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Background: Automated disproportionality analysis of spontaneous reporting is increasingly used routinely. It can theoretically be influenced by a competition bias for signal detection owing to the presence of reports related to well-established drug-event associations.Objective: The aim of the study was to explore the effects of competition bias on safety signals generated from a large spontaneous reporting research database.Methods: Using the case/non-case approach in the French spontaneous reporting research database, which includes data of reporting in France from January 1986 to December 2001, the effects of the competition bias were explored by generating safety signals associated with six events of interest (gastric and oesophageal haemorrhages, central nervous system haemorrhage and cerebrovascular accidents, ischaemic coronary disorders, migraine headaches, muscle pains, and hepatic enzymes and function abnormalities) before and after removing from the database reports relating to drugs known to be strongly associated with these events, whether they constituted cases or non-cases. As this study was performed on a closed database (last data entered 31 December 2001), potential signals unmasked by removal were considered as real signals if no or only incomplete knowledge about the association was available from the literature before 1 January 2002.Results: For gastric and oesophageal haemorrhages, after removing reports involving antithrombotic agents or NSAIDs, three potential signals were unmasked (prednisone, rivastigmine and isotretinoin). For central nervous system haemorrhage and cerebrovascular accidents, after removing reports involving antithrombotic agents, three potential signals were unmasked (ethinylestradiol, interferon-α-2B and methylprednisolone). For ischaemic coronary disorders, after removing reports involving anthracyclines, bleomycine, anti-HIV drugs or triptans, one potential signal was unmasked (ondansetron). For migraine headaches, after removing reports involving nitrates, calcium channel blockers, opioid analgesics or intravenous immunoglobulins, six potential signals were unmasked (ammonium chloride, leflunomide, milnacipran, montelukast, proguanil and pyridostigmine). For muscle pains, after removing reports involving statins or fibrates, seven potential signals were unmasked (hydroxychloroquine, lactulose, levodopa in combination with dopadecarboxylase inhibitor, nevirapine, nomegestrol, ritonavir and stavudine). Finally, for hepatic enzymes and function abnormalities, after removing reports involving NSAIDs, anilides, antituberculosis drugs, antiepileptics, ketoconazole, tacrine, or amineptine, two potential signals were unmasked (caffeine, metformin). Of all these unmasked potential signals, ten appeared non/incompletely documented as at 1 January 2002 and were considered as real signals, with three of these later being confirmed by the literature and finally considered as true positives (isotretinoin, methylprednisolone and milnacipran).Conclusion: This study confirms that a competition bias can occur when performing safety signal generation in spontaneous reporting databases. The minimization of this bias could lead to previously masked signals being revealed. [ABSTRACT FROM AUTHOR]

Background: Improving the detection of drug safety signals has led several pharmacovigilance regulatory agencies to incorporate automated quantitative methods into their spontaneous reporting management systems. The three largest worldwide pharmacovigilance databases are routinely screened by the lower bound of the 95% confidence interval of proportional reporting ratio (PRR₀₂.₅), the 2.5% quantile of the Information Component (IC₀₂.₅) or the 5% quantile of the Gamma Poisson Shrinker (GPS₀₅). More recently, Bayesian and non-Bayesian False Discovery Rate (FDR)-based methods were proposed that address the arbitrariness of thresholds and allow for a built-in estimate of the FDR. These methods were also shown through simulation studies to be interesting alternatives to the currently used methods.Objective: The objective of this work was twofold. Based on an extensive retrospective study, we compared PRR₀₂.₅, GPS₀₅ and IC₀₂.₅ with two FDR-based methods derived from the Fisher's exact test and the GPS model (GPS(pH0) [posterior probability of the null hypothesis H₀ calculated from the Gamma Poisson Shrinker model]). Secondly, restricting the analysis to GPS(pH0), we aimed to evaluate the added value of using automated signal detection tools compared with 'traditional' methods, i.e. non-automated surveillance operated by pharmacovigilance experts.Methods: The analysis was performed sequentially, i.e. every month, and retrospectively on the whole French pharmacovigilance database over the period 1 January 1996-1 July 2002. Evaluation was based on a list of 243 reference signals (RSs) corresponding to investigations launched by the French Pharmacovigilance Technical Committee (PhVTC) during the same period. The comparison of detection methods was made on the basis of the number of RSs detected as well as the time to detection.Results: Results comparing the five automated quantitative methods were in favour of GPS(pH0) in terms of both number of detections of true signals and time to detection. Additionally, based on an FDR threshold of 5%, GPS(pH0) detected 87% of the RSs associated with more than three reports, anticipating the date of investigation by the PhVTC by 15.8 months on average.Conclusions: Our results show that as soon as there is reasonable support for the data, automated signal detection tools are powerful tools to explore large spontaneous reporting system databases and detect relevant signals quickly compared with traditional pharmacovigilance methods. [ABSTRACT FROM AUTHOR]

Background: Anti-tumour necrosis factor (TNF) agents, through their intense immunoregulatory effect, have been suspected to increase the risk of malignant lymphoma. However, the classical epidemiological approaches conducted over about the last 10 years have not totally succeeded in addressing the question of a causal or artifactual association. Therefore, the analysis of a substantial set of case reports, although usually considered as poorly generalizable to the general population, could be particularly informative. Two main sources of case reports in postmarketing settings are available; publications in medical journals and reports to pharmacovigilance systems.Objective: The aim of the study was to compare the characteristics of case reports from both these sources in order to understand whether they provided the same information for the investigation of the causal link between lymphoma and anti-TNF agents.Methods: All case reports of malignant lymphoma in patients treated with an anti-TNF agent published in MEDLINE and all reports to the French pharmacovigilance system up to 1 February 2010 were identified. Cases of malignant lymphoma identified in postmarketing surveillance from both sources were compared regarding the following variables: age, sex, anti-TNF agent involved, indication for use, type of lymphoma, prior or concomitant immunosuppressive drugs and time to onset of lymphoma.Results: A total of 81 published case reports and 61 cases reported to the French pharmacovigilance system were compared. In published reports, patients were younger (p = 0.03) and more frequently receiving a first anti-TNF treatment (p = 0.03), particularly infliximab (p = 0.03). Conversely, in the pharmacovigilance system reports, a succession of different anti-TNFs (p = 0.03) and adalimumab (p < 0.0001) were more frequently reported. Lymphomas in patients treated with anti-TNF agents for Crohn's disease were more prevalent in published cases than in pharmacovigilance reports (p < 0.0001), and in particular involved hepatosplenic T-cell lymphoma. Conversely, rheumatoid arthritis was the main indication for anti-TNF agents in pharmacovigilance reports (p = 0.01). Time to onset was markedly shorter in published cases (median 12 months) than in pharmacovigilance reports (median 30 months; p = 0.0001).Conclusions: Characteristics of published cases and those reported to the French pharmacovigilance system differed markedly for all characteristics tested, except sex and the use of prior or concomitant immunosuppressive drugs. Published case reports favoured convincing arguments for drug causation whereas cases reported to the pharmacovigilance system were more disparate but could describe more accurately the reality of lymphoma occurrence in this particular population. These results argue for the use of the pharmacovigilance reports when case reports are used to investigate the causal link between lymphoma and anti-TNF agents at the population level. Data from cases notified to the French pharmacovigilance system did not indicate an increased risk of lymphoma during the early phase of anti-TNF treatment. To confirm this hypothesis, a study combining pharmacovigilance reports from several countries, or, if feasible, a cohort study both with a large sample size and a long duration of follow-up would be required. [ABSTRACT FROM AUTHOR]

Background: Different methods have been proposed for assessing a possible causal link between a drug treatment and an adverse event in individual patients. They approximately belong to three main categories: expert judgement, operational algorithms and probabilistic approaches.Objective: To compare, in a set of actual drug adverse event reports, three different methods for assessing drug causality, each belonging to one of the three main categories: expert judgement, the algorithm used by the French pharmacovigilance centres since 1985, and a novel method based on the logistic function.Methods: Fifty drug-event pairs were randomly sampled from the database of the Bordeaux pharmacovigilance centre, France. To serve as the gold standard, the probability for drug causation, from 0 to 1, was first determined for each drug-event pair by a panel of senior experts until consensus was reached. Causality was then assessed by members of the Bordeaux pharmacovigilance centre by using the French algorithm and the logistic method. Results expressed as a probability with the logistic method and as a score from 0 to 4 with the French algorithm were then compared with consensual expert judgement, as were the sensitivity, specificity and positive and negative predictive values.Results: Probabilities ranged from 0.08 to 0.99 (median 0.58; mean 0.60) for experts versus 0.18-0.88 (median 0.73; mean 0.67) for the logistic method. Consensual expert judgement was not discriminant (p = 0.50) in ten cases. For the algorithm, only three of five causality scores were found, doubtful scores being clearly predominant (74%) followed by possible (16%) and probable (10%) scores. Sensitivity and specificity were 0.96 and 0.42, respectively, for the logistic method versus 0.42 and 0.92 for the algorithm. Positive and negative predictive values were 0.78 and 0.83, respectively, for the logistic method versus 0.92 and 0.42 for the algorithm.Conclusions: Agreement between the three approaches was poor, and only satisfactory for drug events judged as drug-induced by consensual expert judgement. The logistic method showed high sensitivity at the expense of poor specificity. Conversely, the algorithm had poor sensitivity but good specificity. The comparatively good sensitivity and positive predictive values of the logistic method suggest that it may be more useful in the routine or automated assessment of case reports of suspected but still unknown adverse drug reactions. With a substantial rate of false positives relative to true negatives (low specificity), the logistic method does not replace, but can be complemented by, critical clinical assessment of individual cases in evaluating drug-related risk. [ABSTRACT FROM AUTHOR]

Background: Cholinesterase inhibitors are used in Alzheimer's disease, mostly in elderly persons with co-morbidities and receiving co-medications that could increase the risk of serious adverse reactions.Objective: To identify factors associated with serious adverse drug reactions (ADRs) in patients treated with cholinesterase inhibitors.Methods: All ADRs associated with donepezil, rivastigmine or galantamine were identified in the French pharmacovigilance database, from the launching of these drugs to January 2007. Serious ADRs (SADRs) were those that led to death, hospitalization or prolongation of hospitalization, or that were life threatening. A multiple logistic regression analysis was used to identify factors associated with seriousness in the reported adverse reactions.Results: We identified 773 reports of ADRs related to cholinesterase inhibitor use, among which 438 (57%) concerned SADRs. The median age of patients was 80 years (interquartile range: 75-84 years); 65.1% were women. The most represented ADRs were those responsible for CNS disorders (17.0%), gastrointestinal disorders (16.2%) and cardiac rhythm disorders (11.2%). Factors associated with an increased risk of SADRs were: age (odds ratio [OR] 1.92; 95% CI 1.22, 3.02 for subjects aged 85 years and over), use of atypical antipsychotics (OR 2.15; 95% CI 1.04, 4.46), use of conventional antipsychotics (OR 2.06, 95% CI 1.10, 3.85), use of antihypertensive drugs (OR 2.11; 95% CI 1.47, 3.02) and use of drugs targeting the alimentary tract and metabolism (OR 1.62; 95% CI 1.06, 2.46). The use of benzodiazepines (long-acting or others), antidepressants (tricyclic or others) or antiarrhythmic drugs was not associated with the reporting of SADRs.Conclusions: An increased risk of SADRs related to cholinesterase inhibitors was associated with the use of antipsychotics (with no difference between conventional and atypical antipsychotics), drugs targeting the alimentary tract/metabolism and antihypertensive drugs. It was not associated with the use of other psychotropic drugs, other non-psychotropic CNS drugs or with the use of antiarrhythmic agents. The association with drugs targeting the alimentary tract and metabolism could result from a protopathic bias or reflect the particular sensitivity to serious nausea and vomiting in patients already treated for gastrointestinal disorders. These results confirm that attention needs to be paid to patients receiving both cholinesterase inhibitors and antipsychotics. [ABSTRACT FROM AUTHOR]