Pharmacoepidemiology and Drug Safety最新文献

Background: Routinely collected electronic health records (EHR) offer a valuable opportunity to carry out research on immunization uptake, effectiveness, and safety, using large and representative samples of the population. In contrast to other drugs, vaccines do not require electronic prescription in many settings, which may lead to ambiguous coding of vaccination status and timing.

Methodology: We propose a comprehensive algorithm to identifying childhood immunizations in routinely collected EHR. In order to deal with ambiguous coding, over-recording, and backdating in EHR, we suggest an approach combining a wide range of medical codes in combination to identify vaccination events and using appropriate wash-out periods and quality checks. We illustrate this approach on a cohort of children born between 2006 and 2014 followed up to the age of five in the Clinical Practice Research Datalink (CPRD) Aurum, a UK primary care dataset of EHR, and validate the results against national estimates of vaccine coverage by NHS Digital and Public Health England.

Results: Our algorithm reproduced estimates of vaccination coverage, which are comparable to official national estimates and allows to approximate the age at vaccination. Electronic prescription data only do not cover vaccination events sufficiently.

Conclusion: Our new proposed method could be used to provide a more accurate estimation of vaccination coverage and timing of vaccination for researchers and policymakers using EHR. As with all observational research using real-world data, it is important that researchers understand the context of the used dataset used and the clinical practice of recording.

Purpose: This study aimed to investigate the prescription of beta-blockers (β-blockers) for patients with asthma.

Methods: In this retrospective cross-sectional study using the National Patient Sample (NPS) of the Health Insurance Review and Assessment Service (HIRA) of South Korea, β-blockers and asthma medications were investigated using generic name codes provided by HIRA. Concomitant administration was identified when a β-blocker and an asthma medication were co-prescribed in one billing statement or when separate β-blocker and asthma prescriptions had overlapping dates of use.

Results: In the 1027 patients with asthma who were prescribed non-selective β-blockers (non-SBs), 3087 non-SB prescriptions were identified, of which 62.3% and 37.3% were for carvedilol and propranolol, respectively. Of the 906 patients with asthma prescribed selective β-blockers (SBs), 2942 SB prescriptions were identified, of which 48.5%, 28.3%, and 20.3% were for bisoprolol, atenolol, and nebivolol, respectively. Overall, 2149 non-SB and 2124 SB prescriptions with overlapping use dates with asthma medications were identified, which were prescribed to 726 and 657 patients, accounting for 70.7% and 72.5% of the patients receiving non-SBs and SBs, respectively. β2-agonists accounted for 39.9% of the concomitant asthma medications with overlapping dates of use with non-SBs. Co-prescribing of bronchodilators occurred at a rate of 38.7% and 45.1% for the 3087 non-SB prescriptions and 2942 SB prescriptions, respectively.

Conclusions: Carvedilol and propranolol accounted for half of all β-blockers prescribed to asthma patients. Prescribing β-blockers to patients with asthma requires caution to prevent exacerbation of asthma and drug interactions between β-blockers and co-prescribed asthma medications.

Purpose: Paxlovid is effective in reducing COVID-19 hospitalization and mortality. This study characterized Paxlovid use and evaluated racial/ethnic disparities over time among community-dwelling adults at high risk of progression to severe COVID-19 disease.

Methods: This retrospective cohort study used the National COVID Cohort Collaborative (N3C) data and included individuals aged 18 years or older diagnosed with COVID-19 between January 2022 and December 2023. The study cohort included nonhospitalized individuals who were at high risk of COVID-19 progression, and selected the first COVID-19 episode in each quarter, including reinfection episodes. Paxlovid use was defined as receiving Paxlovid within ±5 days of a COVID-19 diagnosis. We used descriptive statistics to characterize Paxlovid use overall and by calendar quarter and race/ethnicity. We used a generalized estimating equations (GEE) models to quantify the association of race/ethnicity with Paxlovid use controlling for age, gender, and clinical characteristics.

Results: Among 1 264 215 individuals at high risk of disease progression (1 404 607 episodes), Paxlovid use increased from 1.2% in January-March 2022 to 35.1% in October-December 2023. Paxlovid use was more common among non-Hispanic White individuals (23.9%) than non-Hispanic Black (16.5%) and Latinx/e (16.7%) patients. After adjusting age, gender, and clinical characteristics, Paxlovid use was less likely among non-Hispanic Black (odds ratio [OR] 0.69, 95% confidence interval [CI] 0.68-0.70) and Latinx/e (OR 0.72, CI 0.71-0.73) patients than non-Hispanic White patients.

Conclusions: Among a large, diverse cohort of community-dwelling individuals with COVID-19, nearly two out of three eligible individuals did not receive Paxlovid, and minoritized racial/ethnic groups were less likely to use Paxlovid than their non-Hispanic White individuals.

Purpose: Pain is a common symptom following proximal femoral fractures (PFF), however, information on its treatment in terms of agents and type of use (scheduled vs. pro re nata [PRN]) is scarce. The main objective of this study was to examine pain medication regimens according to pain intensity following PFF. Furthermore, we explored the utilization of medication plans.

Methods: The "ProFem"-study on healthcare provision, functional ability, and quality of life after PFF is a German population-based prospective cohort study based on statutory health insurance data and individually linked survey data from different time points including information on the currently used medication. This present analysis refers to the participants' baseline interviews (about 3 months following PFF) conducted from 2018 to 2019 in the participants' private surroundings.

Results: The study population comprised 444 participants (mean age: 81.2 years, 71.0% female). Half of them reported high intensity pain, and the mean value for the EuroQol visual analogue scale was 50.8. Most commonly used analgesics were metamizole and tilidine/naloxone. Among participants with high intensity pain, 21.9% received only PRN pain medication and 17.2% no pain medication at all. Overall, 61.5% of participants presented any (printed) medication plan and only 25.2% a "federal standardized medication plan" (BMP).

Conclusion: As a substantial number of patients reports high intensity pain about 3 months following a PFF, the large proportion of those receiving no or only PRN pain medication raises questions regarding the appropriateness of the therapy. The overall low utilization of the BMP indicates potential for improvement.

Purpose: Bleeding is an important health outcome of interest in epidemiological studies. We aimed to develop and validate rule-based algorithms to identify (1) major bleeding and (2) all clinically relevant bleeding (CRB) (composite of major and all clinically relevant nonmajor bleeding) within real-world electronic healthcare data.

Methods: We took a random sample (n = 1630) of inpatient admissions to Singapore public healthcare institutions in 2019 and 2020, stratifying by hospital and year. We included patients of all age groups, sex, and ethnicities. Presence of major bleeding and CRB were ascertained by two annotators through chart review. A total of 630 and 1000 records were used for algorithm development and validation, respectively. We formulated two algorithms: sensitivity- and positive predictive value (PPV)-optimized algorithms. A combination of hemoglobin test patterns and diagnosis codes were used in the final algorithms.

Results: During validation, diagnosis codes alone yielded low sensitivities for major bleeding (0.16) and CRB (0.24), although specificities and PPV were high (>0.97). For major bleeding, the sensitivity-optimized algorithm had much higher sensitivity and negative predictive values (NPVs) (sensitivity = 0.94, NPV = 1.00), however false positive rates were also relatively high (specificity = 0.90, PPV = 0.34). PPV-optimized algorithm had improved specificity and PPV (specificity = 0.96, PPV = 0.52), with little reduction in sensitivity and NPV (sensitivity = 0.88, NPV = 0.99). For CRB events, our algorithms had lower sensitivities (0.50-0.56).

Conclusions: The use of diagnosis codes alone misses many genuine major bleeding events. We have developed major bleeding algorithms with high sensitivities, which can ascertain events within populations of interest.

Purpose: Metadata for data dIscoverability aNd study rEplicability in obseRVAtional studies (MINERVA), a European Medicines Agency-funded project (EUPAS39322), defined a set of metadata to describe real-world data sources (RWDSs) and piloted metadata collection in a prototype catalogue to assist investigators from data source discoverability through study conduct.

Methods: A list of metadata was created from a review of existing metadata catalogues and recommendations, structured interviews, a stakeholder survey, and a technical workshop. The prototype was designed to comply with the FAIR principles (findable, accessible, interoperable, reusable), using MOLGENIS software. Metadata collection was piloted by 15 data access partners (DAPs) from across Europe.

Results: A total of 442 metadata variables were defined in six domains: institutions (organizations connected to a data source); data banks (data collections sustained by an organization); data sources (collections of linkable data banks covering a common underlying population); studies; networks (of institutions); and common data models (CDMs). A total of 26 institutions were recorded in the prototype. Each DAP populated the metadata of one data source and its selected data banks. The number of data banks varied by data source; the most common data banks were hospital administrative records and pharmacy dispensation records (10 data sources each). Quantitative metadata were successfully extracted from three data sources conforming to different CDMs and entered into the prototype.

Conclusions: A metadata list was finalized, a prototype was successfully populated, and a good practice guide was developed. Setting up and maintaining a metadata catalogue on RWDSs will require substantial effort to support discoverability of data sources and reproducibility of studies in Europe.

Background: Reports of adverse menstrual events emerged during the COVID-19 vaccination campaign in multiple countries. This raised the question whether these reports were caused by the vaccines. The aim of this systematic review was to evaluate comparative studies on this topic (registered at PROSPERO [CRD42022324973]).

Methods: We included observational studies such as cohort studies and surveys comparing the response to self-reported questionnaires between post- versus pre-vaccination data. PubMed and Cochrane Library searches were conducted on 1 September 2023. The primary outcome was the incidence of any prespecified adverse menstrual event, and the outcome measure was the risk ratio. The meta-analysis was conducted by using the Mantel-Haenszel method and the random effects model. We summarized the results on risk factors as well as key findings of the studies included.

Results: We retrieved 161 references from electronic databases and additional sources such as references lists. Of those, we considered 21 comparative observational studies. The meta-analysis of any adverse menstrual adverse event reported in 12 studies resulted in a pooled estimate (risk ratio 1.13; 95% CI, 0.96-1.31) that did not favor any group. The analysis was constrained by considerable clinical and statistical heterogeneity. Risk factors for self-reported menstrual changes included a history of COVID-19 infection, the concern about COVID-19 vaccines, smoking, previous cycle irregularities, depression, and stress, and other issues.

Conclusions: The risk ratio did not favor any group and heterogeneity was prevalent among the studies. Most studies suggested that the reported changes were temporary, minor, and nonserious.

Purpose: The purpose of this study is to evaluate the pattern, appropriateness, and cost of antidiabetic drugs prescribed for patients with Type 2 diabetes at primary healthcare facilities (PHFs) in China.

Methods: We collected outpatient-visit prescriptions from 363 PHFs in 31 cities covering eastern, central, and western regions of China. The visits of adult patients with Type 2 diabetes diagnosis were collected and classified the antidiabetic medication pattern of each patient use as recommended or non-recommended according to Chinese guidelines. We then calculated the proportion of guideline-recommended patterns and the average monthly cost for each pattern, overall and by region.

Results: Of 33 519 prescriptions for Type 2 diabetes, most (73.9%) were for guideline-recommended antidiabetic treatments. The proportion of guideline-recommended prescriptions varied by region (eastern [75.9%], central [87.5%], and western [59.7%]). Metformin monotherapy was the most common guideline-recommended treatment in all three regions (eastern [20.1%], central [28.0%], and western [24.6%]). The most common non-guideline-recommended treatments were monotherapy of insulin (eastern [16.5%], central [5.1%], and western [25.7%]) and traditional Chinese antidiabetic medicines (eastern [5.6%], central [5.7%], and western [11.1%]). The average monthly costs were lower for guideline-recommended treatments compared to non-recommended treatments in all regions (eastern [13.6 ± 15.4 USD vs. 28.1 ± 22.0 USD], central [9.8 ± 10.9 USD vs. 28.7 ± 19.4 USD], and western [17.9 ± 21.4 USD vs. 30.3 ± 23.6 USD]).

Conclusions: The majority of patients with Type 2 diabetes received guideline-recommended antidiabetic medications at PHFs in China, with only half of the prescriptions containing guideline-recommended metformin. Utilization of guideline-recommended therapies differed across regions. Tailored interventions to promote evidence-based antidiabetic prescribing are urgently needed, especially in the undeveloped western region.

Purpose: We investigated time trends in validation performance characteristics for six sources of death data available within the Healthcare Integrated Research Database (HIRD) over 8 years.

Methods: We conducted a secondary analysis of a cohort of advanced cancer patients with linked National Death Index (NDI) data identified in the HIRD between 2010 and 2018. We calculated sensitivity, specificity, positive predictive value, and negative predictive value for six sources of death status data and an algorithm combining data from available sources using NDI data as the reference standard. Measures were calculated for each year of the study including all members in the cohort for at least 1 day in that year.

Results: We identified 27 396 deaths from any source among 40 692 cohort members. Between 2010 and 2018, the sensitivity of the Death Master File (DMF) decreased from 0.77 (95% CI = 0.76, 0.79) to 0.12 (95% CI = 0.11, 0.14). In contrast, the sensitivity of online obituary data increased from 0.43 (95% CI = 0.41, 0.45) in 2012 to 0.71 (95% CI = 0.68, 0.73) in 2018. The sensitivity of the composite algorithm remained above 0.83 throughout the study period. PPV was observed to be high from 2010 to 2016 and decrease thereafter for all sources. Specificity and NPV remained at high levels throughout the study.

Conclusions: We observed that the sensitivity of mortality data sources compared with the NDI could change substantially between 2010 and 2018. Other validation characteristics were less variable. Combining multiple sources of mortality data may be necessary to achieve adequate performance particularly for multiyear studies.