Drug Safety最新文献

BACKGROUND AND OBJECTIVES: SCORe of Toxic Epidermal Necrolysis (SCORTEN) and ABCD-10 have been developed as scoring systems for predicting mortality associated with Stevens-Johnson syndrome (SJS) or toxic epidermal necrolysis (TEN). These scores were developed based on a small number of patients; hence, their generalizability requires further exploration. The present study used three algorithms, including a machine learning method, to construct a mortality prediction model for SJS/TEN and to identify new candidate predictors of mortality from severe drug eruptions.

Methods: Data from 5966 patients with SJS or TEN were extracted from the Japanese Adverse Drug Event Report Database. A mortality prediction model was then constructed using stepwise regression, L1 regularized-logistic regression, and random forests based on the patient characteristics (e.g., age, sex, primary disease, adverse events, drug classification, route of administration) and outcomes (death).

Results and discussion: The mortality prediction models for SJS/TEN identified sex (men), primary disease (hyperlipidemia, diabetes mellitus, renal dysfunction, and malignant tumors), adverse events (renal dysfunction, liver dysfunction, respiratory dysfunction, bacteremia/sepsis, disseminated intravascular coagulation syndrome, shock, and multiple organ failure), number of concomitant drugs, and route of administration (injection) as common factors associated with mortality.

Conclusions: Our findings showed that sex, hyperlipidemia as the primary disease, number of concomitant drugs, use of antipyretic analgesics, and route of administration may be considered as predictors of mortality in patients with SJS/TEN. The external validity of these factors needs to be examined in the future.

Introduction: Medicinal plants are extensively utilized as dietary supplements to encourage disease prevention and to support the treatment of various health disorders. Unfortunately, several plants are known for mycotoxin contamination, which may overwhelm any beneficial effects the plants might have.

Objective: The purpose of the study was to determine the presence of ochratoxin A (OTA) and citrinin (CIT) in medicinal herbal products (MHP).

Methods: Sixty samples of different MHP types were purchased on the Czech market during 2020-2021. Both mycotoxins were determined using high-performance liquid chromatography with a fluorescence detector with immunoaffinity columns employed as a pretreatment.

Results: In total, 40% and 27% of samples were above the limit of quantification with the concentrations ranging up to 826.62 ng/g and 472.79 ng/g for OTA and CIT, respectively. The co-occurrence was confirmed in six MHP types.

Conclusions: MHP could be a significant source of OTA and CIT. To protect the health of MHP users, it is desirable to continue monitoring the presence of mycotoxins in MHP. During this study, new OTA regulations for herbs came into force in the EU.

Background: Adverse drug events (ADEs) are events occurring after the administration of a drug. Several authorities are involved in capturing these ADEs to improve pharmacovigilance. These ADEs are reported directly to healthcare professionals or via the telephone, online, or e-mail and are crucial for maintaining drug safety.

Objective: Patient-reported adverse drug events (ADEs) are collected using various tools, though not much is known with regard to the comparability of these different methodologies. It is known that telephone-based surveys result in a higher report rate, although it is not known if this has an effect on the type of ADEs that are reported. In this prospective study, we aimed to investigate if there are differences in the number, type, and severity of ADEs reported via telephone and online in an event monitoring setting.

Methods: Patients included in Dutch community pharmacies were asked whether they experienced any ADEs via telephone and online (Lareb Intensive Monitoring) surveys as part of the PREPARE study. The PREPARE study was a multicenter study, researching the effect of genotype-guided dosing on the incidence of clinically relevant adverse drug reactions. With the paired data acquired in the PREPARE study, we investigated differences in the number, type, and severity of the reported ADEs.

Results: Patients (N = 525) completed both the telephone and online surveys. Of the 525 patients who completed both surveys, 326 reported ADEs via telephone and 239 online. A visual comparison showed a similar distribution in the type of ADEs among the methods except for less commonly reported types of ADEs and cardiac disorders. The perceived severity of ADEs were proportionally reported as more severe during the telephone survey versus the online survey.

Conclusions: Our study showed a clear difference in the number of ADEs reported during telephone and online monitoring. Additionally, the differences in the type of ADEs and the severity distribution of both tools shows that the tools are not exchangeable (CT.gov identifier: NCT03093818).

Introduction: Opioid agonist treatment (OAT) reduces drug-related poisonings and injection-related infections among people with opioid use disorder (OUD). Despite buprenorphine-naloxone (BNX) and methadone (MET) both being first-line OAT options in Canada, their comparative effectiveness in preventing recurrent injection-related infections and poisonings remains unclear.

Objectives: This study compared the effectiveness of buprenorphine-naloxone and methadone in reducing recurrent risks of injection-related bacterial infections and opioid-related poisoning among people on OAT.

Methods: We used administrative health data from Québec, Canada to create our cohort of adult patients (aged 18-65 years) on OAT maintenance between 2014 and 2019. We applied a time-dependent Cox proportional hazards model for our time-varying exposure definition to estimate hazard ratios (HR) and 95% confidence intervals (CI) for the recurrent risks of injection-related bacterial infections and opioid-related poisoning, adjusting for age, sex, socio-demographic, and clinical factors. We also compared the effectiveness of buprenorphine-naloxone and methadone during the OAT induction phase (i.e., first 30 days of treatment).

Results: The study population included 2010 patients (mean age: 41.21 years, 67.41% male). Compared to methadone, buprenorphine-naloxone was associated with 45% lower recurrent risk of opioid-related poisoning (HR: 0.55; 95% CI 0.35-0.86). Overall, the association between buprenorphine-naloxone and recurrent risk of injection-related bacterial infections suggested a weak protective effect (HR: 0.80; 95% CI 0.59-1.09). During the induction phase, there was limited evidence of differences between buprenorphine-naloxone and methadone for the recurrent risks of injection-related bacterial infections (HR: 0.91; 95% CI 0.51-1.60) and opioid-related poisoning (HR: 1.07; 95% CI 0.51-2.24).

Conclusion: Among patients in OAT maintenance, buprenorphine-naloxone was associated with lower risk of recurrent opioid-related poisoning compared to methadone, but not for injection-related infections. This advantage was not observed during induction, suggesting the need for improved treatment retention early in OAT.

Introduction: Opioids are the most frequently prescribed medications for managing moderate-to-severe pain and are associated with significant potential for harm. Several models have been developed to predict opioid-related harms (ORHs). This study aimed to describe and evaluate the methodological quality of predictive models for identifying patients at high risk of ORHs.

Methods: Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline, we reviewed published studies on developing or validating models for predicting ORHs, identified through a literature search of Scopus, PubMed, Embase, and Google Scholar. The quality of studies was assessed using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). The models were assessed by area under the curve (AUC) or c-statistic, sensitivity, specificity, accuracy, and positive or negative predictive value. The study protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO; CRD42024540456).

Results: We included 36 studies involving participants aged 18 years or older. The frequently modeled ORHs were opioid use disorder (12 studies), opioid overdose (8 studies), opioid-induced respiratory depression (6 studies), and adverse drug events (4 studies). In total, 16 studies (44.4%) developed and validated tools. Most studies measured predictive ability using AUC (31, 86.1%), and some only reported sensitivity (14, 38.9%), specificity (11, 30.6%), or accuracy (4, 11.1%). Of the 31 studies that reported AUC values, 29 (93.5%) had moderate-to-high predictive ability (AUC > 0.70). History of opioid use (66.7%), age (58.3%), comorbidities (41.7%), sex (41.7%), and drug abuse and psychiatric problems (36.1%) were typical factors used in developing models.

Conclusions: The included predictive models showed moderate-to-high discriminative ability for screening patients at risk of ORHs. However, future studies should refine and validate them in various settings before considering the translation into clinical practice.

Background and objective: The new user cohort design has emerged as a best practice for the estimation of drug effects from observational data. However, despite its advantages, this design requires the selection and evaluation of comparators for appropriateness, a process that can be challenging. The objective of this work was to introduce an empirical approach to rank candidate comparators in terms of their similarity to a target drug in high-dimensional covariate space.

Methods: We generated new user cohorts for each RxNorm ingredient and Anatomic Therapeutic Chemical level 4 class in five administrative claims databases then extracted aggregated pre-treatment covariate data for each cohort across five clinically oriented domains. We formed all pairs of cohorts with ≥ 1000 patients and computed a scalar similarity score, defined as the average of cosine similarities computed within each domain, for each pair. We then generated ranked lists of candidate comparators for each cohort.

Results: Across up to 1350 cohorts forming 922,761 comparisons, drugs that were more similar in the Anatomic Therapeutic Chemical hierarchy had higher cohort similarity scores. The most similar candidate comparators for each of six example drugs corresponded to alternative treatments used in the target drug's indication(s), and choosing the top-ranked comparator for randomly selected drugs tended to produce balance on most covariates. This approach also ranked highly those comparators chosen in high-quality published new user cohort design studies.

Conclusion: Empirical comparator recommendations may serve as a useful aid to investigators and could ultimately enable the automated generation of new user cohort design-derived evidence, a process that has previously been limited to self-controlled designs.

Background: Despite ongoing efforts, the prescription of opioids is still common. Long-term opioid use has been associated with an increased risk of adverse cardiovascular outcomes.

Objective: We aimed to evaluate the association between opioid use and the risk of new-onset atrial fibrillation.

Methods: We performed a systematic review and meta-analysis of studies retrieved from MEDLINE and EMBASE databases according to PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines from inception to 29 January, 2024. The protocol was registered at PROSPERO (CRD42024512500). Two authors independently screened and extracted data from included studies. The quantitative analysis included only observational studies and results were synthesised by a pooled hazard ratio. Risk of bias was performed according to the ROBINS-I Cochrane tool, and the summary of evidence according to GRADE (Grading of Recommendations, Assessment, Development and Evaluations).

Results: Four out of 782 studies met the inclusion criteria for a quantitative analysis with 24,006,367 participants. Overall, 153,734 were opioid users. The proportion of women ranged from 13.2 to 100% and the median age ranged from 34 to 65 years. Studies reported 991,263 cases of new-onset atrial fibrillation. The pooled analysis showed a significant association between use of opioids and new-onset atrial fibrillation (hazard ratio 1.96, 95% confidence interval 1.43-2.69 with high heterogeneity). A sensitivity analysis by removing the study with the largest cohort showed similar results to the main analysis. In the summary of findings, the certainty of the evidence according to GRADE was moderate.

Conclusions: We found a significant association between opioid use and the risk of new-onset atrial fibrillation. When prescribing opioids, the risk of new-onset atrial fibrillation should be considered, especially in the presence of other risk factors for atrial fibrillation.