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Owing to a broad spectrum and low cost antimicrobial, cotrimoxazole is largely prescribed. However, its use is associated with various adverse drug reactions (ADRs) that warrant to ensure rational prescribing. This study aimed to describe spontaneous reports of cotrimoxazole ADRs and to evaluate the quality of prescription in patients who had ADRs. Suspected cotrimoxazole-induced ADRs cases reported to the Bordeaux regional pharmacovigilance center (France) during a 5-year period were described. Seriousness was assessed according to international criteria. Quality of prescription was assessed by compliance with the Summary of Product Characteristics (SPC) and relevance of cotrimoxazole indication. Then, an ADR was considered as preventable if the cotrimoxazole indication was not relevant, or potentially preventable if indication was relevant but the prescription was not compliant with the SPC. A total of 96 cases were analyzed: median age was 60.5 years (range: 4-94); 59.4% of patients were male. ADRs were mostly cutaneous disorders (n = 46) and hematological disorders (n = 25). A total of 60 serious ADRs occurred in 55 patients. Prescribers complied with all SPC recommendations in 21.9% of cases. Indication of cotrimoxazole was relevant or highly relevant in 41 cases. In 58% of cases, the occurrence of a cotrimoxazole-induced ADR would have been preventable or potentially preventable. In a context of increasing interest for this antibiotic to treat infections due to resistant bacteria, physicians should be more aware of the potential consequences of inappropriate prescribing cotrimoxazole and reserve its use when there is no alternative and under suitable monitoring., (© 2021 Société Française de Pharmacologie et de Thérapeutique.)

Introduction: Qualitative approaches based on drug causality assessment estimate the causal link between a drug and the occurrence of an adverse event from individual case safety reports. Quantitative approaches based on disproportionality analyses were developed subsequently to allow automated statistical signal detection from pharmacovigilance databases. This study assessed the potential value of causality assessment for automated safety signal detection., Methods: All drug-serious adverse event pairs with a positive rechallenge and a semiology suggestive of drug causality were identified in the French pharmacovigilance database (BNPV) from 2011 to 2017. The results were compared with those obtained from automated disproportionality analyses of the BNPV/World Health Organization (WHO) VigiBase ® , complemented by the list of signals validated by the WHO-UMC (Uppsala Monitoring Centre). Summary of Product Characteristics (SmPCs), Martindale ® , Meyler's ® and MedLINE ® were used as other sources of information for the purpose of comparison., Results: Of the 155 pairs of interest, 115 (74.2%) were also identified by another source of information. Since the individual case reporting in the BNPV, 23 (14.8%) of the adverse events (AEs) have been added to the SmPC, seven of which were not identified by disproportionality. Finally, 40 pairs were not identified by any other source of information, 13 of which were considered as potential new safety signals after analysis of case reports by pharmacovigilance experts. The signals identified by causality assessment involved antineoplastic and immunomodulatory drugs especially, in comparison with signals identified by WHO-UMC or by disproportionality within the BNPV., Conclusion: The approach therefore appears useful as an additional tool for safety signal detection, especially for antineoplastic and immunomodulating agents.

The methods for causality assessment of adverse drug reactions were developed in the 1970s and 1980s, alongside the development of pharmacovigilance. The French method is one of the earlier of these, following on from the pioneering works by Irey and Karch and Lasagna. Initially published in 1978, it was updated in 1985, and again in 2011. The main alterations to the original method are presented in tables annexed to this paper. The successive versions improved the presentation, provided more formalised definitions of the criteria for assessing causality, while at the same time ensuring the method remained easy to use. Causality assessment enables the causal link between a drug and the occurrence of an adverse reaction to be formalised and explained. It contributes to diagnosis, and to determining the action to be taken in case of an adverse drug reaction. It can contribute to the quality and the relevance of the data stored in pharmacovigilance databases., (Copyright © 2016 Société française de pharmacologie et de thérapeutique. Published by Elsevier Masson SAS. All rights reserved.)

Objectives: The aims of this study were to determine the patterns of analgesic adverse drug reactions (ADRs) and to assess their preventability and contributing factors., Methods: This is a retrospective, descriptive study conducted on ADRs of analgesics and other drugs indicated as analgesics, spontaneously reported to the Bordeaux pharmacovigilance center from January 2011 to June 2012., Results: The 141 cases selected for the analysis included 16 cases of medication errors (11.3%) and 15 addiction cases (10.6%). In total, 214 ADRs were registered, for which 173 analgesic medicines were suspected. The most frequent ADRs reported were nervous system disorders (26.6%), psychiatric disorders (15.0%), and skin and subcutaneous tissue disorders (12.1%). Tramadol alone or in combination (17.3%), followed by morphine (15%), fentanyl (9.8%), and paracetamol (8.7%) were the most frequently involved analgesics. More than half of the cases (54.6%) were serious and led to hospitalization or prolonged hospitalization. Preventability was determined for 134 cases (95%): 51.5% were considered as preventable, 26.1% not preventable, and 22.4% not assessable. The main contributing factors for the preventable cases included negligence of recommendations for analgesic use and failure to consider patients' risk factors when prescribing., Conclusions: A significant number of analgesic ADRs could be prevented, and being aware of their contributing factors promotes efficient analgesia with minimum risks to the patients.

To assess the incidence of hospital admissions related to adverse drug reactions (ADRs) in France and the frequency of preventable ADRs in France, a prospective study was conducted among a representative randomly selected sample of medical wards in public hospitals between December 2006 and June 2007; all patients admitted during a 2-week period were included. An ADR-related hospitalization case was defined as a hospital admission because of an ADR, and an independent committee reviewed and validated all potential cases. Preventability was assessed using the French ADR preventability scale. Data were extrapolated to the population of France. Among 2692 admissions, 97 were related to an ADR (incidence 3.6%, 95% confidence interval, CI [2.8-4.4]). Patients admitted for an ADR were significantly older than those admitted for other reasons (P < 0.001). A third (32.0%) of ADR-related hospitalizations were 'preventable', 16.5% 'potentially preventable'. Drug interactions accounted for 29.9% of ADR-related hospitalizations. The most frequent causes of ADR-related hospitalizations were vascular disorders (20.6%), mainly bleeding complications, central nervous system disorders (11.3%), gastrointestinal disorders, and general disorders (9.3%). Antithrombotic and antineoplastic agents were the most frequently involved (12.6% each), followed by diuretics and analgesics (9.0% each). Vitamin-K-antagonists (VKAs) were the most common drugs associated with admission. The estimated annual number of ADR-related hospitalizations in France was 143 915 (95% CI [112 063-175 766]). ADRs were a significant cause of hospital admission in 2006-2007, in particular those due to VKAs. As new oral anticoagulants (NOACs) have been marketed, more attention needs to be paid to ensure a safe use of antithrombotic agents., (© 2014 Société Française de Pharmacologie et de Thérapeutique.)

Objective: The objective of this study was to evaluate the performance of Standardised MedDRA® Queries (SMQs) in adverse drug reaction (ADR) identification., Methods: ADR cases included in the last complete year of the French Pharmacovigilance database for research were used to test four SMQs (narrow and broad): agranulocytosis, demyelination, osteonecrosis and psychosis. Reference cases were identified by free-text search and validated by two authors. Sensitivity (Se), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV) of narrow and broad searches of each SMQ were calculated and reported as proportions with 95% exact confidence interval (CI)., Results: Among 20,830 cases reported in 2009, 337 validated cases of agranulocytosis, 17 of demyelination, 52 of osteonecrosis and 230 of psychosis were included in the reference sets. Estimations of SMQ narrow search performance were as follows: Se 62.9% (95% CI 57.5-68.1) and PPV 46.8% (95% CI 42.1-51.5) for agranulocytosis; Se 88.2% (95% CI 63.6-98.5) and PPV 34.1% (95% CI 20.5-49.9) for demyelination; Se 94.2% (95% CI 84.1-98.8) and PPV 74.2% (95% CI 62.0-84.2) for osteonecrosis; and Se 75.1% (95% CI 69.0-80.6) and PPV 87.8% (95% CI 82.3-92.0) for psychosis. Results obtained using the broad search were similar except for PPV concerning osteonecrosis (52.7% [95% CI 42.1-63.1]) and psychosis (61.4% [95% CI 55.7-66.8]). For all selected SMQs, Sp and NPV were greater than 98% for both narrow and broad searches., Conclusion: Heterogeneous performance of SMQs for case retrieval was found and seems to be related to the characteristics of the condition of interest. It could therefore be expected that for other SMQs, performance may be affected in the same manner.

Background: In the context of the European reassessment of the benefit-risk balance of hormonal contraceptives, French data about thromboembolic events were requested., Objective: The aim of this study was to determine the number of patients exposed to hormonal contraception or cyproterone acetate among hospitalized females diagnosed with a thromboembolic event in 2012, to retrospectively analyze specific risk factors of venous and arterial thromboembolism and to assess the magnitude of the under-reporting of such events to the national pharmacovigilance system., Methods: This cross-sectional study included 15- to 49-year-old women with pulmonary embolism, venous cerebral thrombosis, ischemic stroke, or myocardial infarction, hospitalized in 2012, and identified within the computerized hospital databases of 30 French teaching hospitals., Results: Among the 2,966 cases identified, 803 (27.1 %) patients had been exposed to a hormonal contraceptive (747) or to cyproterone acetate (56). Among these, there were 452 venous thromboembolic events (VTEs) and 351 arterial thromboembolic events (ATEs). Age ≥40 years and personal thrombophilia diagnosed after the event were the main VTE risk factors, while current smoking and age ≥40 years were the main ATE risk factors. The mean number of associated risk factors was significantly lower for VTE than for ATE (1.1 vs 2.3). The proportion of cases with no risk factors was higher for third- and fourth-generation than for first- and second-generation combined oral contraceptives. Overall, the under-reporting rate was 92.5 % (95 % CI 70.0-97.3)., Conclusion: This study highlighted the need to strengthen the knowledge of patients and health professionals about thromboembolic risk factors at the first prescription and renewal of hormonal contraceptives.

Purpose: To test an automated method to decrease the number of false-positive (FP) signals of disproportionate reportings (SDRs) generated by co-prescription., Methods: Automated backward stepwise removal of reports concerning the drug associated with the highest ranked SDR for an event was tested for gastric and oesophageal haemorrhages (GOH), central nervous system haemorrhages and cerebrovascular accidents (CNSH), ischaemic coronary artery disorders and muscle pains (MP) using the reporting odds ratio in the French spontaneous reporting research database. After ranking SDRs detected in the complete dataset on the lower limit of the reporting odds ratio 95% confidence interval, reports concerning the drug with the highest ranked SDR were removed. In the dataset thus generated, SDRs were again identified, ranked and reports related to the drug involved in the newly highest ranked SDR removed. The process was repeated until no signal was detected. Initially detected SDRs eliminated using this technique were assessed regarding the summary of products characteristics and the literature to determine their FP nature., Results: Seventeen SDRs were successively eliminated for GOH, 37 for CNSH, 15 for ischaemic coronary artery disorders, and 36 for MP. Four were FP for GOH, 29 for CNSH, 7 for ACI and none were FP for MP. The positive predictive value of the backward stepwise removal procedure in identifying FP SDRs ranged from 0% (MP) to 78.4% (CNSH)., Conclusions: Although further adjustment is needed to improve the method presented herein, our results suggest that numerous FP signals because of co-prescription bias could be eliminated using an automated method., (Copyright © 2013 John Wiley & Sons, Ltd.)

Background: An updated probabilistic causality assessment method and the Liverpool algorithm presented as an improved version of the Naranjo algorithm, one of the most used and accepted causality assessment methods, have recently been proposed., Objective: In order to test the validity of the probabilistic method in routine pharmacovigilance, results provided by the Naranjo and Liverpool algorithms, as well as the updated probabilistic method, were each compared with a consensual expert judgement taken as reference., Methods: A sample of 59 drug-event pairs randomly sampled from spontaneous reports to the French pharmacovigilance system was assessed by expert judgement until reaching consensus and by members of a pharmacovigilance unit using the updated probabilistic method, the Naranjo and Liverpool algorithms. Probabilities given by the probabilistic method, and categories obtained by both the Naranjo and the Liverpool algorithms were compared as well as their sensitivity, specificity, positive and negative predictive values., Results: The median probability for drug causation given by the consensual expert judgement was 0.70 (inter-quartile range, IQR 0.54-0.84) versus 0.77 (IQR 0.54-0.91) for the probabilistic method. For the Naranjo algorithm, the 'possible' causality category was predominant (61 %), followed by 'probable' (35 %), 'doubtful', and 'almost certain' categories (2 % each). Category distribution obtained with the Liverpool algorithm was similar to that obtained by the Naranjo algorithm with a majority of 'possible' (61 %) and 'probable' (30 %) followed by 'definite' (7 %) and 'unlikely' (2 %). For the probabilistic method, sensitivity, specificity, positive and negative predictive values were 0.96, 0.56, 0.92 and 0.71, respectively. For the Naranjo algorithm, depending on whether the 'possible' category was considered in favour or in disfavour of drug causation, sensitivity was, respectively, 1 or 0.42, specificity 0.11 or 0.89, negative predictive value 1 or 0.22 and positive predictive value 0.86 or 0.95; results were identical for the Liverpool algorithm., Conclusion: The logistic probabilistic method gave results closer to the consensual expert judgment than either the Naranjo or Liverpool algorithms whose performance were strongly dependent on the meaning given to the 'possible' category. Owing to its good sensitivity and positive predictive value and by providing results as continuous probabilities, the probabilistic method seems worthy to use for a trustable assessment of adverse drug reactions in routine practice.

Purpose: To assess the prevalence of adverse drug reactions (ADRs) occurring in patients with Alzheimer's disease (AD) or other dementia in France., Methods: A cross-sectional multicentre study was conducted by the French network of the 31 regional pharmacovigilance centres on a given day. The subjects were selected by random draw to be a representative sample of French patients with dementia: consultations of dementia clinics, nursing-homes, acute and long care geriatric units, rehabilitation care geriatric units. The staff of each medical structure together with that of the pharmacovigilance centre defined a day for including the patients. Socio-demographic data, history, ADR and drugs given were registered., Results: There were 1332 subjects included, 51.1% living at home, 48.8% in institutions, aged 82.0 ± 8.0 years (46-108); 61.3% suffered from AD. Mean number of drugs was 6.3 ± 3.1. Anti-dementia drugs were given to 66.4% subjects. ADR prevalence was 5.0% (95% CI: 3.9-6.2) without a significant difference between at home and institutionalized patients. ADR consisted of gastro-intestinal (23.2%), central nervous system (17.4%) and psychiatric disorders (8.7%). Of the ADR, 31.9% were serious, and 47.8% preventable. The drugs most often involved were anti-dementia (28.9%), cardio-vascular (28.9%) and psychotropic drugs (26.4%, anxiolytics, hypnotics, antidepressants, neuroleptics)., Conclusion: This national scale study showed that iatrogenesis in patients with AD and related dementia can at times be serious and preventable. Therefore, special attention is required when prescribing psychotropic and anti-dementia drugs, as they are frequently used and induce half of the ADR in this population., (Copyright © 2013 John Wiley & Sons, Ltd.)

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.

Objective: Updating a logistic causality assessment method to improve its agreement with consensual expert judgment (CEJ)., Study Design and Setting: A random sample of 53 drug-event pairs from a pharmacovigilance database were evaluated independently by CEJ and by a group of experts in pharmacovigilance using the logistic method. Causes of disagreement between both approaches were analyzed, and changes in the assessment of some criteria of the logistic method were proposed and tested in models. The model giving results closest to the CEJ was retained and compared with the initial version on another set of drug-event pairs., Results: Finally, only the criterion "Search for nondrug cause" was changed into "Search for other causes." The assessment not investigated, possible other cause decreased the probability of drug causation instead of being neutral, whereas the assessment not applicable, not required remained neutral. This new version presents much improved specificity (0.56 vs. 0.33), relatively good sensitivity (0.96), and positive and negative predictive values (0.92 and 0.71)., Conclusion: The updated logistic method presented here improves the initial version that had poor specificity and tended to overestimate drug causation. This new version presents satisfactory characteristics to be used in routine pharmacovigilance., (Copyright © 2012 Elsevier Inc. All rights reserved.)

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.

Purpose: To study whether reports related to known drug-event associations could hinder the detection of new signals by increasing the detection thresholds when using disporportionality analyses in spontaneous reporting (SR) databases., Methods: The French SR database (2005-2006 data) was used to test this hypothesis for the following events: bleeding, headache, hepatitis, myalgia, myocardial infarction, stroke, and toxic epidermal necrolysis (TEN). For each of these, using the Proportional Reporting Ratio (PRR) and the Reporting Odds Ratio (ROR), the number of cases needed to trigger a signal out of 50, 100, and 200 reports for a hypothetical newly introduced drug were computed before and after removing from the database reports involving drugs known to be associated with the event., Results: For bleeding and stroke, removing potentially competitive data resulted in a decrease of the number of cases needed to trigger a signal for a newly introduced drug for both PRR and ROR (e.g., from 9 to 4, and 5 to 3 cases out of 50 reports for bleeding and stroke, respectively using the PRR). They were not or only slightly modified for the other studied events., Conclusions: Removing reports related to known drug-event associations could increase the sensitivity of signal detection in SR databases. This should be considered when using SR databases for signal detection as it could result in earlier identification of new drug-event associations., (Copyright © 2010 John Wiley & Sons, Ltd.)

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.

Purpose: Data mining on electronic health records (EHRs) has emerged as a promising complementary method for post-marketing drug safety surveillance. The EU-ADR project, funded by the European Commission, is developing techniques that allow mining of EHRs for adverse drug events across different countries in Europe. Since mining on all possible events was considered to unduly increase the number of spurious signals, we wanted to create a ranked list of high-priority events., Methods: Scientific literature, medical textbooks, and websites of regulatory agencies were reviewed to create a preliminary list of events that are deemed important in pharmacovigilance. Two teams of pharmacovigilance experts independently rated each event on five criteria: 'trigger for drug withdrawal', 'trigger for black box warning', 'leading to emergency department visit or hospital admission', 'probability of event to be drug-related', and 'likelihood of death'. In case of disagreement, a consensus score was obtained. Ordinal scales between 0 and 3 were used for rating the criteria, and an overall score was computed to rank the events., Results: An initial list comprising 23 adverse events was identified. After rating all the events and calculation of overall scores, a ranked list was established. The top-ranking events were: cutaneous bullous eruptions, acute renal failure, anaphylactic shock, acute myocardial infarction, and rhabdomyolysis., Conclusions: A ranked list of 23 adverse drug events judged as important in pharmacovigilance was created to permit focused data mining. The list will need to be updated periodically as knowledge on drug safety evolves and new issues in drug safety arise., (Copyright (c) 2009 John Wiley & Sons, Ltd.)

Objective: To assess the characteristics of life-threatening adverse drug reactions in patients admitted to medical intensive care unit and to define those that could facilitate early identification., Design: A prospective 6-month observational study., Patients: Of the 436 admissions to the teaching hospital medical intensive care unit, all patients aged over 15 years and who had received documented drug treatment were included (n = 405)., Measurements: Characteristics of patients [age, gender, underlying diseases, organ failure(s), drugs taken, Severity Acute Physiologic Score II, length of stay, outcome at discharge] were prospectively collected using a standardised questionnaire. A panel of experts assessed putative serious adverse drug reaction(s) for each drug taken and each organ failure at admission by using a standardised causality assessment method. Characteristics of patients with and without serious adverse drug reactions at admission were compared using univariate and then stepwise descending multivariate logistic regression., Results: Of the 405 patients included, 111 (27.4%) presented an adverse drug reaction leading to organ failure. In 48% of cases adverse drug reactions were preventable, 23% were undiagnosed and 19% contributed to death. Age over 75 years [odds ratio (OR) 2.25; 95% confidence interval (CI) 1.15-4.38; p = 0.02], having more than three drugs (OR 6.90; 95% CI 1.44-33.00; p = 0.02) and a diagnosis of haematological malignancy (OR 6.19; 95% CI 2.07-18.53; p = 0.001) were independently associated with serious adverse drug reactions., Conclusions: Preventable life-threatening adverse drug reactions were frequently involved in organ failure at admission to medical intensive care; many of them had not been identified.

Aims: To evaluate agreement between five senior experts when assessing seven causality criteria and the probability of drug causation., Methods: A sample of 31 adverse event-drug pairs was constituted. For each pair, five experts separately assessed (i) the probability of drug causation, which was secondarily divided into seven causality levels: ruled out (0-0.05), unlikely (0.06-0.25), doubtful (0.26-0.45), indeterminate (0.46-0.55), plausible (0.56-0.75), likely (0.76-0.95), and certain (0.96-1); and (ii) seven causality criteria. To test discrepancies between experts, the kappa index was used., Results: The agreement of the five experts was very poor (kappa = 0.05) for the probability of drug causation. Among the seven levels of causality, only 'doubtful' showed a significant rate of agreement (kappa = 0.32, P < 0.001). For all criteria, the kappa index was significant except for the item 'risk(s) factor(s)' (kappa = 0.09). Agreement between experts was good (0.64, P < 0.001) only for the criterion 'reaction at site of application or toxic plasma concentration of the drug or validated test'. However, the rate of agreement with kappa indices of the causality criteria ranged from 0.12 to 0.38., Conclusions: This study confirms that in the absence of an operational procedure, agreement between experts is low. This should be considered when designing a causality assessment method. In particular, criteria inducing a low level of agreement should have their weight reduced.

Background and Objective: The many methods proposed for causality assessment of adverse drug reaction (ADR) generally rely on algorithms. They have no clear relationship to probabilities, however, a situation we attempted to improve., Study Design and Setting: Thirty ADR cases corresponding to 32 suspect drugs were randomly selected from the French pharmacovigilance database. The statistical weighting was performed by using a multilinear regression with logit(p) as the dependent variable and seven judgment criteria as independent variables. The best model (i.e., giving the best correlation with the gold standard) was retained for the new causality assessment method., Results: The weights [logit(p)] for the 21 choices, on average three for each of the seven criteria, ranged from -3.95 to 0.86, secondarily rounded to multiples of 0.5. The correlation between the probability obtained from the final method and the gold standard was quite good (R(2) = .92)., Conclusion: This method based on the rational weighting of seven causality criteria is straightforward to use and provides very good agreement with experts' judgment. Moreover, unlike most classical algorithms, it respects one basic rule of probabilities-namely, a symmetrical probability distribution for drug causation around the .5 neutral position (maximum uncertainty).

Background: Global introspection is, with operational algorithms and Bayes' theorem, one of the three main approaches used to assess the causal relationship between a drug treatment and the occurrence of an adverse event., Objective: To analyze and compare the judgments of five senior experts using global introspection about drug causation on a random set of putative adverse drug reactions., Methods: A random sample of 150 drug-effect pairs was constituted. For each pair, five senior experts had to independently assess the probability of drug causation from 0 to 1 by using a 100 mm visual analog scale (VAS). For analysis, those probabilities were secondarily split into seven levels of causality: excluded (0-0.05); unlikely (0.06-0.25); doubtful (0.26-0.45); unassessable/unclassifiable (0.46-0.55); plausible (0.56-0.75); likely (0.75-0.95); and certain (0.95-1). Agreement among the five experts was assessed using kappa coefficients (kappa)., Results: The overall agreement between experts was poor (kappa=0.20), although significantly different from chance, and varied according to the level of causality. It was lower for the unlikely, doubtful, unassessable/unclassifiable, and plausible categories (kappa=0.03, 0.03, -0.01, and 0.13, respectively) than for VAS extremes: excluded, likely, and certain (kappa=0.40, 0.32, and 0.30, respectively)., Conclusion: This study confirms that experts express marked disagreements when assessing drug causality independently. The agreement rate was lower for intermediate levels of causality, especially when strong evidence was lacking for confirming or ruling out drug causality. Therefore, in a decision-making context, a step-by-step consensual approach such as the Delphi method seems necessary to make the assessment of such cases more reliable.