Pharmacoepidemiology and drug safety
-
Pharmacoepidemiol Drug Saf · Aug 2019
ReviewBarriers towards effective pharmacovigilance systems of biosimilars in rheumatology: A Latin American survey.
This review summarises the current status of regulatory guidelines for the approval of biosimilars in Latin America and highlights the main barriers to effective pharmacovigilance in this region. We also report results from a survey of Latin American rheumatologists assessing their understanding of prescribing biosimilars and the pharmacovigilance of these drugs. ⋯ The main barriers to effective pharmacovigilance in Latin America are the lack of consensus on the interchangeability of reference biologics and biosimilars, and the need for more suitably trained personnel to carry out effective postmarketing pharmacovigilance of biosimilars. Inconsistencies in biosimilar nomenclature make it difficult to adequately trace drugs and record adverse drug reactions associated with their use, creating a barrier to the global pharmacovigilance of biologics.
-
Pharmacoepidemiol Drug Saf · Aug 2019
A simulation study of the statistical power and signaling characteristics of an early season sequential test for influenza vaccine safety.
The US Food and Drug Administration monitors the risk of Guillain-Barré syndrome (GBS) following influenza vaccination using several data sources including Medicare. In the 2017 to 2018 season, we transitioned our near real-time surveillance in Medicare to more effectively detect large GBS risk increases early in the season while avoiding false positives. ⋯ On the basis of the results from this simulation and subsequent consultations with experts and stakeholders, we specified USPRT to test continuously from weeks 7 to 11 using the null hypothesis that the observed GBS rate was 2.5× the historical rate. This helped improve the ability of USPRT to provide early detection of GBS risk following influenza vaccination as part of a multilayered system of surveillance.
-
Pharmacoepidemiol Drug Saf · Aug 2019
Using natural language processing of clinical text to enhance identification of opioid-related overdoses in electronic health records data.
To enhance automated methods for accurately identifying opioid-related overdoses and classifying types of overdose using electronic health record (EHR) databases. ⋯ Methods that process text clinical notes show promise for improving accuracy and fidelity at identifying and classifying overdoses according to type using EHR data.