Dataset Information

Application of an Integrative Drug Safety Model for Detection of Adverse Drug Events Associated With Inhibition of Glutathione Peroxidase 1 in Chronic Obstructive Pulmonary Disease.

ABSTRACT:

Background

Chronic Obstructive Pulmonary Disease is characterised by declining lung function and a greater oxidative stress burden due to reduced activity of antioxidant enzymes such as Glutathione Peroxidase 1.

Objectives

The extent to which drugs may contribute to this compromised activity is largely unknown. An integrative drug safety model explores inhibition of Glutathione Peroxidase 1 by drugs and their association with chronic obstructive pulmonary disease adverse drug events.

Methods

In silico molecular modelling approaches were utilised to predict the interactions that drugs have within the active site of Glutathione Peroxidase 1 in both human and bovine models. Similarities of chemical features between approved drugs and the known inhibitor tiopronin were also investigated. Subsequently the Food and Drug Administration Adverse Event System was searched to uncover adverse drug event signals associated with chronic obstructive pulmonary disease.

Results

Statistical and molecular modelling analyses confirmed that the use of several registered drugs, including acetylsalicylic acid and atenolol may be associated with inhibition of Glutathione Peroxidase 1 and chronic obstructive pulmonary disease.

Conclusion

The integration of molecular modelling and pharmacoepidemological data has the potential to advance drug safety science. Ongoing review of medication use and further pharmacoepidemiological and biological analyses are warranted to ensure appropriate use is recommended.

SUBMITTER: Janetzki JL

PROVIDER: S-EPMC10338407 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Application of an Integrative Drug Safety Model for Detection of Adverse Drug Events Associated With Inhibition of Glutathione Peroxidase 1 in Chronic Obstructive Pulmonary Disease.

Janetzki Jack L JL Pratt Nicole L NL Ward Michael B MB Sykes Matthew J MJ

Pharmaceutical research 20230512 6

<h4>Background</h4>Chronic Obstructive Pulmonary Disease is characterised by declining lung function and a greater oxidative stress burden due to reduced activity of antioxidant enzymes such as Glutathione Peroxidase 1.<h4>Objectives</h4>The extent to which drugs may contribute to this compromised activity is largely unknown. An integrative drug safety model explores inhibition of Glutathione Peroxidase 1 by drugs and their association with chronic obstructive pulmonary disease adverse drug even ...[more]

PMID: 37173537

Similar Datasets

Project description:BACKGROUND:Chronic obstructive pulmonary disease (COPD) is a common chronic disease. Exacerbations of COPD (eCOPD) contribute to the worsening of the disease and the patient's evolution. There are some clinical prediction rules that may help to stratify patients with eCOPD by their risk of poor evolution or adverse events. The translation of these clinical prediction rules into computer applications would allow their implementation in clinical practice. OBJECTIVE:The goal of this study was to create a computer application to predict various outcomes related to adverse events of short-term evolution in eCOPD patients attending an emergency department (ED) based on valid and reliable clinical prediction rules. METHODS:A computer application, Prediction of Evolution of patients with eCOPD (PrEveCOPD), was created to predict 2 outcomes related to adverse events: (1) mortality during hospital admission or within a week after an ED visit and (2) admission to an intensive care unit (ICU) or an intermediate respiratory care unit (IRCU) during the eCOPD episode. The algorithms included in the computer tool were based on clinical prediction rules previously developed and validated within the Investigación en Resultados y Servicios de Salud COPD study. The app was developed for Windows and Android systems, using Visual Studio 2008 and Eclipse, respectively. RESULTS:The PrEveCOPD computer application implements the prediction models previously developed and validated for 2 relevant adverse events in the short-term evolution of patients with eCOPD. The application runs under Windows and Android systems and it can be used locally or remotely as a Web application. Full description of the clinical prediction rules as well as the original references is included on the screen. Input of the predictive variables is controlled for out-of-range and missing values. Language can be switched between English and Spanish. The application is available for downloading and installing on a computer, as a mobile app, or to be used remotely via internet. CONCLUSIONS:The PrEveCOPD app shows how clinical prediction rules can be summarized into simple and easy to use tools, which allow for the estimation of the risk of short-term mortality and ICU or IRCU admission for patients with eCOPD. The app can be used on any computer device, including mobile phones or tablets, and it can guide the clinicians to a valid stratification of patients attending the ED with eCOPD. TRIAL REGISTRATION:ClinicalTrials.gov NCT00102401; https://clinicaltrials.gov/ct2/show/results/NCT02434536 (Archived by WebCite at http://www.webcitation.org/76iwTxYuA). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):RR2-10.1186/1472-6963-11-322.

Project description:Rationale: Targeted lung denervation (TLD) is a bronchoscopic radiofrequency ablation therapy for chronic obstructive pulmonary disease (COPD), which durably disrupts parasympathetic pulmonary nerves to decrease airway resistance and mucus hypersecretion.Objectives: To determine the safety and impact of TLD on respiratory adverse events.Methods: We conducted a multicenter, randomized, sham bronchoscopy-controlled, double-blind trial in patients with symptomatic (modified Medical Research Council dyspnea scale score, ≥2; or COPD Assessment Test score, ≥10) COPD (FEV1, 30-60% predicted). The primary endpoint was the rate of respiratory adverse events between 3 and 6.5 months after randomization (defined as COPD exacerbation, tachypnea, wheezing, worsening bronchitis, worsening dyspnea, influenza, pneumonia, other respiratory infections, respiratory failure, or airway effects requiring therapeutic intervention). Blinding was maintained through 12.5 months.Measurements and Main Results: Eighty-two patients (50% female; mean ± SD: age, 63.7 ± 6.8 yr; FEV1, 41.6 ± 7.3% predicted; modified Medical Research Council dyspnea scale score, 2.2 ± 0.7; COPD Assessment Test score, 18.4 ± 6.1) were randomized 1:1. During the predefined 3- to 6.5-month window, patients in the TLD group experienced significantly fewer respiratory adverse events than those in the sham group (32% vs. 71%, P = 0.008; odds ratio, 0.19; 95% confidence interval, 0.0750-0.4923, P = 0.0006). Between 0 and 12.5 months, these findings were not different (83% vs. 90%; P = 0.52). The risk of COPD exacerbation requiring hospitalization in the 0- to 12.5-month window was significantly lower in the TLD group than in the sham group (hazard ratio, 0.35; 95% confidence interval, 0.13-0.99; P = 0.039). There was no statistical difference in the time to first moderate or severe COPD exacerbation, patient-reported symptoms, or other physiologic measures over the 12.5 months of follow-up.Conclusions: Patients with symptomatic COPD treated with TLD combined with optimal pharmacotherapy had fewer study-defined respiratory adverse events, including hospitalizations for COPD exacerbation.Clinical trial registered with www.clinicaltrials.gov (NCT02058459).

Project description:Rationale: Older adults with chronic obstructive pulmonary disease (COPD) are at substantially increased risk for medication-related adverse events. Two frequently prescribed classes of drugs that pose a particular risk to this patient group are opioids and benzodiazepines. Research on this topic has yielded conflicting findings.Objectives: The purpose of this study was to examine, among older adults with COPD, whether: 1) independent or concurrent use of opioid and benzodiazepine medications was associated with hospitalizations for respiratory events, and 2) this association was exacerbated by the presence of obstructive sleep apnea (OSA).Methods: We conducted a case-control study of Medicare beneficiaries aged ≥66 years, who were diagnosed with COPD in 2013, using the 5% national Medicare database. Cases (n = 3,232) were defined as patients hospitalized for a primary COPD-related respiratory diagnosis in 2014 and were matched with up to two control subjects (n = 6,247) on index date, age, sex, socioeconomic status, comorbidity, presence of OSA, COPD medication, and COPD complexity.Results: In comparison to the referent (no opioid or benzodiazepine use), opioid use alone (adjusted odds ratio [aOR], 1.73; 95% confidence interval [CI], 1.52-1.97), benzodiazepine use alone (aOR, 1.42; 95% CI, 1.21-1.66), and concurrent opioid/ benzodiazepine use (aOR, 2.32; 95% CI, 1.94-2.77) in the 30 days before the event/index date were all associated with an increased risk of hospitalization for a respiratory condition. Risk of hospitalization was higher with concurrent opioid and benzodiazepine use when compared with use of either medication alone. There was no statistically significant interaction between OSA and either of the drugs, alone or in combination. However, the adverse respiratory effects of concurrent opioid and benzodiazepine use were increased in patients with a high degree of COPD complexity. All of the above findings persisted using exposure windows that extended to 60 and 90 days before the event/index date.Conclusions: Among older adults with COPD, use of opioid and benzodiazepine medications alone or in combination were associated with increased adverse respiratory events. The adverse effects of these medications were not exacerbated in patients with COPD-OSA overlap syndrome. However, the adverse impact of dual opioid and benzodiazepine was greater in patients with high-complexity COPD.

Project description:BackgroundIn Japan, Mycobacterium avium complex lung disease (MAC-LD) is the most common in nontuberculous mycobacterial lung disease. Patients often experience adverse events, resulting in the discontinuation of treatment, which causes treatment failure. The JADER (Japanese Adverse Drug Event Report) database is a database of adverse events that allows us to collect real-world data on adverse events. We can collect large-scale data cost-effectively and detect signals of potential adverse events such as reporting odds ratio (ROR) by using spontaneous reporting systems. In this study, we aimed to elucidate the adverse events of clarithromycin (CAM), ethambutol (EB), and rifampicin (RFP) using the JADER database.MethodsWe included cases of MAC-LD between April 2004 and June 2017. We investigated sex, age, and medications that may have caused the adverse events, outcomes, and time of onset. We calculated the safety signal index as the ROR. Time-to-event analysis was performed using the Weibull distribution.ResultsThe total number of adverse events of CAM, EB, and RFP was 2780, with 806 patients. In the overall adverse events, hematologic and lymphatic disorders were the most common adverse events, with 17.3%, followed by eye disorders (16.6%), and hepatobiliary disorders (14.0%). The outcomes were as follows: recovery, 40.0%; remission, 27.1%; non-recovery, 11.2%; and death, 7.1%. Regarding the most common onset time of CAM, EB, and RFP was within 120 days at 40%, 181-300 days at 43.6%, and within 120 days at 88.5%. For CAM, the RORs of infections and infestations, hepatobiliary system disorders, and immune system disorders were 4.13 (95% confidence interval [CI], 2.3-7.44), 2.61 (95% CI, 1.39-4.91), and 2.38 (95% CI, 1.04-5.44). For EB, the ROR of eye disorders was 215.79 (95% CI, 132.62-351.12). For RFP, the RORs of renal and urinary tract disorders and investigations were 7.03 (95% CI, 3.35-14.77) and 6.99 (95% CI, 3.22-15.18). The β value of EB was 2.07 (95% CI, 1.48-2.76), which was classified as a wear-out failure type.ConclusionsFor MAC-LD, the adverse event which has the highest ROR is infections and infestations in CAM, eye disorders in EB, renal and urinary tract disorders in RFP. Adverse events of EB occur after 180 days, whereas the adverse events of CAM and RFP occur early in the course of treatment.

Dataset Information

Application of an Integrative Drug Safety Model for Detection of Adverse Drug Events Associated With Inhibition of Glutathione Peroxidase 1 in Chronic Obstructive Pulmonary Disease.

Background

Objectives

Methods

Results

Conclusion

Publications

Application of an Integrative Drug Safety Model for Detection of Adverse Drug Events Associated With Inhibition of Glutathione Peroxidase 1 in Chronic Obstructive Pulmonary Disease.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets