Ondansetron use in nausea and vomiting during pregnancy:A descriptive analysis of prescription patterns and patient characteristics in UK general practice

AIMS: The objective of this study was to describe ondansetron drug utilization patterns during pregnancy to treat nausea and vomiting in pregnancy (NVP). Moreover, we aimed to describe the maternal factors associated with NVP and antiemetic use. METHODS: The data consist of pregnancies with a live birth(s) within an IMRD‐UK registered GP practice. Descriptive statistics were used to investigate patterns of ondansetron use in pregnancy and to describe maternal characteristics associated with NVP and antiemetic drug utilization. We differentiate first‐ from second‐line use during pregnancy using antiemetic prescription pathways. RESULTS: The dataset included 733 633 recorded complete pregnancies from 2005 to 2019. NVP diagnosis and ondansetron prescription prevalence increased from 2.7% and 0.1% in 2005 to 4.8% and 2.5% in 2019 respectively. Over the period 2015–2019, the most common oral daily dosages were 4 mg/d (8.5%), 8 mg/d (37.1%), 12 mg/d (37.5%) and between 16 and 24 mg/d (16.9%). Prescription of ondansetron was initiated during the first trimester of pregnancy in 40% of the cases and was moderately used as a first‐line therapy (2.8%), but preferred choice of second‐line therapy. Women with mental health disorders, asthma and/or prescribed folic acid were more likely to experience NVP and use antiemetics in pregnancy than their counterparts. CONCLUSION: This study confirms that ondansetron is increasingly used off‐label to treat NVP during pregnancy, also in the first trimester and before other prescription antiemetics have been prescribed. Several maternal comorbidities and folic acid use were more common among women experiencing NVP and using antiemetics, including ondansetron

Lessons Learned on Observed-to-Expected Analysis Using Spontaneous Reports During Mass Vaccination

During the COVID-19 vaccination campaign, observed-to-expected analysis was used by the European Medicines Agency to contextualise data from spontaneous reports to generate real-time evidence on emerging safety concerns that may impact the benefit-risk profile of COVID-19 vaccines. Observed-to-expected analysis compares the number of cases spontaneously reported for an event of interest after vaccination (‘observed’) to the ‘expected’ number of cases anticipated to occur in the same number of individuals had they not been vaccinated. Observed-to-expected analysis is a robust methodology that relies on several assumptions that have been described in regulatory guidelines and scientific literature. The use of observed-to-expected analysis to support the safety monitoring of COVID-19 vaccines has provided valuable insights and lessons on its design and interpretability, which could prove to be beneficial in future analyses. When undertaking an observed-to-expected analysis within the context of safety monitoring, several aspects need attention. In particular, we emphasise the importance of stratified and harmonised data collection both for vaccine exposure and spontaneous reporting data, the need for alignment between coding dictionaries and the crucial role of accurate background incidence rates for adverse events of special interest. While these considerations and recommendations were determined in the context of the COVID-19 mass vaccination setting, they are generalisable in principle.</p

Создание монумента «Возрождение крымскотатарского народа» как культурное явление в жизни крымского общества

В статье автором охарактеризован градостроительный объект Монумент «Возрождение крымскотатарского народа» как культурное явление в жизни крымского общества, призванное внести вклад в процесс воспитания духовности и культуры в молодых людях.У статті автором охарактеризовано містобудівельний об’єкт Монумент «Відродження кримськотатарського народу» як культурне явище у житті кримського суспільства, що призвание донести внесок у процес виховання духовності та культури молоді.The author describes a monument „Rebirth of the Crimean Tatars” as a cultural phenomenon in the life of the Crimean society, which can contribute in the process of spiritual and cultural upbringing of young people

The Reporting of a Disproportionality Analysis for Drug Safety Signal Detection Using Individual Case Safety Reports in PharmacoVigilance (READUS-PV): Development and Statement

Background and aim: Disproportionality analyses using reports of suspected adverse drug reactions are the most commonly used quantitative methods for detecting safety signals in pharmacovigilance. However, their methods and results are generally poorly reported in published articles and existing guidelines do not capture the specific features of disproportionality analyses. We here describe the development of a guideline (REporting of A Disproportionality analysis for drUg Safety signal detection using individual case safety reports in PharmacoVigilance [READUS-PV]) for reporting the results of disproportionality analyses in articles and abstracts. Methods: We established a group of 34 international experts from universities, the pharmaceutical industry, and regulatory agencies, with expertise in pharmacovigilance, disproportionality analyses, and assessment of safety signals. We followed a three-step process to develop the checklist: (1) an open-text survey to generate a first list of items; (2) an online Delphi method to select and rephrase the most important items; (3) a final online consensus meeting. Results: Among the panel members, 33 experts responded to round 1 and 30 to round 2 of the Delphi and 25 participated to the consensus meeting. Overall, 60 recommendations for the main body of the manuscript and 13 recommendations for the abstracts were retained by participants after the Delphi method. After merging of some items together and the online consensus meeting, the READUS-PV guidelines comprise a checklist of 32 recommendations, in 14 items, for the reporting of disproportionality analyses in the main body text and four items, comprising 12 recommendations, for abstracts. Conclusions: The READUS-PV guidelines will support authors, editors, peer-reviewers, and users of disproportionality analyses using individual case safety report databases. Adopting these guidelines will lead to more transparent, comprehensive, and accurate reporting and interpretation of disproportionality analyses, facilitating the integration with other sources of evidence

The REporting of A Disproportionality Analysis for DrUg Safety Signal Detection Using Individual Case Safety Reports in PharmacoVigilance (READUS-PV): Explanation and Elaboration

In pharmacovigilance, disproportionality analyses based on individual case safety reports are widely used to detect safety signals. Unfortunately, publishing disproportionality analyses lacks specific guidelines, often leading to incomplete and ambiguous reporting, and carries the risk of incorrect conclusions when data are not placed in the correct context. The REporting of A Disproportionality analysis for drUg Safety signal detection using individual case safety reports in PharmacoVigilance (READUS-PV) statement was developed to address this issue by promoting transparent and comprehensive reporting of disproportionality studies. While the statement paper explains in greater detail the procedure followed to develop these guidelines, with this explanation paper we present the 14 items retained for READUS-PV guidelines, together with an in-depth explanation of their rationale and bullet points to illustrate their practical implementation. Our primary objective is to foster the adoption of the READUS-PV guidelines among authors, editors, peer reviewers, and readers of disproportionality analyses. Enhancing transparency, completeness, and accuracy of reporting, as well as proper interpretation of their results, READUS-PV guidelines will ultimately facilitate evidence-based decision making in pharmacovigilance

Case-only designs for studying the association of antidepressants and hip or femur fracture.

The purpose of this study is to evaluate the performance and validity of the case-crossover (CCO) and self-controlled case-series (SCCS) designs when studying the association between hip/femur fracture (HF) and antidepressant (AD) use in general practitioner databases. In addition, comparability with cohort and case-control designs is discussed. Adult patients with HF and who received an AD prescription during 2001-2009 were identified from UK's The Health Improvement Network (THIN) and the Dutch Mondriaan databases. AD exposure was classified into current, recent and past/non-use (reference). In the CCO, for each patient, a case moment (date of HF) and four prior control moments at -91, -182, -273 and -365 days were defined. In SCCS, incidence of HF was compared between exposure states. Conditional logistic regression was used in the CCO and Poisson regression in the SCCS to compute odds ratios and incidence rate ratios, respectively. In CCO, we adjusted for time-varying co-medication and in SCCS for age. Adjusted estimates for the effect of current AD exposure on HF were higher in the CCO (co-medication-adjusted odds ratio, THIN: 2.24, 95% confidence interval [CI]: 2.04-2.47; Mondriaan: 2.57, 95%CI [1.50, 4.43]) than in the SCCS (age-adjusted incidence rate ratio, THIN: 1.41, 95%CI [1.32, 1.49]; Mondriaan: 2.14, 95%CI [1.51, 3.03]). The latter were comparable with the traditional designs. Case-only designs confirmed the association between AD and HF. The CCO design violated assumptions in this study with regard to exchangeability and length of exposure, and transient effects on outcome. The SCCS seems to be an appropriate design for assessing AD-HF association. Copyright © 2016 John Wiley &amp; Sons, Ltd

No impact of adjusting for lifestyle factors or general practice on risk estimates for the association between antidepressants and hip/femur fracture

Background: Routinely collected data from electronic health record databases often lack information on relevant risk factors, like lifestyle-factors (LSF, smoking, alcohol use, body mass index) or socioeconomic factors that may be needed for confounder adjustment in epidemiogical studies. Objectives: In the context of the Pharmacoepidemiological Research on Outcomes of Therapeutics by a European Consortium (PROTECT) project, the impact of confounder adjustment on the risk of antidepressant (AD) use on hip/femur fracture (HF) and compared results across three primary care databases was assessed. Methods: We conducted a case-control study nested within 3 new AD user cohorts of adult patients (2001-2009) in three databases (Spanish BIFAP, Dutch Mondriaan and UK THIN. Cases were defined as a first HF during the study period. Up to 4 controls were matched by sex, age (+/-2 years) and time since cohort entry (+/- 6 months). Exposure to AD was classified into current, recent and past use. We adjusted for comedication and comorbidities, using same models for all data sources. The impact of matching on practice (marker for socioeconomic factors) and additional adjustment for LSF was done in THIN. Odds ratios (OR) were estimated using conditional logistic regression analysis. Results: Current use of AD was associated with an significantly increased risk of HF in all data sources. Adjusted ORs were 1.52 in BIFAP (1535 cases), 1.59 in THIN (3756 cases) and 3.32 in Mondriaan (79 cases). In BIFAP/THIN, adjustment resulted i

Impact of varying control moment selection in a case-crossover (CCO) study on antidepressant drug (AD) use and hip/femur fracture (HFF) in protect

Background: The CCO design is appealing because it eliminates time-invariant person related confounding. A prerequisite is that exposure in real life drug use is sufficiently transient to allow for independence of exposure states. The impact of variation in time of control moment selection is relatively unknown. Objectives: To assess the influence of selection of control moments at different times in a CCO study of AD and HFF on variation in effect estimates. Methods: Adult patients with HFF who received an AD prescription during 2001-2009 were identified from the Dutch Mondriaan GP database. For each patient, a case moment (the date of HFF) and four control moments at 3, 6, 9, and 12 months before the HFF (M3, M6, M9, M12) were defined. Each AD prescription had a pre-defined duration of 90 days.AD treatment episodes were constructed and divided into current, recent (0-2 months following current use) and past use (>2months follow current use).We used conditional logistic regression to compute odds ratios (ORs) and 95% confidence intervals CI between AD use and HFF. Results: Pairwise (1:1) comparisons of 82 case moments to varied control moments for current versus no use resulted in ORs for HFF-M3 of 16.3 (95%CI: 2.2-123), M6: 7.8 (2.3-26), M9: 5.9 (2.1-16.1), and M12: 4.1 (1.8-9.4). Including all (1:4),M3-M12, resulted in OR 7.0 (3.2-15.2). For recent use even higher ORs were found; M3: 49.7 (3.9-637), M6: 17.6 (2.5-136), M9: 2.6 (0.7-9.5), M12: 3.7 (0.7-20), All 8.6 (2.7-27). Discordancy of exposure and thus number of strata contributing to the analyses increased from 32% in M3 to 50% in M12. Conclusions: Selection of control moments at different times in CCO has considerable impact on effect estimates in this particular setting. CCO studies should be designed with sufficient time between case and control moments to allow for sufficient discordancy in exposure to get reliable estimates