Systematic assessment of prescribed medications and short-term risk of myocardial infarction - a pharmacopeia-wide association study from Norway and Sweden

Dispensed prescription medications and short-term risk of pulmonary embolism in Norway and Sweden

Scandinavian electronic health-care registers provide a unique setting to investigate potential unidentified side effects of drugs. We analysed the association between prescription drugs dispensed in Norway and Sweden and the short-term risk of developing pulmonary embolism. A total of 12,104 pulmonary embolism cases were identified from patient- and cause-of-death registries in Norway (2004-2014) and 36,088 in Sweden (2005-2014). A case-crossover design was used to compare individual drugs dispensed 1-30 days before the date of pulmonary embolism diagnosis with dispensation in a 61-90 day time-window, while controlling for the receipt of other drugs. A BOLASSO approach was used to select drugs that were associated with short-term risk of pulmonary embolism. Thirty-eight drugs were associated with pulmonary embolism in the combined analysis of the Norwegian and Swedish data. Drugs associated with increased risk of pulmonary embolism included certain proton-pump inhibitors, antibiotics, antithrombotics, vasodilators, furosemide, anti-varicose medications, corticosteroids, immunostimulants (pegfilgrastim), opioids, analgesics, anxiolytics, antidepressants, antiprotozoals, and drugs for cough and colds. Mineral supplements, hydrochlorothiazide and potassium-sparing agents, beta-blockers, angiotensin 2 receptor blockers, statins, and methotrexate were associated with lower risk. Most associations persisted, and several additional drugs were associated, with pulmonary embolism when using a longer time window of 90 days instead of 30 days. These results provide exploratory, pharmacopeia-wide evidence of medications that may increase or decrease the risk of pulmonary embolism. Some of these findings were expected based on the drugs' indications, while others are novel and require further study as potentially modifiable precipitants of pulmonary embolism.

Major adverse cardiovascular events and mortality with opioids versus NSAIDs initiation in patients with rheumatoid arthritis

OBJECTIVE

Assess major adverse cardiovascular event (MACE) risk with opioids compared with non-steroidal anti-inflammatory drugs (NSAIDs) in patients with rheumatoid arthritis (RA) METHODS: We conducted a new-user active comparator cohort study among patients with RA within FORWARD, The National Databank for Rheumatic Diseases, with ≥1 year participation between 1998 and 2021. Each opioid initiator was matched to two NSAID initiators by propensity scores (PSs). Patients were followed until the occurrence of the composite endpoint of MACE (myocardial infarction, stroke, heart failure, cardiovascular disease (CVD) death, venous thromboembolism (VTE)) and all-cause mortality. The risk of outcomes was estimated using Cox proportional hazards with adjustment for PS weights and imbalanced covariables.

RESULTS

Among 6866 opioid initiators and 13 689 NSAID initiators, 212 vs 253 MACE (20.6/1000 person-years (PY) vs 18.9/1000 PY) and 144 vs 150 deaths (13.5/1000 PY vs 10.8/1000 PY) occurred, respectively. The risk of MACE with opioids was similar to NSAIDs (HR=1.02, 95% CI 0.85 to 1.22), whereas all-cause mortality with opioids was 33% higher than NSAIDs (HR=1.33, 95% CI 1.06 to 1.67) in PS-weighted models. Among the individual outcomes of MACE, VTE risk tended to be higher in opioid initiators than NSAID initiators (HR=1.41, 95% CI 0.84 to 2.35). Strong opioids had a higher risk for all-cause mortality and VTE than weak opioids compared with NSAIDs suggesting a dose-dependent association.

CONCLUSION

Opioids had similar MACE risk compared with NSAIDs in patients with RA with increased all-cause mortality and likely VTE, which suggests that opioids are not safer than NSAIDs, as clinicians have perceived.

Cardioprotective Role of Swertiamarin, a Plant Glycoside Against Experimentally Induced Myocardial Infarction via Antioxidant and Anti-inflammatory Functions

The study examined the protective effects of swertiamarin on rats with experimentally induced myocardial infarction. Three to six week-old male albino Wistar rats were used in this study and experimental myocardial infarction (MI) was induced using isoproterenol. Our results showed that swertiamarin restored the alteration in heart weight, body weight, and heart weight/tibia length ratio of MI-induced rats to basal levels significantly (p < 0.05). Swertiamarin significantly (p < 0.05) restored the levels of cardiac pathophysiological marker creatine kinase (CKMB), lactate dehydrogenase (LDH), aspartate aminotransferase (AST), alanine transaminase (ALT), and cardiac troponin I (cTn-1) to near normalcy in MI-induced rats. Levels of oxidative stress markers malondialdehyde (MDA), protein carbonyls (PC), and levels of Vitamin C and Vitamin E were significantly (p < 0.05) reverted to near basal levels in MI-induced rats by swertiamarin. Levels of the antioxidant glutathione (GSH) and antioxidant enzymes which include superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), glutathione-s-transferase (GST), glutathione reductase (GR), and plasma total antioxidant capacity (TAC) were (p < 0.05) brought to near normalcy in MI-induced rats by swertiamarin. Levels of sodium (Na), potassium (k), and calcium (Ca) ATPases were significantly (p < 0.05) restored to near normalcy in MI-induced rats by swertiamarin. Status of pro-inflammatory cytokines including tumor necrosis factor (TNF-α), interleukin-6 (IL-6), and histological aberrations were also significantly (p < 0.05) restored to near normalcy in MI-induced rats by swertiamarin. Together, our results concluded that swertiamarin exerts significant cardioprotective functions in experimental MI in rats.

Real-World Trends in the Evaluation of Medical Products

There is a compelling need to evaluate the real-world health effects of medical products outside of tightly controlled preapproval clinical trials. This is done through pharmacoepidemiology, which is the study of the health effects of medical products (including drugs, biologicals, and medical devices and diagnostics) in populations, often using nonrandomized designs. Recent developments in pharmacoepidemiology span changes in the focus of research questions, research designs, data used, and statistical analysis methods. Developments in these areas are thought to improve the value of the evidence produced by such studies, and are prompting greater use of real-world evidence to inform clinical, regulatory, and reimbursement decisions.

Genetic predictors of lifelong medication-use patterns in cardiometabolic diseases

Little is known about the genetic determinants of medication use in preventing cardiometabolic diseases. Using the Finnish nationwide drug purchase registry with follow-up since 1995, we performed genome-wide association analyses of longitudinal patterns of medication use in hyperlipidemia, hypertension and type 2 diabetes in up to 193,933 individuals (55% women) in the FinnGen study. In meta-analyses of up to 567,671 individuals combining FinnGen with the Estonian Biobank and the UK Biobank, we discovered 333 independent loci (P < 5 × 10-9) associated with medication use. Fine-mapping revealed 494 95% credible sets associated with the total number of medication purchases, changes in medication combinations or treatment discontinuation, including 46 credible sets in 40 loci not associated with the underlying treatment targets. The polygenic risk scores (PRS) for cardiometabolic risk factors were strongly associated with the medication-use behavior. A medication-use enhanced multitrait PRS for coronary artery disease matched the performance of a risk factor-based multitrait coronary artery disease PRS in an independent sample (UK Biobank, n = 343,676). In summary, we demonstrate medication-based strategies for identifying cardiometabolic risk loci and provide genome-wide tools for preventing cardiovascular diseases.

A medication-wide association study (MWAS) on repurposed drugs for COVID-19 with Pre-pandemic prescription medication exposure and pregnancy outcomes

Information on effects of medication therapies during pregnancy is lacking as pregnant patients are often excluded from clinical trials. This retrospective study explores the potential of using electronic health record (EHR) data to inform safety profiles of repurposed COVID medication therapies on pregnancy outcomes using pre-COVID data. We conducted a medication-wide association study (MWAS) on prescription medication exposures during pregnancy and the risk of cesarean section, preterm birth, and stillbirth, using EHR data between 2010-2017 on deliveries at PennMedicine. Repurposed drugs studied for treatment of COVID-19 were extracted from ClinicalTrials.gov (n = 138). We adjusted for known comorbidities diagnosed within 2 years prior to birth. Using previously developed medication mapping and delivery-identification algorithms, we identified medication exposure in 2,830 of a total 63,334 deliveries; from 138 trials, we found 31 medications prescribed and included in our cohort. We found 21 (68%) of the 31 medications were not positively associated with increased risk of the outcomes examined. With caution, these medications warrant potential for inclusion of pregnant individuals in future studies, while drugs found to be associated with pregnancy outcomes require further investigation. MWAS facilitates hypothesis-driven evaluation of drug safety across all prescription medications, revealing potential drug candidates for further research.

Medication-Wide Association Study Using Electronic Health Record Data of Prescription Medication Exposure and Multifetal Pregnancies: Retrospective Study

Background

Medication-wide association studies (MWAS) have been applied to assess the risk of individual prescription use and a wide range of health outcomes, including cancer, acute myocardial infarction, acute liver failure, acute renal failure, and upper gastrointestinal ulcers. Current literature on the use of preconception and periconception medication and its association with the risk of multiple gestation pregnancies (eg, monozygotic and dizygotic) is largely based on assisted reproductive technology (ART) cohorts. However, among non-ART pregnancies, it is unknown whether other medications increase the risk of multifetal pregnancies.

Objective

This study aimed to investigate the risk of multiple gestational births (eg, twins and triplets) following preconception and periconception exposure to prescription medications in patients who delivered at Penn Medicine.

Methods

We used electronic health record data between 2010 and 2017 on patients who delivered babies at Penn Medicine, a health care system in the Greater Philadelphia area. We explored 3 logistic regression models: model 1 (no adjustment); model 2 (adjustment for maternal age); and model 3—our final logistic regression model (adjustment for maternal age, ART use, and infertility diagnosis). In all models, multiple births (MBs) were our outcome of interest (binary outcome), and each medication was assessed separately as a binary variable. To assess our MWAS model performance, we defined ART medications as our gold standard, given that these medications are known to increase the risk of MB.

Results

Of the 63,334 distinct deliveries in our cohort, only 1877 pregnancies (2.96%) were prescribed any medication during the preconception and first trimester period. Of the 123 medications prescribed, we found 26 (21.1%) medications associated with MB (using nominal P values) and 10 (8.1%) medications associated with MB (using Bonferroni adjustment) in fully adjusted model 3. We found that our model 3 algorithm had an accuracy of 85% (using nominal P values) and 89% (using Bonferroni-adjusted P values).

Conclusions

Our work demonstrates the opportunities in applying the MWAS approach with electronic health record data to explore associations between preconception and periconception medication exposure and the risk of MB while identifying novel candidate medications for further study. Overall, we found 3 novel medications linked with MB that could be explored in further work; this demonstrates the potential of our method to be used for hypothesis generation.

Screening Large Population Health Databases for Potential COVID-19 Therapeutics: A Pharmacopeia-Wide Association Study (PWAS) of Commonly Prescribed Medications

Background

For both the current and future pandemics, there is a need for high-throughput drug screening methods to identify existing drugs with potential preventative and/or therapeutic activity. Epidemiologic studies could complement lab-focused efforts to identify possible therapeutic agents.

Methods

We performed a pharmacopeia-wide association study (PWAS) to identify commonly prescribed medications and medication classes that are associated with the detection of SARS-CoV-2 in older individuals (&gt;65 years) in long-term care homes (LTCH) and the community, between January 15 th, 2020 and December 31 st, 2020, across the province of Ontario, Canada.

Results

26,121 cases and 2,369,020 controls from LTCH and the community were included in this analysis. Many of the drugs and drug classes evaluated did not yield significant associations with SARS-CoV-2 detection. However, some drugs and drug classes appeared significantly associated with reduced SARS-CoV-2 detection, including cardioprotective drug classes such as statins (weighted OR 0.91, standard p-value &lt;0.01, adjusted p-value &lt;0.01) and beta-blockers (weighted OR 0.87, standard p-value &lt;0.01, adjusted p-value 0.01), along with individual agents ranging from levetiracetam (weighted OR 0.70, standard p-value &lt;0.01, adjusted p-value &lt;0.01) to fluoxetine (weighted OR 0.86, standard p-value 0.013, adjusted p-value 0.198) to digoxin (weighted OR 0.89, standard p-value &lt;0.01, adjusted p-value 0.02).

Conclusions

Using this epidemiologic approach which can be applied to current and future pandemics we have identified a variety of target drugs and drug classes that could offer therapeutic benefit in COVID-19 and may warrant further validation. Some of these agents (e.g. fluoxetine) have already been identified for their therapeutic potential.

Assessing short-term risk of ischemic stroke in relation to all prescribed medications

We examined the short-term risk of stroke associated with drugs prescribed in Norway or Sweden in a comprehensive, hypothesis-free manner using comprehensive nation-wide data. We identified 27,680 and 92,561 cases with a first ischemic stroke via the patient- and the cause-of-death registers in Norway (2004–2014) and Sweden (2005–2014), respectively, and linked these data to prescription databases. A case-crossover design was used that compares the drugs dispensed within 1 to 14 days before the date of ischemic stroke occurrence with those dispensed 29 to 42 days before the index event. A Bolasso approach, a version of the Lasso regression algorithm, was used to select drugs that acutely either increase or decrease the apparent risk of ischemic stroke. Application of the Bolasso regression algorithm selected 19 drugs which were associated with increased risk for ischemic stroke and 11 drugs with decreased risk in both countries. Morphine in combination with antispasmodics was associated with a particularly high risk of stroke (odds ratio 7.09, 95% confidence intervals 4.81–10.47). Several potentially intriguing associations, both within and across pharmacological classes, merit further investigation in focused, follow-up studies.

Optimizing drug selection from a prescription trajectory of one patient

It is unknown how sequential drug patterns convey information on a patient's health status and treatment guidelines rarely account for this. Drug-agnostic longitudinal analyses of prescription trajectories in a population-wide setting are needed. In this cohort study, we used 24 years of data (1.1 billion prescriptions) from the Danish prescription registry to model the risk of sequentially redeeming a drug after another. Drug pairs were used to build multistep longitudinal prescription trajectories. These were subsequently used to stratify patients and calculate survival hazard ratios between the stratified groups. The similarity between prescription histories was used to determine individuals' best treatment option. Over the course of 122 million person-years of observation, we identified 9 million common prescription trajectories and demonstrated their predictive power using hypertension as a case. Among patients treated with agents acting on the renin-angiotensin system we identified four groups: patients prescribed angiotensin converting enzyme (ACE) inhibitor without change, angiotensin receptor blockers (ARBs) without change, ACE with posterior change to ARB, and ARB posteriorly changed to ACE. In an adjusted time-to-event analysis, individuals treated with ACE compared to those treated with ARB had lower survival probability (hazard ratio, 0.73 [95% CI, 0.64-0.82]; P < 1 × 10^-16). Replication in UK Biobank data showed the same trends. Prescription trajectories can provide novel insights into how individuals' drug use change over time, identify suboptimal or futile prescriptions and suggest initial treatments different from first line therapies. Observations of this kind may also be important when updating treatment guidelines.

Association of Nonacute Opioid Use and Cardiovascular Diseases: A Scoping Review of the Literature

BACKGROUND In this scoping review, we identified and reviewed 23 original articles from the PubMed database that investigated the relationship between nonacute opioid use (NOU) and cardiovascular outcomes. METHODS AND RESULTS We defined NOU to include both long-term opioid therapy and opioid use disorder. We summarized the association between NOU and 5 classes of cardiovascular disease, including infective endocarditis, coronary heart disease (including myocardial infarction), congestive heart failure, cardiac arrythmia (including cardiac arrest), and stroke. The most commonly studied outcomes were coronary heart disease and infective endocarditis. There was generally consistent evidence of a positive association between community prevalence of injection drug use (with opioids being the most commonly injected type of drug) and community prevalence of infective endocarditis, and between (primarily medically indicated) NOU and myocardial infarction. There was less consensus about the relationship between NOU and congestive heart failure, cardiac arrhythmia, and stroke. CONCLUSIONS There is a dearth of high-quality evidence on the relationship between NOU and cardiovascular disease. Innovative approaches to the assessment of opioid exposure over extended periods of time will be required to address this need.