Pharmacoepidemiology and Drug Safety最新文献

Purpose: Accurate identification of non-melanoma skin cancer (NMSC) using ICD-10 claims-based algorithms is largely uncharacterized. This study aimed to develop and validate claim-based algorithms for NMSC.

Methods: Adult patients with psoriasis were identified in Optum Market Clarity between Oct 2015 and Dec 2020. Eligible patients had at least 1 year of claim enrollment prior to cohort entry, linked claims-EHRs, overlapping follow-up periods, and no prior malignancy. Data were randomly split into the development and validation datasets. Broad NMSC encompassed narrow NMSC (basal cell carcinoma, squamous cell carcinoma, sebaceous cell carcinoma, and malignant neoplasms of the sweat glands), Merkel cell carcinoma, carcinoma in situ, Kaposi sarcoma of skin, and cutaneous T-cell or B-cell lymphoma. The five developed claims-based algorithms consisted of 1+ diagnosis code (1) at any position; (2) at the primary position; (3) by a dermatologist; (4) at any position plus treatment procedure code; (5) at primary position plus treatment procedure code. NMSC cases and non-cases were adjudicated using EHR records. Algorithms performance measures were estimated.

Results: Of 25 647 patients (mean age 51.4 ± 15.2 years, female 53.6%), 321 broad and 281 narrow NMSC patients were identified in the development dataset (n = 12 824). Algorithm sensitivity was 89.9% (algorithm 1) and 81.9% (algorithm 2) but under 65% for algorithms 3-5 for broad NMSC. PPV ranged from 98.2% to 99.1%. Results were consistent in the validation dataset.

Conclusion: This study developed and validated high-performing ICD10-based algorithms for NMSC to facilitate future dermatology research using health data.

Introduction: The COVID-19 pandemic restricted healthcare access. Mental illness in combination with isolation and fear of the virus possibly decreased routine monitoring for lithium using patients during the lockdown. Our aim was to study if monitoring frequencies and serum level values for lithium, TSH (thyroid stimulating hormone), and renal function changed during the COVID-19 pandemic.

Methods: Using the PHARMO database (laboratory, pharmacy, and hospitalization data), we identified lithium users in The Netherlands over 2 years (14 October 2018-14 October 2020). The first year served as the control period; the second year was divided into pre-COVID, lockdown, and post-lockdown segments. A time series analysis with a linear regression model was performed to test for differences in monitoring frequency and aberrant serum levels at the beginning of the lockdown (immediate effect) and during the lockdown (post-lockdown trend, effect over 12 weeks).

Results: We identified 2835 patients using lithium. Monitoring measurements declined by 52% (7.74% vs. 4.01%) for lithium serum levels, 28% (5.56% vs. 4.20%) for TSH, and 26% (17.7% vs. 13.2%) for renal function in the first week of lockdown. These reductions were statistically significant compared to the control period. Monitoring for all measurements gradually recovered during lockdown. Changes in aberrant serum levels were not statistically different during the exposure and control periods.

Conclusion: Monitoring for lithium, TSH and renal function declined at the beginning of lockdown. However, it is unlikely that postponed laboratory measurements had clinically relevant negative treatment effects since no differences in aberrant serum levels were identified.

Background: Traditional pharmacovigilance systems have limitations in detecting common adverse drug reactions. We investigated whether real-world data (RWD) could have detected rofecoxib's cardiovascular adverse effects earlier using nested case-control (NCC) and case-crossover (CCO) designs.

Methods: We included adult rofecoxib users from the UK CPRD GOLD (1999-2004). In NCC design, cases of a first major adverse cardiovascular event (MACE) were matched with four controls on age, sex, practice and calendar time. Rofecoxib exposure was categorised as current (≤ 3 months), recent (3-6), or past use (> 6) in NCC, and assessed at the start of each 3-month interval in CCO design. Exposure odds in CCO were compared between a 3-month risk with four reference windows. Conditional logistic regression models estimated adjusted intensity ratio (aIR). To identify the shortest time necessary to detect the association, analyses were conducted in 1-, 2-, 3-, 4- and 5-years after the drug's market uptake.

Results: Three thousand two hundred and eighteen cases were matched to 10 745 controls (mean age 73.8 years, 66% female). In NCC, current rofecoxib use (42% of cases) was associated with an 18% higher risk of MACE (aIR 1.18, 95% CI 1.08-1.29) versus past use. The CCO (3210 risk and 12 737 reference windows) showed an 83% increased risk of MACE (aIR 1.83, 95% CI 1.53-2.18). First signal emerged after 2 years with CCO (aIR 3.94, 95% CI 1.88-8.25), and after 3 years with NCC design (aIR 1.46, 95% CI 1.18-1.81).

Conclusion: Using RWD, cardiovascular adverse effects of rofecoxib could have been detected within 2 years of the market entry in the UK, well before traditional pharmacovigilance methods. This supports incorporating RWD analysis into routine drug safety monitoring.

Purpose: People living with HIV (PLWH) face many challenges in adhering to antiretroviral therapy (ART). Measuring individual changes in adherence is essential to assess quality of care and to manage healthcare costs. This study aimed to identify patterns of ART adherence among adult PLWH in Belgium over a 24-month follow-up period.

Methods: A retrospective analysis of longitudinal data related to PLWH in Belgium was conducted using the Pharmanet database from 2019 to 2022. Adherence was assessed monthly and reported as the proportion of days covered. Group-based trajectory modeling was used to identify adherence patterns, with changes within each trajectory described using chi-square tests. Unordered multinomial logistic regression was used to identify predictors.

Results: We included 15 128 prevalent ART users, 2076 of whom were incident ART users living with HIV, 65.3% were male, 40.4% were aged between 35 and 49 years, and 44.9% lived in the Flanders region. During follow-up period, 61.0% of prevalent users and 52.1% of incident users maintained optimal adherence. Three groups ("consistently high" (61.0%), "moderately decreasing" (28.6%), and "highly decreasing" (10.4%)); and four groups adherence trajectories ("consistently high" (52.1%), "moderately decreasing" (24.3%), "early decrease" (12.9%), and "late decrease" (10.8%)) were identified respectively among prevalent and incident ART users. Female sex, younger age, living in the Brussels-Capital Region, and treatment initiation during the COVID-19 pandemic were significantly associated with suboptimal adherence.

Conclusions: ART adherence during the 24 months of follow-up among PLWH in Belgium was suboptimal. Interventions targeting at-risk groups during periods of declining adherence are needed among PLWH.

Purpose: Adverse drug reactions (ADRs) present significant obstacles for healthcare systems, impacting both patient safety and the effectiveness of treatments. Despite this, there is a scarcity of research on ADR reports in Sierra Leone, especially over long periods. This study aims to investigate the characteristics and reporting patterns found in the Sierra Leone pharmacovigilance database managed through VigiFlow.

Method: This study analyzes reports of ADRs from Sierra Leone's national pharmacovigilance database, VigiFlow, spanning from January 2008 to December 2022. Data collected included patient demographics (age, sex), reporter characteristics (type of reporter, year of reporting), and ADR-specific information (suspected medication, indication, ADR types (MedDRA), seriousness, outcome, actions taken, and time to onset), and completeness score. Descriptive statistics, chi-square tests, and the Kruskal-Wallis test with Bonferroni-adjusted post hoc tests were applied to identify patterns and associations within the dataset.

Results: A total of 3381 individual case safety reports (ICSRs) were analysed. The majority of reports involved females (54.7%) and adults aged 18 to 44 years (51.4%). Reporting rates increased after 2015, peaking in 2021. The most frequently implicated medications were anti-infective drugs (40.7%) and antiparasitic medicines (34.1%), particularly ivermectin, albendazole, and vaccines for cholera and yellow fever. The most commonly reported ADRs were headache (13.2%), fever (12.2%), and diarrhoea (7.6%), primarily affecting the nervous system and general disorder classes. Pharmacists were responsible for 39.0% of reports and achieved the highest completeness score, with a mean of 0.78. Age was significantly associated with the seriousness, outcome, and onset time of ADRs (p < 0.001), while gender was significantly associated with onset time (p = 0.007).

Conclusion: ADR reporting in Sierra Leone has improved, with antiparasitic medicines and vaccines most frequently linked to reactions. Sustaining progress requires enhanced training, public engagement, and strengthened active pharmacovigilance to ensure completeness and patient safety.

Purpose: Information from electronic health records (EHRs) may be incorporated into computable phenotype algorithms in efforts to overcome inaccuracies of algorithms based on administrative claims data alone. However, such efforts can be resource-intensive and unsuccessful. Assessing the feasibility of computable phenotyping for a health outcome of interest (HOI) before proceeding is therefore recommended.

Methods: We developed a systematic fitness-for-purpose (FFP) assessment process to implement concepts outlined in a previously described general framework for computable phenotyping incorporating EHR data. Our process includes verifying the HOI is well-defined, reviewing clinical information about the HOI, identifying existing algorithms and their performance, evaluating HOI clinical and data complexity, and determining an overall FFP conclusion and recommendation. We applied this process to 10 HOIs lacking high-performing claims-based algorithms, selecting HOIs of public health importance that varied in clinical and data complexity, including neutropenia, pericardial effusion, and drug-induced liver injury.

Results: HOIs assessed as having moderate (vs. easy) overall difficulty had characteristics such as the need for natural language processing, integration of multiple laboratory test results, or longitudinal EHR data. HOIs assessed as having high difficulty required using data from multiple EHR sources, ruling out many other potential causes, or relying on low-sensitivity diagnostic tests. Input from experts in EHR data and clinical care was crucial.

Conclusion: EHR data have the potential to enhance the accuracy of defining certain HOIs for research and surveillance compared to administrative claims data. The process and tools we created will support others in assessing FFP of HOIs for computable phenotyping.

Background: Trimethoprim-sulfamethoxazole (TMP-SMX) is associated with hypersensitivity and other adverse reactions. East Asian-specific genetic susceptibility may increase severe adverse events, limiting the therapeutic use of TMP-SMX for uncomplicated cystitis in Japan. However, data on its short-term safety in this population are scarce. This study compared the short-term safety of TMP-SMX with fluoroquinolones for the treatment of uncomplicated cystitis using a nationwide Japanese claims database.

Methods: We conducted a retrospective cohort study using the JMDC Claims Database (2006-2022). We included female outpatients aged ≥ 18 years with acute uncomplicated cystitis who were newly treated with TMP-SMX or fluoroquinolones (levofloxacin, ciprofloxacin, or tosufloxacin). The primary outcome was drug-induced hypersensitivity (anaphylaxis or treatment-requiring rash) within 7 days after the prescription of these drugs. The secondary outcomes included treatment failure, all-cause hospitalization, and other adverse events. Propensity score-overlap weighting was applied to adjust for confounding. Subgroup analyses were stratified by age (< 50 or ≥ 50 years).

Results: Among 50 773 eligible patients (TMP-SMX, 2.1%; fluoroquinolones, 97.9%), the baseline characteristics were well balanced after weighting. The incidence of hypersensitivity did not differ significantly between the groups (0.9% vs. 0.7%; risk difference, 0.3%; 95% confidence interval, -0.3% to 0.8%; p = 0.410). No significant differences were observed for secondary outcomes. Subgroup analyses showed consistent results.

Conclusions: Short-term use of TMP-SMX was not associated with increased risks of adverse events or treatment failure compared with fluoroquinolones. TMP-SMX may represent a reasonable first-line option for acute uncomplicated cystitis in Japan.

Background: Drug-induced immune hemolytic anemia (DIIHA), a rare complication of beta-lactams, lacks population-level data on subclinical antibody prevalence.

Objective: To quantify drug-induced antibody incidence and hematologic impact in beta-lactam-treated patients.

Methods: Prospective cohort of 4040 patients receiving ceftriaxone, piperacillin/trizobactam, piperacillin/sulbactam 2:1 and piperacillin/tazobactam at a Chinese tertiary hospital (2020.1-2020.9). Antibodies were detected via immunoadsorption assays. The primary outcomes were changes in hemoglobin, bilirubin, and lactate dehydrogenase (LDH) levels.

Results: Antibody positivity occurred in 18.07% (730/4040), highest with piperacillin/sulbactam 2:1 (24.02% vs. 0.43% Ceftriaxone, p < 0.001). Seropositive patients had a significant hemoglobin decline (Δ = -5.00 g/L, 95% CI -6.2 to -3.8) and bilirubin elevation (Δ = +0.95 μmol/L, 95% CI +0.4 to +1.5), but only 0.2% (2/730) progressed to severe anemia. Subclinical hemolysis (LDH > 250 U/L) was prevalent (89.3%).

Conclusion: Beta-lactams exhibit high asymptomatic antibody rates (18.07%) with minimal severe hemolysis risk (0.2%). Protocolized monitoring and HLA screening may optimize safety. This first large-scale prospective cohort quantifies the underrecognized epidemic of subclinical antibody formation, challenging traditional pharmacovigilance frameworks that focus solely on overt hemolysis.

Purpose: An increasing number of studies based on secondary data use, including registry-based studies, have been initiated to address post-authorization regulatory commitments. We map differences across tools used in data quality (DQ) assessments, including those embedded in fitness-for-purpose (FFP) assessments, and describe their strengths and limitations for use in DQ assessments of registries considered for use in post-approval safety studies (PASS). We focus on the use case where marketing authorization holders (MAHs) cannot directly analyze patient-level data. Furthermore, we propose complementary measures to improve DQ assessment, including a set of data quality indicators (DQIs).

Methods: We analyzed the extent to which the selected tools used in registry assessments address DQ dimensions and metrics defined in the European Medicines Agency-DQ Framework (EMA-DQF). We specifically considered the use case where DQ assessment was purely based on registry documentation and qualitative due to data access restrictions.

Results: None of the tools covered all DQ dimensions and metrics; they had limited utility for evaluating extensiveness (i.e., completeness and coverage), semantic coherence, and reliability (i.e., accuracy and plausibility). Furthermore, some supporting document requirements were more useful than others. For example, the data dictionary is useful for evaluating precision and structural coherence. In contrast, publications have limited utility in DQ assessment.

Conclusions: We propose a set of consistent definitions of information requirements and quantitative DQIs that complement existing tools that can be used for evaluating DQ throughout the registry-based PASS lifecycle. If DQIs cannot be evaluated during the preparation of the PASS protocol, uncertainties and their potential impact on the study results need to be acknowledged in the relevant study documents. Additionally, scenario mapping for the removal or replacement of registries with insufficient DQ after PASS initiation is needed.

Background: Differences in performance of the Self-Controlled Case Series (SCCS) for signal detection have been reported across different databases. However, there has been limited comparative analysis of performance and it remains unknown whether combinations of databases could enable more effective signal detection.

Objectives: This study aims to compare the performance of the SCCS for signal detection across several data sources, and to determine whether combinations of databases can improve SCCS performance.

Methods: We applied the SCCS to macrolides and fluoroquinolone antibiotics, in four databases: Merative MarketScan Commercial Claims and Medicare, the Clinical Practice Research Datalink (CPRD) Aurum and the Système National des Données de Santé. We developed a reference set of 104 positive controls and 58 negative controls, using a taxonomy framework to ensure the selected drug outcome pairs are theoretically well suited to the SCCS design. The observation period lasted 2 years, with a 30-day risk-window after each dispensing. Diagnostic performance was measured using sensitivity, specificity and area under the receiver operating curve (AUC) with respect to the product labels, both for individual and combinations of databases.

Results: The sensitivity of the SCCS ranged from 0.57-0.89 across individual databases, and the specificity from 0.43-0.77 when limited to drug-outcome pairs sufficiently powered. The combination of all databases achieved the maximum sensitivity of 0.89 (0.41 specificity) for the full reference set, and a sensitivity of 1 (0.35 specificity) for drug outcome pairs with enough power. Whilst AUCs ranged from 0.66 to 0.71 across individual databases, the highest performing combination was CPRD plus MarketScan Commercial Claims (0.76 AUC).

Conclusions: Using a carefully designed reference set of drug-outcome pairs well suited to the study design, the SCCS performance varied substantially by database due to differences in population, reporting, healthcare and coding systems and prescribing patterns. Multi-database studies showed increased performance of SCCS for signal detection.