Search

Composite indicators are a common choice for synthesizing complex phenomena. Over the years, they have grown in popularity and are now applied in many social and environmental sciences. Among others, a subject of increasing interest is gender equality analysis. Gender composite indicators, even if easy to read, may provide a limited picture of the problem. Here we discuss the potentiality to integrate the use of composite indicators for gender gaps with Bayesian networks, powerful tools for explaining the complex association structure in the dataset and developing scenarios to orient policy-making. An example is carried out on Italian province-level data.

Purpose: Clustering of patients in databases is usually ignored in one-stage meta-analysis of multi-database studies using matched case-control data. The aim of this study was to compare bias and efficiency of such a one-stage meta-analysis with a two-stage meta-analysis. Methods: First, we compared the approaches by generating matched case-control data under 5 simulated scenarios, built by varying: (1) the exposure-outcome association; (2) its variability among databases; (3) the confounding strength of one covariate on this association; (4) its variability; and (5) the (heterogeneous) confounding strength of two covariates. Second, we made the same comparison using empirical data from the ARITMO project, a multiple database study investigating the risk of ventricular arrhythmia following the use of medications with arrhythmogenic potential. In our study, we specifically investigated the effect of current use of promethazine. Results: Bias increased for one-stage meta-analysis with increasing (1) between-database variance of exposure effect and (2) heterogeneous confounding generated by two covariates. The efficiency of one-stage meta-analysis was slightly lower than that of two-stage meta-analysis for the majority of investigated scenarios. Based on ARITMO data, there were no evident differences between one-stage (OR = 1.50, CI = [1.08; 2.08]) and two-stage (OR = 1.55, CI = [1.12; 2.16]) approaches. Conclusions: When the effect of interest is heterogeneous, a one-stage meta-analysis ignoring clustering gives biased estimates. Two-stage meta-analysis generates estimates at least as accurate and precise as one-stage meta-analysis. However, in a study using small databases and rare exposures and/or outcomes, a correct one-stage meta-analysis becomes essential.

OBJECTIVES: To estimate the risk of AMI for individual NSAIDs.METHODS: A nested case-control study was performed from a cohort of new NSAID users ≥18 years (1999-2011) matching cases to a maximum of 100 controls on database, sex, age, and calendar time. Data were retrieved from six healthcare databases. Adjusted odds ratios (ORs) of current use of individual NSAIDs compared to past use were estimated per database. Pooling was done by two-stage pooling using a random effects model (ORmeta) and by one-stage pooling (ORpool).RESULTS: Among 8.5 million new NSAID users, 79,553 AMI cases were identified. The risk was elevated for current use of ketorolac (ORmeta 2.06;95%CI 1.83-2.32, ORpool 1.80; 1.49-2.18) followed, in descending order of point estimate, by indometacin, etoricoxib, rofecoxib, diclofenac, fixed combination of diclofenac with misoprostol, piroxicam, ibuprofen, naproxen, celecoxib, meloxicam, nimesulide and ketoprofen (ORmeta 1.12; 1.03-1.22, ORpool 1.00;0.86-1.16). Higher doses showed higher risk estimates than lower doses.CONCLUSIONS: The relative risk estimates of AMI differed slightly between 28 individual NSAIDs. The relative risk was highest for ketorolac and was correlated with COX-2 potency, but not restricted to coxibs.BACKGROUND: Use of selective COX-2 non-steroidal anti-inflammatory drugs (NSAIDs) (coxibs) has been associated with an increased risk of acute myocardial infarction (AMI). However, the risk of AMI has only been studied for very few NSAIDs that are frequently used

Contains fulltext : 168016.pdf (publisher's version ) (Open Access), Several studies have identified an association between Pandemrix(TM), an AS03 adjuvanted pandemic influenza A(H1N1) vaccine, and narcolepsy, a rare and under-diagnosed sleep disorder with a median onset-to-diagnosis interval of ten years. This paper reviews potential sources of bias in published studies and aims to provide, through simulation, methodological recommendations for assessment of vaccine safety signals. Our simulation study showed that in the absence of an association between the vaccine and the outcome, presence of detection bias and differential exposure misclassification could account for elevated risk estimates. These may play a major role, particularly in alert situations when observation times are limited and the disease has a long latency period. Estimates from the case-control design were less inflated than those from the cohort design when these biases were present. Overall, these simulations provide useful insights for the design and interpretation of future studies.

OBJECTIVES: To investigate the cardiovascular safety of non-steroidal anti-inflammatory drugs (NSAIDs) and estimate the risk of hospital admission for heart failure with use of individual NSAIDs.DESIGN: Nested case-control study.SETTING: Five population based healthcare databases from four European countries (the Netherlands, Italy, Germany, and the United Kingdom).PARTICIPANTS: Adult individuals (age ≥18 years) who started NSAID treatment in 2000-10. Overall, 92 163 hospital admissions for heart failure were identified and matched with 8 246 403 controls (matched via risk set sampling according to age, sex, year of cohort entry).MAIN OUTCOME MEASURE: Association between risk of hospital admission for heart failure and use of 27 individual NSAIDs, including 23 traditional NSAIDs and four selective COX 2 inhibitors. Associations were assessed by multivariable conditional logistic regression models. The dose-response relation between NSAID use and heart failure risk was also assessed.RESULTS: Current use of any NSAID (use in preceding 14 days) was found to be associated with a 19% increase of risk of hospital admission for heart failure (adjusted odds ratio 1.19; 95% confidence interval 1.17 to 1.22), compared with past use of any NSAIDs (use >183 days in the past). Risk of admission for heart failure increased for seven traditional NSAIDs (diclofenac, ibuprofen, indomethacin, ketorolac, naproxen, nimesulide, and piroxicam) and two COX 2 inhibitors (etoricoxib and rofecoxib). Odds ratios ranged from 1.16 (95% confidence interval 1.07 to 1.27) for naproxen to 1.83 (1.66 to 2.02) for ketorolac. Risk of heart failure doubled for diclofenac, etoricoxib, indomethacin, piroxicam, and rofecoxib used at very high doses (≥2 defined daily dose equivalents), although some confidence intervals were wide. Even medium doses (0.9-1.2 defined daily dose equivalents) of indomethacin and etoricoxib were associated with increased risk. There was no evidence that celecoxib increased the

Background: The risk of Guillain-Barre syndrome (GBS) following the United States' 1976 swine flu vaccination campaign in the USA led to enhanced active surveillance during the pandemic influenza (A(H1N1)pdm09) immunization campaign. This study aimed to estimate the risk of GBS following influenza A(H1N1) pdm09 vaccination. Methods: A self-controlled case series (SCCS) analysis was performed in Denmark, Finland, France, Netherlands, Norway, Sweden, and the United Kingdom. Information was collected according to a common protocol and standardised procedures. Cases classified at levels 1-4a of the Brighton Collaboration case definition were included. The risk window was 42 days starting the day after vaccination. Conditional Poisson regression and pooled random effects models estimated adjusted relative incidences (RI). Pseudo likelihood and vaccinated-only methods addressed the potential contraindication for vaccination following GBS. Results: Three hundred and three (303) GBS and Miller Fisher syndrome cases were included. Ninety-nine (99) were exposed to A(H1N1) pdm09 vaccination, which was most frequently adjuvanted (Pandemrix and Focetria). The unadjusted pooled RI for A(H1N1) pdm09 vaccination and GBS was 3.5 (95% Confidence Interval (CI): 2.2-5.5), based on all countries. This lowered to 2.0 (95% CI: 1.2-3.1) after adjustment for calendartime and to 1.9 (95% CI: 1.1-3.2) when we accounted for contra-indications. In a subset (Netherlands, Norway, and United Kingdom) we further adjusted for other confounders and there the RI decreased from 1.7 (adjusted for calendar month) to 1.4 (95% CI: 0.7-2.8), which is the main finding. Conclusion: This study illustrates the potential of conducting European collaborative vaccine safety studies. The main, fully adjusted analysis, showed that the RI of GBS was not significantly elevated after influenza A(H1N1) pdm09 vaccination (RI = 1.4 (95% CI: 0.7-2.8). Based on the upper limits of the pooled estimate we can rule out with 95

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. Conclusi

Contains fulltext : 117810.pdf (publisher's version ) (Closed access), BACKGROUND: In August 2010 reports of a possible association between exposure to AS03 adjuvanted pandemic A(H1N1)pdm09 vaccine and occurrence of narcolepsy in children and adolescents emerged in Sweden and Finland. In response to this signal, the background rates of narcolepsy in Europe were assessed to rapidly provide information for signal verification. METHODS: We used a dynamic retrospective cohort study to assess the narcolepsy diagnosis rates during the period 2000-2010 using large linked automated health care databases in six countries: Denmark, Finland, Italy, the Netherlands, Sweden and the United Kingdom. RESULTS: Overall, 2608 narcolepsy cases were identified in almost 280 million person years (PY) of follow up. The pooled incidence rate was 0.93 (95% CI: 0. 90-0.97) per 100,000 PY. There were peaks between 15 and 30 year of age (women>men) and around 60 years of age. In the age group 5-19 years olds rates were increased after the start of pandemic vaccination compared to the period before the start of campaigns, with rate ratios (RR) of 1.9 (95% CI: 1.1-3.1) in Denmark, 6.4 (95% CI: 4.2-9.7) in Finland and 7.5 (95% CI: 5.2-10.7) in Sweden. Cases verification in the Netherlands had a significant effect on the pattern of incidence over time. CONCLUSIONS: The results of this incidence study provided useful information for signal verification on a population level. The safety signal of increased narcolepsy diagnoses following the start of the pandemic vaccination campaign as observed in Sweden and Finland could be observed with this approach. An increase in narcolepsy diagnoses was not observed in other countries, where vaccination coverage was low in the affected age group, or did not follow influenza A(H1N1)pdm09 vaccination. Patient level analyses in these countries are being conducted to verify the signal in more detail.

Introduzione. Da recenti studi basati su dati amministrativi è emerso che gli inibitori della ricaptazione della serotonina (SSRI) sono associati ad un rischio di frattura superiore a quello associato agli antidepressivi triciclici (TCA) [1]. Questo risultato, tuttavia, potrebbe essere spiegato dal fatto che (i) gli SSRI potrebbero essere preferiti dai medici per trattare pazienti più fragili e (ii) gli antidepressivi sono indicati per il trattamento della depressione che, di per sé, aumenta il rischio di frattura [2]. Obiettivi. Valutare l’effetto di SSRI e TCA sul rischio di frattura attraverso opportuni disegni di studio, tenendo sotto controllo il potenziale confondimento. Metodi. E’ stato condotto uno studio caso-controllo innestato in una coorte di utilizzatori di antidepressivi orali. Nella coorte sono stati inclusi tutti i soggetti residenti in Lombardia di età superiore ai 18 anni, con almeno una prescrizione di antidepressivi orali nel periodo 2005-2007. Tutti gli individui della coorte sono stati seguiti dall’ingresso nello studio fino al primo tra i seguenti episodi: ospedalizzazione per frattura, uscita dallo studio, fine del follow-up (fine 2010). Ad ogni caso di frattura, sono stati appaiati fino a 10 controlli, selezionati tra i membri della coorte ancora a rischio di sperimentare l’evento al momento della data indice (data del primo evento di frattura) del caso. Per ciascun individuo è stato valutato l’uso di SSRI e TCA, definito come “corrente”, se la distanza tra l’ultimo giorno di copertura e la data indice era inferiore a 30 giorni, “recente” se compresa tra i 31 e i 60 giorni e “passato” se superava i 61 giorni. Inoltre, per minimizzare l’effetto del confondimento è stato implementato uno studio case-crossover, in cui per ogni caso di frattura si è confrontata l’esposizione a SSRI e TCA nel periodo a rischio (1-30 giorni precedenti la data indice) con quello di controllo (61-90 giorni precedenti la data indice). Risultati. Risultati prel

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 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. F 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.

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: P

Healthcare decision-makers are increasingly developing policies that seek information on "real-world" data providing "evidence" to support and monitor changes in clinical practice or policy decisions. Many strategies may be evaluated in experimental circumstances, but this does rarely reflect clinical practice. Due to the current focus on information and computer technology to provide safer and more efficient healthcare delivery, the amount of electronic medical records and other electronic healthcare data is increasing exponentially, and these real-world data can be used for evidence generation. This review describes why and how healthcare/policy decision making could benefit from real-world data, it introduces methods to investigate real-world clinical practice, lists potentialities of routinely collected real-world data, reviews their availability in the word, and outlines future challenges in this field.

Objective: To assess the association between pandemic influenza A (H1N1) 2009 vaccine and Guillain-Barré syndrome. Design: Case-control study. Setting: Five European countries. Participants: 104 patients with Guillain-Barré syndrome and its variant Miller-Fisher syndrome matched to one or more controls. Case status was classified according to the Brighton Collaboration definition. Controls were matched to cases on age, sex, index date, and country. Main outcome measures: Relative risk estimate for Guillain-Barré syndrome after pandemic influenza vaccine. Results: Case recruitment and vaccine coverage varied considerably between countries; the most common vaccines used were adjuvanted (Pandemrix and Focetria). The unadjusted pooled risk estimate for all countries was 2.8 (95% confidence interval 1.3 to 6.0). After adjustment for influenza-like illness/upper respiratory tract infection and seasonal influenza vaccination, receipt of pandemic influenza vaccine was not associated with an increased risk of Guillain-Barré syndrome (adjusted odds ratio 1.0, 0.3 to 2.7). The 95% confidence interval shows that the absolute effect of vaccination could range from one avoided case of Guillain-Barré syndrome up to three excess cases within six weeks after vaccination in one million people. Conclusions