Proton pump inhibitors and myocardial infarction: an application of active comparators in a self-controlled case series

Network Analysis and Machine Learning for Signal Detection and Prioritization Using Electronic Healthcare Records and Administrative Databases: A Proof of Concept in Drug-Induced Acute Myocardial Infarction

BACKGROUND

Safety signals for potential drug-induced adverse events (AEs) typically emerge from multiple data sources, primarily spontaneous reporting systems, despite known limitations. Increasingly, real-world data from sources such as electronic health records (EHRs) and administrative databases are leveraged for signal detection. Although network analysis has shown promise in mapping relationships between clinical attributes for signal detection in spontaneous reporting system databases, its application in real-world data from EHRs and administrative databases remains limited.

OBJECTIVE

This study aimed to evaluate the performance of network analysis in detecting safety signals within Italian administrative databases, using drug-induced acute myocardial infarction (AMI) as a proof of concept.

METHODS

We employed a case-crossover design to explore the association between drug exposure and AMI using the Healthcare Administrative Database of Mantova, Italy, from 2014 to 2018. Patients with their first AMI hospitalization were identified after a 365-day washout period to exclude prior hospitalizations. We constructed a network to analyse the relationships between prescribed drugs and diagnoses, represented as nodes, with undirected edges illustrating their interactions. For each patient with AMI, we identified all diagnoses and drugs recorded or redeemed within 365 days of the first AMI episode and generated various drug-diagnosis, drug-drug, and diagnosis-diagnosis pairs. We calculated the frequency of these pairs, and three types of edge weights quantified the strength of connections. We identified outlier drug-AMI pairs using a predictive score (F) based on frequency (C) and full edge weights (WF), with validation for known AMI associations. We prioritized signals using the F score, C of AMI, and WF, analysed through k-means clustering to identify patterns in the data.

RESULTS

From 2014 to 2018, a total of 3918 patients had an AMI, with 4686 AMI diagnoses. Of those, 2866 had prescriptions in the previous year, totalling 498,591 prescriptions. A network analysis identified 2968 unique nodes, revealing 529,935 diagnosis-diagnosis connections, 235,380 drug-diagnosis connections, and 102,831 drug-drug connections. The median number of connections (C) was 404 (Q1-Q3: 194-671) for drug nodes and 380 (Q1-Q3: 216-664) for diagnosis nodes. The median WF was 11.8 (Q1-Q3: 9-14), and the median F score across pairs was 0.1 (Q1-Q3: 0.1-0.3). A total of 249 potential safety signals were detected, with 63.4% aligning with known AEs. Among the remaining signals, 80 were prioritized, and five emerged as the highest priority: terazosin, tamsulosin, allopurinol, esomeprazole, and omeprazole.

CONCLUSIONS

Overall, our novel method demonstrates that network analysis is a valuable tool for signal detection and prioritization in drug-induced AEs based on EHRs and administrative databases.

Overcoming time-varying confounding in self-controlled case series with active comparators: application and recommendations

Confounding by indication is a key challenge for pharmacoepidemiologists. Although self-controlled study designs address time-invariant confounding, indications sometimes vary over time. For example, infection might act as a time-varying confounder in a study of antibiotics and uveitis, because it is time-limited and a direct cause of both receipt of antibiotics and uveitis. Methods for incorporating active comparators in self-controlled studies to address such time-varying confounding by indication have only recently been developed. In this paper, we formalize these methods and provide a detailed description for how the active comparator rate ratio can be derived in a self-controlled case series: either by explicitly comparing the regression coefficients for a drug of interest and an active comparator under certain circumstances using a simple ratio approach or through the use of a nested regression model. The approaches are compared in 2 case studies, one examining the association between thiazolidinedione use and fractures and one examining the association between fluoroquinolone use and uveitis, using the United Kingdom's Clinical Practice Research Datalink. Finally, we provide recommendations for the use of these methods, which we hope will support the design, execution, and interpretation of self-controlled case series using active comparators and thereby increase the robustness of pharmacoepidemiologic studies. This article is part of a Special Collection on Pharmacoepidemiology.

Core Concepts: Self-Controlled Designs in Pharmacoepidemiology

One of the key challenges in pharmacoepidemiological studies is that of uncontrolled confounding, which occurs when confounders are poorly measured, unmeasured or unknown. Self-controlled designs can help address this issue, as their key comparison is not between people, but periods of time within the same person. This controls for all time-stable confounders (genetics) and in the absence of time-varying confounding negates the need for an external control group. However, these benefits come at the cost of strong assumptions, not all of which are verifiable. This review briefly introduces the reader to different types of self-controlled study designs, their terminology and highlights key publications through an annotated reference list. We include a practical description of how these designs can be implemented and visualised using recent examples, and finish by discussing recent developments. We hope this review will serve as a starting point for researchers looking to apply self-controlled designs in their own work.

Adverse events in patients with cardiovascular disease taking proton pump inhibitors

INTRODUCTION

Proton pump inhibitors (PPIs) rank among the most frequently prescribed medications to treat acid-related diseases. Mounting concerns surround the potential for serious adverse events, including cardiovascular events, associated with their prolonged use/misuse.

AREAS COVERED

This comprehensive review explores cardiovascular adverse events linked to PPI use among high-risk cardiovascular patients. A structured search was conducted on PubMed.

EXPERT OPINION

Many patients with cardiovascular disease who require antiplatelet treatment will require long-term PPI treatment. Interpreting the published data is not straightforward. First, because there is no plausible mechanistic explanation for PPIs to induce cardiovascular events apart from the potential interaction with the metabolism of thienopyridines. Although several observational studies have shown an increased cardiovascular risk and mortality in patients taking long-term PPIs, most available clinical trials and meta-analyses of available studies do not. However, the absence of firm evidence of this link does not necessarily imply that this association does not exist, and other hypothesis must be explored. Anemia is a common event in patients who take antiplatelet therapy and PPIs, and it is a factor associated with cardiovascular events and death. Anemia in these patients is often attributed to erosive lesions of the small intestine, where PPI may play a key role by modifying the microbiota.

Association Between Oral Fluoroquinolones and Neuropsychiatric Events: Self-Controlled Case Series With Active Comparator Design

PURPOSE

The evidence of the neuropsychiatric effects associated with fluoroquinolones is mainly supported by case reports. Population-based evidence remains largely limited. We aimed to investigate the association between the use of fluoroquinolones and hospitalization or Accident & Emergency department visits for acute neuropsychiatric events using a self-controlled case series (SCCS) and active comparator to reduce confounding.

METHODS

We conducted a SCCS with a recently described active comparator design using all public outpatient clinics, hospitalization, and Accident and Emergency department records from the Clinical Data Analysis and Reporting System, Hong Kong from 2001 to 2013. Among 166 325 people with an oral fluoroquinolone prescription, 4287 people who had an incident neuropsychiatric event were included. We then estimated the incidence rate ratio (IRR) of acute neuropsychiatric events during periods before and after fluoroquinolone prescription, versus baseline. We repeated the analysis for amoxicillin/clavulanic acid users as an active comparator. We then estimated the comparator-adjusted estimates by dividing the IRR for fluoroquinolone by the IRR for amoxicillin/clavulanic acid. The primary outcome was neuropsychiatric events. Secondary outcomes were psychotic events and cognitive impairment.

RESULTS

An increased risk of neuropsychiatric events was observed in the current use of fluoroquinolone [IRR: 2.11 (95% confidence interval (CI): 1.58-2.83)] and 1-7 days after the end of fluoroquinolone prescription [IRR: 1.90 (95% CI: 1.30-2.75)] versus baseline. No increased risk was observed in other risk periods versus baseline. Similar patterns were observed in the current use of amoxicillin/clavulanic acid [IRR: 1.92 (95% CI: 1.19-3.11)] and 1-7 days after the end of fluoroquinolone prescription [IRR: 1.81 (95% CI: 1.11-2.97)] versus baseline. Similar results were found for secondary outcomes. Using the active comparator design, comparator-adjusted estimates were 1.10 (95% CI: 0.63-1.93) in current use of fluoroquinolones and 1.05 (95% CI: 0.57-1.95) in 1-7 days postexposure to fluoroquinolones versus baseline.

CONCLUSIONS

Although our study showed a higher incidence of neuropsychiatric events in the current use of fluoroquinolones and 7 days after the end of fluoroquinolones prescriptions compared with baseline, a similar temporal pattern was also found for amoxicillin/clavulanic acid users. Using amoxicillin/clavulanic acid as the active comparator, we found no difference in the risk of neuropsychiatric events associated with fluoroquinolone compared with baseline. Therefore, the risk of neuropsychiatric events may not need to influence the decision to prescribe either fluoroquinolones or amoxicillin/clavulanic acid based on the evidence in this study.

Risk of circulatory diseases associated with proton-pump inhibitors: a retrospective cohort study using electronic medical records in Thailand

Background

Proton-pump inhibitors (PPIs) are prescribed to treat gastric acid-related diseases, while they may also have potential risks to population health. Recent studies suggested that a potential mechanism explaining the association between PPIs and cardiovascular diseases (CVD) includes the inhibition of the nitrate-nitrite-nitric oxide (NO) pathway. However, previous observational studies showed controversial results of the association. In addition, the inhibition of the NO pathway due to PPIs use may lead to peripheral vascular diseases (PVD); however, none of the studies explore the PPI-PVD association. Therefore, this study aimed to evaluate the association of PPIs with circulatory diseases (CVD, ischemic strokes or IS, and PVD).

Methods

We conducted a retrospective hospital-based cohort study from Oct 2010 to Sep 2017 in Songkhla province, Thailand. PPIs and histamine 2-receptor antagonists (H2RAs) prescriptions were collected from electronic pharmacy records, while diagnostic outcomes were retrieved from electronic medical records at Songklanagarind hospital. Patients were followed up with an on-treatment approach. Cox proportional hazard models were applied to measure the association comparing PPIs vs H2RAs after 1:1 propensity-score-matching. Sub-group analysis, multi-bias E-values, and array-based sensitivity analysis for some covariates were used to assess the robustness of associations.

Results

A total of 3,928 new PPIs and 3,928 H2RAs users were included in the 1:1 propensity score-matched cohort. As compared with H2RAs, the association of PPIs with CVD, IS, and PVD, the hazard ratios were 1.76 95% CI = [1.40-2.20] for CVD, 3.53 95% CI = [2.21-5.64] for ischemic strokes, and 17.07 95% CI = [13.82-76.25] for PVD. The association between PPIs and each outcome was significant with medication persistent ratio of over 50%. In addition, the association between PPIs and circulatory diseases was robust to unmeasured confounders (i.e., smoking and alcohol).

Conclusion

PPIs were associated with circulatory diseases, particularly ischemic strokes in this hospital-based cohort study, whereas, the strength of associations was robust to unmeasured confounders.

Association between the Use of Proton Pump Inhibitors and Cardiovascular Diseases: A Nested Case-Control Study Using a National Health Screening Cohort

We investigated the association of proton pump inhibitor (PPI) use with the risk of stroke and ischemic heart disease (IHD). The Korean National Health Insurance Service-Health Screening cohort from 2002 to 2003, the participants of which were followed up until 2019, was used. In study I, 45,905 participants who were diagnosed with stroke were matched with 91,810 control I participants. The history of PPI medication was examined. In study II, 40,928 participants who were diagnosed with IHD were matched with 81,856 control II participants. In both study I and study II, the previous history of PPI medication was examined. A propensity score overlap-weighted multivariable logistic regression analysis was conducted to estimate the overlap-weighted odds ratios (ORs) of PPI use for stroke (study I) and IHD (study II). Current PPI use was linked with higher odds for stroke in study I. The odds for stroke were higher in groups with a longer duration of PPI use (OR = 0.96 [95% CI = 0.92-1.00] < 1.55 [1.50-1.61] < 1.62 [1.57-1.68] for < 30 days, 30 to 180 days, and ≥180 days of PPI use). Previous PPI use was linked with higher odds for IHD in study II. The odds for stroke were higher in groups with a longer duration of PPI use (OR = 1.13 [95% CI = 1.08-1.18] < 2.12 [2.04-2.21] < 2.60 [2.51-2.69] for <30 days, 30 to 180 days, and ≥180 days of PPI use). Current PPI medication is associated with a high risk of stroke and IHD. A longer duration of PPI medication was related to a higher risk of stroke and IHD. However, a prior history of PPI medication was not linked with a high risk of stroke or IHD.

Adverse Effects Associated with Long-Term Use of Proton Pump Inhibitors

Proton Pump Inhibitors are used widely to manage many gastric acid-related conditions such as gastroesophageal disease, gastritis, esophagitis, Barrett's esophagus, Zollinger-Ellison syndrome, peptic ulcer disease, nonsteroidal anti-inflammatory drug-associated ulcers, and Helicobacter pylori eradication, around the globe. This review article focuses on adverse effects associated with the long-term use of proton pump inhibitors. Various observational studies, clinical trials, and meta-analyses have established the adverse effects associated with the long-term use of proton pump inhibitors including renal disorders (acute interstitial nephritis, acute kidney injury, chronic kidney disease, and end-stage renal disease), cardiovascular risks (major adverse cardiovascular events, myocardial infarction, stent thrombosis, and stroke), fractures, infections (Clostridium difficile infection, community-acquired pneumonia, and Coronavirus disease 2019), micronutrient deficiencies (hypomagnesemia, anemia, vitamin B12 deficiency, hypocalcemia, hypokalemia), hypergastrinemia, cancers (gastric cancer, pancreatic cancer, colorectal cancer, hepatic cancer), hepatic encephalopathy, and dementia. Clinicians including prescribers and pharmacists should be aware of the adverse effects of taking proton pump inhibitors for an extended period of time. In addition, the patients taking proton pump inhibitors for long-term should be monitored for the listed adverse effects. The American Gastroenterological association recommends a few non-pharmacological measures and the use of histamine 2 blockers to lessen gastrointestinal symptoms of gastroesophageal reflex disease and the utilization of proton pump inhibitors treatment if there is a definitive indication. Additionally, the American Gastroenterological association's Best Practice Advice statements emphasize deprescribing when there is no clear indication for proton pump inhibitors therapy.