Apport du vitex agnus castus L. dans le traitement du syndrome prémenstruel

STRASBOURG-Medecine (674822101) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Descriptions of Adverse Drug Reactions Are Less Informative in Forums Than in the French Pharmacovigilance Database but Provide More Unexpected Reactions

Background: Social media have drawn attention for their potential use in Pharmacovigilance. Recent work showed that it is possible to extract information concerning adverse drug reactions (ADRs) from posts in social media. The main objective of the Vigi4MED project was to evaluate the relevance and quality of the information shared by patients on web forums about drug safety and its potential utility for pharmacovigilance.Methods: After selecting websites of interest, we manually evaluated the relevance of the content of posts for pharmacovigilance related to six drugs (agomelatine, baclofen, duloxetine, exenatide, strontium ranelate, and tetrazepam). We compared forums to the French Pharmacovigilance Database (FPVD) to (1) evaluate whether they contained relevant information to characterize a pharmacovigilance case report (patient’s age and sex; treatment indication, dose and duration; time-to-onset (TTO) and outcome of the ADR, and drug dechallenge and rechallenge) and (2) perform impact analysis (nature, seriousness, unexpectedness, and outcome of the ADR).Results: The cases in the FPVD were significantly more informative than posts in forums for patient description (age, sex), treatment description (dose, duration, TTO), and outcome of the ADR, but the indication for the treatment was more often found in forums. Cases were more often serious in the FPVD than in forums (46% vs. 4%), but forums more often contained an unexpected ADR than the FPVD (24% vs. 17%). Moreover, 197 unexpected ADRs identified in forums were absent from the FPVD and the distribution of the MedDRA System Organ Classes (SOCs) was different between the two data sources.Discussion: This study is the first to evaluate if patients’ posts may qualify as potential and informative case reports that should be stored in a pharmacovigilance database in the same way as case reports submitted by health professionals. The posts were less informative (except for the indication) and focused on less serious ADRs than the FPVD cases, but more unexpected ADRs were presented in forums than in the FPVD and their SOCs were different. Thus, web forums should be considered as a secondary, but complementary source for pharmacovigilance

Phenome-Wide Association Studies on a Quantitative Trait: Application to TPMT Enzyme Activity and Thiopurine Therapy in Pharmacogenomics

International audiencePhenome-Wide Association Studies (PheWAS) investigate whether genetic polymorphisms associated with a phenotype are also associated with other diagnoses. In this study, we have developed new methods to perform a PheWAS based on ICD-10 codes and biological test results, and to use a quantitative trait as the selection criterion. We tested our approach on thiopurine S-methyltransferase (TPMT) activity in patients treated by thiopurine drugs. We developed 2 aggregation methods for the ICD-10 codes: an ICD-10 hierarchy and a mapping to existing ICD-9-CM based PheWAS codes. Eleven biological test results were also analyzed using discretization algorithms. We applied these methods in patients having a TPMT activity assessment from the clinical data warehouse of a French academic hospital between January 2000 and July 2013. Data after initiation of thiopurine treatment were analyzed and patient groups were compared according to their TPMT activity level. A total of 442 patient records were analyzed representing 10,252 ICD-10 codes and 72,711 biological test results. The results from the ICD-9-CM based PheWAS codes and ICD-10 hierarchy codes were concordant. Cross-validation with the biological test results allowed us to validate the ICD phenotypes. Iron-deficiency anemia and diabetes mellitus were associated with a very high TPMT activity (p = 0.0004 and p = 0.0015, respectively). We describe here an original method to perform PheWAS on a quantitative trait using both ICD-10 diagnosis codes and biological test results to identify associated phenotypes. In the field of pharmacogenomics, PheWAS allow for the identification of new subgroups of patients who require personalized clinical and therapeutic management

Computerized CHA2DS2Vasc classification in remote atrial fibrillation alerts: an ontology-based approach

International audienceIntroduction: Atrial fibrillation (AF) notifications in remote monitoring represent a high medical burden in terms of alert management. In the AKENATON project (Automated Knowledge Extraction from medical records iN Association with a Telecardiolgy Observation Network), we developed a method based on the integration of clinical information with data transmitted by implantable cardiac devices for clinical decision support purposes.Methods: Patient (pt) data were extracted from available textual or structured documents by an information extraction tool, and integrated with data extracted from device memories into a specific data model. An ontology (knowledge model) offering reasoning capabilities based on this data model was used to classify AF alerts. The thrombo-embolic risk (Low (L)/Medium (M)/High (H)/Critical (C)) based on CHA2DS2VASc score, medication and AF episode duration (Figure 1) was estimated by the system for 60 pts and compared to manual review by a domain expert. Results: At the level of the CHA2DS2VASc calculation (8 criteria per pt), 446 out of the 480 criteria to be estimated by the system were correct, resulting in 58 (97\%) pts with correct CHA2DS2VASc score classification (0/1/2+). Medication was adequately evaluated in 57 (95\%) pts. The final alert classification (11 L, 13 M, 31 H and 5 C) was correct for all pts minus one case of risk over-estimation (C instead of H).Conclusion: This work proves the ability of the system to better classify alerts and improve alert response based on clinical data. Such method could be of great use for remote monitoring and extended to other use cases and domains

Descriptions of Adverse Drug Reactions are Less Informative in Forums than in the French Pharmacovigilance Database but Provide More Unexpected Reactions

International audienceBackground: In the past years, social media have drawn attention for their potential use in Pharmacovigilance. Recent work showed that it is possible to extract adverse drug reactions (ADRs) in users’ posts on social media. The main objective of the Vigi4MED project is to evaluate the relevance and quality of the information shared by patients on web forums about drug safety, and its potential usefulness for pharmacovigilance.Methods: After selecting websites of interest, we manually evaluated the relevance of posts’ content for pharmacovigilance related to 6 drugs (agomelatine, baclofen, duloxetine, exenatide, strontium ranelate and tetrazepam). We compared forums to the French pharmacovigilance database (FPVD) in order to (1) evaluate if they contained relevant information to characterize a pharmacovigilance case report (patient's age and sex; treatment indication, dose and duration; time-to-onset (TTO) and outcome of ADR) and (2) patients’ age and sex; ADRs’ nature, seriousness, unexpectedness and outcome; drug dechallenge and rechallenge.Results: The cases in the FPVD were significantly more informative than the posts in forums for patient description (age, sex), treatment description (dose, duration, TTO) and the outcome of the ADR, but indication of the treatment was more often found in forums. Cases were more often serious in the FPVD than in forums (46% vs 4%) but contained more often an unexpected ADR in forums than in the FPVD (24% vs 17%). Moreover, 197 unexpected ADRs identified in forums were absent from the FPVD and the distribution of the MedDRA System Organ Classes (SOCs) was different between both data sources.Discussion: To our knowledge, this study is the first to evaluate how patients’ posts may qualify as potential and informative case reports to support the pharmacovigilance classical workflow compared to case reports in a pharmacovigilance database. The posts were less informative (except for the indication) and focused on less serious ADRs than the FPVD’s cases, but we found more unexpected ADRs in forums than in the FPVD and their SOCs were different. Thus, web forums should be considered as a secondary but complementary source for pharmacovigilance

Adverse Drug Reaction Identification and Extraction in Social Media: A Scoping Review

International audienceBackground: The underreporting of adverse drug reactions (ADRs) through traditional reporting channels is a limitation in the efficiency of the current pharmacovigilance system. Patients' experiences with drugs that they report on social media represent a new source of data that may have some value in postmarketing safety surveillance.Objective: A scoping review was undertaken to explore the breadth of evidence about the use of social media as a new source of knowledge for pharmacovigilance.Methods: Daubt et al's recommendations for scoping reviews were followed. The research questions were as follows: How can social media be used as a data source for postmarketing drug surveillance? What are the available methods for extracting data? What are the different ways to use these data? We queried PubMed, Embase, and Google Scholar to extract relevant articles that were published before June 2014 and with no lower date limit. Two pairs of reviewers independently screened the selected studies and proposed two themes of review: manual ADR identification (theme 1) and automated ADR extraction from social media (theme 2). Descriptive characteristics were collected from the publications to create a database for themes 1 and 2.Results: Of the 1032 citations from PubMed and Embase, 11 were relevant to the research question. An additional 13 citations were added after further research on the Internet and in reference lists. Themes 1 and 2 explored 11 and 13 articles, respectively. Ways of approaching the use of social media as a pharmacovigilance data source were identified.Conclusions: This scoping review noted multiple methods for identifying target data, extracting them, and evaluating the quality of medical information from social media. It also showed some remaining gaps in the field. Studies related to the identification theme usually failed to accurately assess the completeness, quality, and reliability of the data that were analyzed from social media. Regarding extraction, no study proposed a generic approach to easily adding a new site or data source. Additional studies are required to precisely determine the role of social media in the pharmacovigilance system

Personalized and automated remote monitoring of atrial fibrillation

International audienceAIMS: Remote monitoring of cardiac implantable electronic devices is a growing standard; yet, remote follow-up and management of alerts represents a time-consuming task for physicians or trained staff. This study evaluates an automatic mechanism based on artificial intelligence tools to filter atrial fibrillation (AF) alerts based on their medical significance.METHODS AND RESULTS: We evaluated this method on alerts for AF episodes that occurred in 60 pacemaker recipients. AKENATON prototype workflow includes two steps: natural language-processing algorithms abstract the patient health record to a digital version, then a knowledge-based algorithm based on an applied formal ontology allows to calculate the CHA2DS2-VASc score and evaluate the anticoagulation status of the patient. Each alert is then automatically classified by importance from low to critical, by mimicking medical reasoning. Final classification was compared with human expert analysis by two physicians. A total of 1783 alerts about AF episode \textgreater5 min in 60 patients were processed. A 1749 of 1783 alerts (98%) were adequately classified and there were no underestimation of alert importance in the remaining 34 misclassified alerts.CONCLUSION: This work demonstrates the ability of a pilot system to classify alerts and improves personalized remote monitoring of patients. In particular, our method allows integration of patient medical history with device alert notifications, which is useful both from medical and resource-management perspectives. The system was able to automatically classify the importance of 1783 AF alerts in 60 patients, which resulted in an 84% reduction in notification workload, while preserving patient safet

Remote Monitoring of Cardiac Implantable Devices: Ontology Driven Classification of the Alerts

International audienceThe number of patients that benefit from remote monitoring of cardiac implantable electronic devices, such as pacemakers and defibrillators, is growing rapidly. Consequently, the huge number of alerts that are generated and transmitted to the physicians represents a challenge to handle. We have developed a system based on a formal ontology that integrates the alert information and the patient data extracted from the electronic health record in order to better classify the importance of alerts. A pilot study was conducted on atrial fibrillation alerts. We show some examples of alert processing. The results suggest that this approach has the potential to significantly reduce the alert burden in telecardiology. The methods may be extended to other types of connected device