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1.
Pharmacoepidemiol Drug Saf ; 28(10): 1309-1317, 2019 10.
Artigo em Inglês | MEDLINE | ID: mdl-31392844

RESUMO

PURPOSE: Adverse event (AE) identification in social media (SM) can be performed using various types of natural language processing (NLP) and machine learning (ML). These methods can be categorized by complexity and precision level. Co-occurrence-based ML methods are rather basic, as they identify simultaneous appearance of drugs and clinical events in a single post. In contrast, statistical learning methods involve more complex NLP and identify drugs, events, and associations between them. We aimed to compare the ability of co-occurrence and NLP to identify AEs and signals of disproportionate reporting (SDR) in patient-generated SM. We also examined the performance of lift in SM-based signal detection (SD). METHODS: Our examination was performed in a corpus of SM posts crawled from open online patient forums and communities, using the spontaneously reported VigiBase data as reference data set. RESULTS: We found that co-occurrence and NLP produce AEs, which are 57% and 93% consistent with VigiBase AEs, respectively. Among the SDRs identified both in SM and in VigiBase, up to 55.3% were identified earlier in co-occurrence, and up to 32.1% were identified earlier in NLP-processed SM. Using lift in SM SD provided performance similar to frequentist methods, both in co-occurrence and in NLP-processed AEs. CONCLUSION: Our results indicate that using SM as a data source complementary to traditional pharmacovigilance sources should be considered further. Various levels of SM processing may be considered, depending on the preferred policies and tolerance for false-positive to false-negative balance in routine pharmacovigilance processes.


Assuntos
Coleta de Dados/métodos , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/epidemiologia , Processamento de Linguagem Natural , Farmacovigilância , Mídias Sociais/estatística & dados numéricos , Sistemas de Notificação de Reações Adversas a Medicamentos/estatística & dados numéricos , Conjuntos de Dados como Assunto , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/diagnóstico , Reações Falso-Negativas , Reações Falso-Positivas , Estudos de Viabilidade , Estudos Retrospectivos , Sensibilidade e Especificidade
2.
Curr Med Res Opin ; 38(3): 461-468, 2022 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-34931552

RESUMO

OBJECTIVE: Since 2014, valproate has not been recommended for use in girls and women of childbearing potential unless other treatments are ineffective or not tolerated. Risk minimization measures (RMMs) of valproate were implemented to reduce the potential risks of developmental disorders among pregnant women. A drug utilization study was carried out to assess the effectiveness of RMMs. METHODS: This was a multinational, non-interventional cohort study. For the UK, existing data from the Clinical Practice Research Datalink database were used. The primary study endpoint was a change in the proportion of valproate initiations preceded by other medications relevant for valproate indications before and after implementation of RMMs. RESULTS: The proportion of valproate initiations preceded by medications related to valproate indications increased after RMM implementation in incident female users in the UK from 66.4% to 72.4%. The proportion of incident prescriptions for epilepsy and bipolar disorder with prior medication related to valproate indications increased, from 36.2% to 44.1% and 72.9% to 77.8%, respectively. The incidence rate of valproate-exposed pregnancies decreased from 16.9 to 10.9 per 1000 person-years in the pre- and post-implementation periods, respectively. CONCLUSIONS: Results from this study indicated some improvement in physician prescribing and a potential reduction in valproate-exposed pregnancies in the UK. Given only modest improvement has been achieved, additional RMMs were implemented in 2018.


Assuntos
Uso de Medicamentos , Ácido Valproico , Anticonvulsivantes/efeitos adversos , Estudos de Coortes , Europa (Continente) , Feminino , Humanos , Masculino , Gravidez , Reino Unido , Ácido Valproico/efeitos adversos
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