting systems for signal detection and strengthening.

Population-based analysis of non-steroidal anti-inflammatory drug use among children in four European countries in the SOS project: what size of data platforms and which study designs do we need to assess safety issues?

BACKGROUND: Data on utilization patterns and safety of non-steroidal anti-inflammatory drugs (NSAIDs) in children are scarce. The purpose of this study was to investigate the utilization of NSAIDs among children in four European countries as part of the Safety Of non-Steroidal anti-inflammatory drugs (SOS) project. METHODS: We used longitudinal patient data from seven databases (GePaRD, IPCI, OSSIFF, Pedianet, PHARMO, SISR, and THIN) to calculate prevalence rates of NSAID use among children (0-18 years of age) from Germany, Italy, Netherlands, and United Kingdom. All databases contained a representative population sample and recorded demographics, diagnoses, and drug prescriptions. Prevalence rates of NSAID use were stratified by age, sex, and calendar time. The person-time of NSAID exposure was calculated by using the duration of the prescription supply. We calculated incidence rates for serious adverse events of interest. For these adverse events of interest, sample size calculations were conducted (alpha = 0.05; 1-beta = 0.8) to determine the amount of NSAID exposure time that would be required for safety studies in children. RESULTS: The source population comprised 7.7 million children with a total of 29.6 million person-years of observation. Of those, 1.3 million children were exposed to at least one of 45 NSAIDs during observation time. Overall prevalence rates of NSAID use in children differed across countries, ranging from 4.4 (Italy) to 197 (Germany) per 1000 person-years in 2007. For Germany, United Kingdom, and Italian pediatricians, we observed high rates of NSAID use among children aged one to four years. For all four countries, NSAID use increased with older age categories for children older than 11. In this analysis, only for ibuprofen (the most frequently used NSAID), enough exposure was available to detect a weak association (relative risk of 2) between exposure and asthma exacerbation (the most common serious adverse event of interest). CONCLUSIONS: Patterns of NSAID use in children were heterogeneous across four European countries. The SOS project platform captures data on more than 1.3 million children who were exposed to NSAIDs. Even larger data platforms and the use of advanced versions of case-only study designs may be needed to conclusively assess the safety of these drugs in children.

Replication of the OMOP experiment in Europe: evaluating methods for risk identification in electronic health record databases.

BACKGROUND: The Observational Medical Outcomes Partnership (OMOP) has just completed a large scale empirical evaluation of statistical methods and analysis choices for risks identification in longitudinal observational healthcare data. This experiment drew data from four large US health insurance claims databases and one US electronic health record (EHR) database, but it is unclear to what extend the findings of this study apply to other data sources. OBJECTIVE: To replicate the OMOP experiment in six European EHR databases. RESEARCH DESIGN: Six databases of the EU-ADR (Exploring and Understanding Adverse Drug Reactions) database network participated in this study: Aarhus (Denmark), ARS (Italy), HealthSearch (Italy), IPCI (the Netherlands), Pedianet (Italy), and Pharmo (the Netherlands). All methods in the OMOP experiment were applied to a collection of 165 positive and 234 negative control drug-outcome pairs across four outcomes: acute liver injury, acute myocardial infarction, acute kidney injury, and upper gastrointestinal bleeding. Area under the receiver operator characteristics curve (AUC) was computed per database and for a combination of all six databases using meta-analysis for random effects. We provide expected values of estimation error as well, based on negative controls. RESULTS: Similarly to the US experiment, high predictive accuracy was found (AUC >0.8) for some analyses. Self-controlled designs, such as self-controlled case series, IC temporal pattern discovery and self-controlled cohort achieved higher performance than other methods, both in terms of predictive accuracy and observed bias. CONCLUSIONS: The major findings of the recent OMOP experiment were also observed in the European databases.

Drug-induced acute myocardial infarction: identifying 'prime suspects' from electronic healthcare records-based surveillance system.

BACKGROUND: Drug-related adverse events remain an important cause of morbidity and mortality and impose huge burden on healthcare costs. Routinely collected electronic healthcare data give a good snapshot of how drugs are being used in 'real-world' settings. OBJECTIVE: To describe a strategy that identifies potentially drug-induced acute myocardial infarction (AMI) from a large international healthcare data network. METHODS: Post-marketing safety surveillance was conducted in seven population-based healthcare databases in three countries (Denmark, Italy, and the Netherlands) using anonymised demographic, clinical, and prescription/dispensing data representing 21,171,291 individuals with 154,474,063 person-years of follow-up in the period 1996-2010. Primary care physicians' medical records and administrative claims containing reimbursements for filled prescriptions, laboratory tests, and hospitalisations were evaluated using a three-tier triage system of detection, filtering, and substantiation that generated a list of drugs potentially associated with AMI. Outcome of interest was statistically significant increased risk of AMI during drug exposure that has not been previously described in current literature and is biologically plausible. RESULTS: Overall, 163 drugs were identified to be associated with increased risk of AMI during preliminary screening. Of these, 124 drugs were eliminated after adjustment for possible bias and confounding. With subsequent application of criteria for novelty and biological plausibility, association with AMI remained for nine drugs ('prime suspects'): azithromycin; erythromycin; roxithromycin; metoclopramide; cisapride; domperidone; betamethasone; fluconazole; and megestrol acetate. LIMITATIONS: Although global health status, co-morbidities, and time-invariant factors were adjusted for, residual confounding cannot be ruled out. CONCLUSION: A strategy to identify potentially drug-induced AMI from electronic healthcare data has been proposed that takes into account not only statistical association, but also public health relevance, novelty, and biological plausibility. Although this strategy needs to be further evaluated using other healthcare data sources, the list of 'prime suspects' makes a good starting point for further clinical, laboratory, and epidemiologic investigation.

Idiopathic acute liver injury in paediatric outpatients: incidence and signal detection in two European countries.

BACKGROUND: Acute liver failure is idiopathic and drug-related in, respectively, around 50 and 15 % of children. Population-based, epidemiologic data about the pattern of disease manifestation and incidence of less severe acute liver injury, either idiopathic or potentially drug-attributed are limited in children and adolescents. OBJECTIVES: (i) To assess the incidence of idiopathic acute liver injury (ALI) and its clinical features in children and adolescent outpatients; and (ii) to investigate the role of the drug as a potential cause of ALI which is considered idiopathic. METHODS: A retrospective cohort study was performed during the years 2000-2008. Data were retrieved from three longitudinal electronic healthcare databases in two European countries: Pedianet and Health Search/CSD Longitudinal Patient Database from Italy and the Integrated Primary Care Information database from The Netherlands. Cases of idiopathic acute liver injury in population aged <18 years were identified by exclusion of all competing causes of liver injury (e.g. viral, autoimmune hepatitis), according to CIOMS criteria. The potential role of drug exposure as actual underlying cause of idiopathic ALI was detected through signal detection mining techniques. Both pooled and country-specific incidence rates [IR/100,000 person-years (PYs)] of idiopathic ALI and pooled adjusted rate ratios (RR) of drugs identified as a potential cause of idiopathic ALI, plus 95 % confidence intervals (CI) were estimated using the custom-built software Jerboa. RESULTS: Among 785 definite cases of idiopathic ALI, the pooled IR was 62.4/100,000 PYs (95 % CI 58.1-66.8). The country-specific IR was higher in Italy (73.0/100,000 PYs, 95 % CI 67.8-78.4) than in The Netherlands (21.0/100,000 PYs, 95 % CI 16.0-27.2) and increased with age in both countries. Isolated elevations of liver enzymes were reported in around two-thirds of cases in Italy, while in The Netherlands the cases were more often identified by a combination of signs/symptoms. Among drugs detected as potential underlying cause of idiopathic ALI, clarithromycin (RR 25.9, 95 % CI 13.4-50), amoxicillin/clavulanic acid (RR 18.6, 95 % CI 11.3-30.6), and amoxicillin (RR 7.5, 95 % CI 3.4-16.8) were associated with the highest risk compared to non-use. CONCLUSION: The incidence of idiopathic ALI in paediatrics is relatively low and comparable with adults. Clinical presentations differ between the two European countries. Signal detection in healthcare databases allowed identifying antibiotics as the drugs mostly associated with ALI with apparently unknown aetiology.