Methodological considerations when analysing and interpreting real-world data

Risk of Neuroinflammatory Diseases Among New Recipients of Biologic and Targeted Synthetic Disease-Modifying Antirheumatic Drugs

OBJECTIVE

Neuroinflammatory adverse events have been observed among new users of tumor necrosis factor (TNF) inhibitors. No studies to date have compared the real-world risk of TNFs with other new users of biologic or targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs). The objective of this study is to describe the risk of neuroinflammatory disease after initiation b/tsDMARDs.

METHODS

This new user comparative effectiveness cohort study used a large US-based electronic health records database to describe the unadjusted incidence of neuroinflammatory adverse events over a 3-year period. The cohort included patients with rheumatoid arthritis, psoriasis, psoriatic arthritis, ankylosing spondylitis, Crohn's disease, or ulcerative colitis initiating treatment with a TNF inhibitor (n = 93,661) or other b/tsDMARD (n = 38,354).

RESULTS

Among 132,015 patients included in the analysis, the most common first biologic agent was a TNF inhibitor; the unadjusted incidence of neuroinflammatory events was numerically lower among new users of TNF inhibitors (incidence 1.34 per 1,000 patient-years) as compared with the combined non-TNF group (1.69 per 1,000 patient-years). There was no significant association between TNF exposure and neuroinflammatory events as compared with the combined non-TNF b/tsDMARDs overall (hazard ratio 1.01; 95% confidence interval 0.75-1.36) and within each disease group.

CONCLUSION

The overall risk of neuroinflammatory events among new users of TNF inhibitors did not differ substantially as compared with new users of other b/tsDMARDs. Meta-analyses of randomized trials should be conducted to corroborate these findings, which may be affected by channeling bias.

Alzheimer Disease and Related Dementia Following Hormone-Modulating Therapy in Patients With Breast Cancer

Importance

Hormone-modulating therapy (HMT) is a widely accepted treatment for hormone receptor-positive breast cancer, although its cognitive effects, including a potential link to Alzheimer disease and related dementias (ADRD), remain understudied.

Objective

To investigate the association between HMT for breast cancer treatment and risk of developing ADRD in women aged 65 years or older.

Design, Setting, and Participants

This cohort study used a comprehensive dataset from the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database to identify patients who did and did not receive HMT treatment within 3 years after the initial diagnosis of breast cancer and assessed their risk of developing ADRD in later life. Individuals with a preexisting diagnosis of ADRD or receiving HMT before the diagnosis of breast cancer were excluded. This study was performed from June 2022 through January 2024.

Exposure

Receipt of HMT.

Main Outcomes and Measures

Risk of ADRD associated with HMT; associations of risk with age, self-identified race, and HMT type. Risk was measured using hazard ratios (HRs) with 95% CIs and adjusted for potential confounders such as demographic, sociocultural, and clinical variables.

Results

Among 18 808 women aged 65 years and older diagnosed with breast cancer between 2007 and 2009 (1266 Black [6.7%], 16 526 White [87.9%], 1016 other [5.4%]), 12 356 (65.7%) received HMT within 3 years after diagnosis, while 6452 (34.3%) did not. The most common age group in both samples was the 75 to 79 years age group (HMT, 2721 women [22.0%]; no HMT, 1469 women [22.8%]), and the majority of women in both groups self-identified as White (HMT, 10 904 women [88.3%]; no HMT, 5622 women [87.1%]). During an average of 12 years of follow-up, 2926 (23.7%) of HMT users and 1802 (27.9%) of non-HMT users developed ADRD. HMT was associated with a 7% lower relative risk of ADRD overall (HR, 0.93; 95% CI, 0.88-0.98; P = .005). The association decreased with age and varied by race. The reduction in ADRD risk associated with HMT was greatest for women aged 65 to 74 years who self-identified as Black (HR, 0.76; 95% CI, 0.62-0.92). This association decreased among women aged 75 years or older (HR, 0.81; 95% CI, 0.67-0.98). Women aged 65 to 74 years who self-identified as White had an 11% relative risk reduction (HR, 0.89; 95% CI, 0.81-0.97), but the association disappeared for women aged 75 years or older (HR, 0.96; 95% CI, 0.90-1.02). Other races showed no significant association between HMT and ADRD. Age- and race-based associations also varied by HMT type.

Conclusions and Relevance

In this retrospective cohort study, hormone therapy was associated with protection against ADRD in women aged 65 years or older with newly diagnosed breast cancer; the decrease in risk was relatively greater for Black women and women under age 75 years, while the protective effect of HMT diminished with age and varied by race in women. When deciding to use HMT for breast cancer in women aged 65 years or more, clinicians should consider age, self-identified race, and HMT type in treatment decisions.

A practical guide to estimating treatment effects in patients with rheumatic diseases using real-world data

OBJECTIVE

Randomized controlled trials are considered the gold standard in study methodology. However, due to their study design and inclusion criteria, these studies may not capture the heterogeneity of real-world patient populations. In contrast, the lack of randomization and the presence of both measured and unmeasured confounding factors could bias the estimated treatment effect when using observational data. While causal inference methods allow for the estimation of treatment effects, their mathematical complexity may hinder their application in clinical research.

METHODS

We present a practical, nontechnical guide using a common statistical package (Stata) and a motivational simulated dataset that mirrors real-world observational data from patients with rheumatic diseases. We demonstrate regression analysis, regression adjustment, inverse-probability weighting, propensity score (PS) matching and two robust estimation methods.

RESULTS

Although the methods applied to control for confounding factors produced similar results, the commonly used one-to-one PS matching method could yield biased results if not thoroughly assessed.

CONCLUSION

The guide we propose aims to facilitate the use of readily available methods in a common statistical package. It may contribute to robust and transparent epidemiological and statistical methods, thereby enhancing effectiveness research using observational data in rheumatology.

Incidence of Liver and Non-liver Cancers After Hepatitis C Virus Eradication: A Population-Based Cohort Study

BACKGROUND AND OBJECTIVES

Direct-acting antivirals (DAAs) offer a high rate of hepatitis C virus (HCV) eradication. However, concerns on the risk of cancer after HCV eradication remain. Our study aimed at quantifying the incidence of cancer in patients treated with anti-HCV therapies in Catalonia (Spain) and their matched controls.

METHODS

This was a population-based study using real-world data from the public healthcare system of Catalonia between 2012 and 2016. Propensity score matching was performed in patients with HCV infection treated with interferon-based therapy (IFN), sequential IFN and DAA (IFN+DAA), and DAA only (DAA) with concurrent controls. We estimated the annual incidence of overall cancer, hepatocellular carcinoma, and non-liver cancer of HCV-treated patients and their corresponding rate ratios.

RESULTS

The study included 11,656 HCV-treated patients and 49,545 controls. We found statistically significant increases in the rate of overall cancer for IFN+DAA-treated (rate ratio [RR] 1.77, 95% confidence interval [CI] 1.27-2.46) and DAA-treated patients (RR 1.90, 95% CI 1.66-2.19) and in the rate of HCC for IFN-treated (RR 1.50, 95% CI 1.02-2.22), IFN+DAA-treated (RR 3.89, 95% CI 2.26-6.69), and DAA-treated patients (RR 6.45, 95% CI 4.90-8.49) compared with their corresponding controls. Moreover, DAA-treated patients with cirrhosis showed an increased rate of overall cancer versus those without cirrhosis (RR 1.92, 95% CI 1.51-2.44).

CONCLUSIONS

Results showed that overall cancer and hepatocellular carcinoma incidence in Catalonia was significantly higher among HCV-treated patients compared with matched non-HCV-infected controls, and risks were higher in patients with cirrhosis. An increased awareness of the potential occurrence of uncommon malignant events and monitoring after HCV eradication therapy may benefit patients.

Safety of Combined Statin and Fibrate Therapy: Risks of Liver Injury and Acute Kidney Injury in a Cohort Study from the Shizuoka Kokuho Database

INTRODUCTION

Statins and fibrates are important means of preventing cardiovascular diseases, particularly when administered in combination as part of various therapeutic strategies. In this study, we explored the risks associated with various combinations of these drugs.

OBJECTIVE

We aimed to evaluate the risk of 1-year hospitalization with acute kidney injury, liver injury, pancreatitis, or rhabdomyolysis related to the concurrent administration of statins and fibrates.

METHODS

We performed a retrospective cohort study using data from the Shizuoka Kokuho Database, focusing on patients prescribed statins, fibrates, or a combination. Four drug exposure patterns were evaluated: adding statins to fibrates (exposure 1), switching from fibrates to statins (exposure 2), adding fibrates to statins (exposure 3), and switching from statins to fibrates (exposure 4). Hospitalization for the specified conditions within 1 year was the outcome. Propensity score matching was used to create balanced cohorts for comparison.

RESULTS

We studied 269,226 statin users and 16,282 fibrate users. After propensity score matching, there were 498 participants in the group of exposure 1, matched with 2988 in the fibrate-only group; 1180 in the group of exposure 2, matched with 7080 in the fibrate-only group; 1183 in group of exposure 3, matched with 11,830 in the statin only group; and 1356 in group of exposure 4, matched with 13,560 in the statin only group. The 1-year hospitalization rate with liver injury was higher in the group of exposure 1 than in the fibrate-only group (1.2% vs 0.3%, p < 0.01), in the group of exposure 2 than in the fibrate-only group (0.9% vs 0.3%, p < 0.01), and in the group of exposure 4 than in the statin-only group (0.6% vs 0.2%, p = 0.02). There was also a higher risk of 1-year hospitalization with acute kidney injury in group of exposure 1 than in the fibrate-only group (1.3% vs 0.3%, p = 0.01) but not in evaluations of exposure 2, 3, and 4. However, there were no differences in the risks of 1-year hospitalization with pancreatitis or rhabdomyolysis among the matched groups.

CONCLUSIONS

We have demonstrated higher risks of 1-year hospitalization with liver injury or acute kidney injury associated with the use of combinations of statins and fibrates. This underscores the need for a cautious approach to the prescribing of such drug combinations and the importance of monitoring patients for potential adverse events.

Sodium-Glucose Cotransporter-2 Inhibitors vs Sulfonylureas for Gout Prevention Among Patients With Type 2 Diabetes Receiving Metformin

Importance

Sodium-glucose cotransporter type 2 inhibitors (SGLT2i) are a revolutionary treatment for type 2 diabetes (T2D) with cardiovascular, kidney, and serum urate-lowering benefits.

Objective

To compare risk of incident gout and rate of recurrent flares between patients with T2D initiating SGLT2i vs sulfonylurea, most common second-line glucose-lowering therapy, when added to metformin monotherapy.

Design, Setting, and Participants

This sequential, propensity score-matched, new-user comparative effectiveness study using target trial emulation framework included adults with T2D receiving metformin monotherapy in a Canadian general population database from January 1, 2014, to June 30, 2022.

Exposures

Initiation of SGLT2i vs sulfonylurea.

Main Outcomes and Measures

The primary outcome was incident gout diagnosis, ascertained by emergency department (ED), hospital, outpatient, and medication dispensing records. Secondary outcomes were gout-primary hospitalizations and ED visits and major adverse cardiovascular events (MACE), as well as recurrent flare rates among prevalent gout patients. Heart failure (HF) hospitalization was assessed as positive control outcome and osteoarthritis encounters as negative control. For target trial emulations, we used Cox proportional hazards and Poisson regressions with 1:1 propensity score matching (primary analysis) and overlap weighting (sensitivity analysis). The analysis was conducted from September to December, 2023.

Results

Among 34 604 propensity score matched adults with T2D initiating SGLT2i or sulfonylurea (20 816 [60%] male, mean [SD] age, 60 [12.4] years), incidence of gout was lower among SGLT2i initiators (4.27 events per 1000 person-years) than sulfonylurea initiators (6.91 events per 1000 person-years), with a hazard ratio (HR) of 0.62 (95% CI, 0.48-0.80) and a rate difference (RD) of -2.64 (95% CI, -3.99 to -1.29) per 1000 person-years. Associations persisted regardless of sex, age, or baseline diuretic use. SGLT2i use was also associated with fewer recurrent flares among gout patients (rate ratio, 0.67; 95% CI, 0.55-0.82; and RD, -20.9; 95% CI, -31.9 to -10.0 per 1000 person-years). HR and RD for MACE associated with SGLT2i use were 0.87 (95% CI, 0.77-0.98) and -3.58 (95% CI, -6.19 to -0.96) per 1000 person-years. For control outcomes, SGLT2i users had lower risk of HF (HR, 0.53; 95% CI, 0.38-0.76), as expected, with no difference in osteoarthritis (HR, 1.11; 95% CI, 0.94-1.34). Results were similar when applying propensity score overlap weighting.

Conclusions

In this population-based cohort study, the gout and cardiovascular benefits associated with SGLT2i in these target trial emulations may guide selection of glucose-lowering therapy in patients with T2D, at risk for or already with gout.

Iterative Causal Forest: A Novel Algorithm for Subgroup Identification

Precisely and efficiently identifying subgroups with heterogeneous treatment effects (HTEs) in real-world evidence studies remains a challenge. Based on the causal forest (CF) method, we developed an iterative CF (iCF) algorithm to identify HTEs in subgroups defined by important variables. Our method iteratively grows different depths of the CF with important effect modifiers, performs plurality votes to obtain decision trees (subgroup decisions) for a family of CFs with different depths, and then finds the cross-validated subgroup decision that best predicts the treatment effect as a final subgroup decision. We simulated 12 different scenarios and showed that the iCF outperformed other machine learning methods for interaction/subgroup identification in the majority of scenarios assessed. Using a 20% random sample of fee-for-service Medicare beneficiaries initiating sodium-glucose cotransporter-2 inhibitors or glucagon-like peptide-1 receptor agonists, we implemented the iCF to identify subgroups with HTEs for hospitalized heart failure. Consistent with previous studies suggesting patients with heart failure benefit more from sodium-glucose cotransporter-2 inhibitors, iCF successfully identified such a subpopulation with HTEs and additive interactions. The iCF is a promising method for identifying subgroups with HTEs in real-world data where the potential for unmeasured confounding can be limited by study design.

Timing of Initiation of Xanthine Oxidase Inhibitors Based on Serum Uric Acid Level Does Not Predict Renoprognosis in Patients with Preserved Kidney Function

Background: Despite recent evidence of remaining possibility that early initiation of xanthine oxidase inhibitors (XOIs) is beneficial in renoprognosis for patients with stage 2 or less chronic kidney disease (CKD), no evidence is available regarding the difference in renoprognosis based on serum uric acid (sUA) levels at the initiation of XOIs among patients with preserved kidney function. Methods: New XOI initiators were divided into quartiles based on baseline sUA. Primary outcome was the composite incidence of a significant estimated glomerular filtration rate (eGFR) decline (≥40% decline in eGFR from baseline or development of eGFR <30 mL/1.73 m2/min) or all-cause death within 5 years. Results: After excluding inapplicable patients, 1170 XOI initiators were analyzed (mean ± standard deviation age: 68 ± 14.3 years; sUA: 10.6 ± 1.15 mg/dL). On overall median [interquartile range (IQR)] follow-up of 824 (342, 1576) days, incidence rate of the primary outcome was 287 per 1000 person-years for 5 years. Although the nonadjusted model showed a dose-response association between baseline sUA level and the outcome, the adjusted model showed no significant association. Adjusted hazard ratios (95% confidence interval) of the second, third, and fourth quartiles of baseline sUA with the composite outcome within 5 years compared to the first quartile were 1.00 (0.78, 1.29), 1.00 (0.80, 1.30), and 1.02 (0.80, 1.32), respectively. Conclusions: Early initiation of XOIs did not predict a significant benefit on renoprognosis even among the population with preserved kidney function. The validity of initiating XOIs with the aim of improving renoprognosis based on sUA is questionable.

The use of real-world data for clinical investigation of effectiveness in drug development

With the growing interest in leveraging real-world data (RWD) to support effectiveness evaluations for new indications, new target populations, and post-market performance, the United States Food and Drug Administration has published several guidance documents on RWD sources and real-world studies (RWS) to assist sponsors in generating credible real-world evidence (RWE). Meanwhile, the randomized controlled trial (RCT) remains the gold standard in drug evaluation. Along this line, we propose a hybrid two-stage adaptive design to evaluate effectiveness based on evidence from both RCT and RWS. At the first stage, a typical non-inferiority test is conducted using RCT data to test for not-ineffectiveness. Once not-ineffectiveness is established, the study proceeds to the second stage to conduct an RWS and test for effectiveness using integrated information from RCT and RWD. The composite likelihood approach is implemented as a down-weighing strategy to account for the impact of high variability in RWS population. An optimal sample size determination procedure for RCT and RWS is introduced, aiming to achieve the minimal expected sample size. Through extensive numerical study, the proposed design demonstrates the ability to control type I error inflation in most cases and consistently maintain statistical power above the desired level. In general, this RCT/RWS hybrid two-stage adaptive design is beneficial for effectiveness evaluations in drug development, especially for oncology and rare diseases.

On the use of RWD in support of regulatory submission in drug development

For the approval of a drug product, the United States Food and Drug Administration requires substantial evidence (SE) regarding effectiveness and safety of the test drug to be provided. In recent years, the use of real-world data in support of regulatory submission of pharmaceutical development has received much attention, and real-world evidence (RWE) is treated as complementary to SE by evaluating the real-world performance of the test treatment. In this article, we start by summarizing current regulatory perspectives on drug evaluation and some potential challenges in using RWE. To test for superiority in co-primary endpoints, a two-stage hybrid RCT/RWS adaptive design that combines randomized control trial for providing SE and real-world study for generating RWE is proposed. We use superiority in effectiveness and non-inferiority in safety as an example to illustrate how to implement this design. Numerical studies have shown that the proposed design has merits in reducing the required sample size compared with traditional co-primary endpoint tests while maintaining statistical power and controlling type I error inflation. The proposed design can be implemented in drug development considering co-primary endpoints, especially for oncology and rare disease drug development.

Staging and clean room: Constructs designed to facilitate transparency and reduce bias in comparative analyses of real-world data

PURPOSE

We describe constructs designed to protect the integrity of the results from comparative analyses using real-world data (RWD): staging and clean room.

METHODS

Staging involves performing sequential preliminary analyses and evaluating the population size available and potential bias before conducting comparative analyses. A clean room involves restricted access to data and preliminary results, policies governing exploratory analyses and protocol deviations, and audit trail. These constructs are intended to allow decisions about protocol deviations, such as changes to design or model specification, to be made without knowledge of how they might affect subsequent analyses. We describe an example for implementing staging with a clean room.

RESULTS

Stage 1 may involve selecting a data source, developing and registering a protocol, establishing a clean room, and applying inclusion/exclusion criteria. Stage 2 may involve attempting to achieve covariate balance, often through propensity score models. Stage 3 may involve evaluating the presence of residual confounding using negative control outcomes. After each stage, check points may be implemented when a team of statisticians, epidemiologists and clinicians masked to how their decisions may affect study outcomes, reviews the results. This review team may be tasked with making recommendations for protocol deviations to address study precision or bias. They may recommend proceeding to the next stage, conducting additional analyses to address bias, or terminating the study. Stage 4 may involve conducting the comparative analyses.

CONCLUSIONS

The staging and clean room constructs are intended to protect the integrity and enhance confidence in the results of analyses of RWD.

Use of Healthcare Claims Data to Generate Real-World Evidence on Patients With Drug-Resistant Epilepsy: Practical Considerations for Research

Objectives: Regulatory bodies, health technology assessment agencies, payers, physicians, and other decision-makers increasingly recognize the importance of real-world evidence (RWE) to provide important and relevant insights on treatment patterns, burden/cost of illness, product safety, and long-term and comparative effectiveness. However, RWE generation requires a careful approach to ensure rigorous analysis and interpretation. There are limited examples of comprehensive methodology for the generation of RWE on patients who have undergone neuromodulation for drug-resistant epilepsy (DRE). This is likely due, at least in part, to the many challenges inherent in using real-world data to define DRE, neuromodulation (including type implanted), and related outcomes of interest. We sought to provide recommendations to enable generation of robust RWE that can increase knowledge of "real-world" patients with DRE and help inform the difficult decisions regarding treatment choices and reimbursement for this particularly vulnerable population. Methods: We drew upon our collective decades of experience in RWE generation and relevant disciplines (epidemiology, health economics, and biostatistics) to describe challenges inherent to this therapeutic area and to provide potential solutions thereto within healthcare claims databases. Several examples were provided from our experiences in DRE to further illustrate our recommendations for generation of robust RWE in this therapeutic area. Results: Our recommendations focus on considerations for the selection of an appropriate data source, development of a study timeline, exposure allotment (specifically, neuromodulation implantation for patients with DRE), and ascertainment of relevant outcomes. Conclusions: The need for RWE to inform healthcare decisions has never been greater and continues to grow in importance to regulators, payers, physicians, and other key stakeholders. However, as real-world data sources used to generate RWE are typically generated for reasons other than research, rigorous methodology is required to minimize bias and fully unlock their value.

Cardiovascular, Neurological, and Immunological Adverse Events and the 23-Valent Pneumococcal Polysaccharide Vaccine

Importance

Despite widespread immunization with the 23-valent pneumococcal polysaccharide vaccine (PPSV23), safety concerns remain owing to a lack of statistical power and largely outdated evidence.

Objective

To evaluate the association between cardiovascular, neurological, and immunological adverse events and PPSV23 vaccination in older adults.

Design, Setting, and Participants

This population-based cohort study using a self-controlled risk interval design used a large linked database created by linking the Korea Immunization Registry Information System and the National Health Information Database (2018 to 2021). Participants included patients aged 65 years or older with a history of PPSV23 vaccination and incident cardiovascular, neurological, or immunological events during the risk and control intervals. Data were analyzed from November 2022 to April 2023.

Exposure

23-valent pneumococcal polysaccharide vaccine.

Main Outcomes and Measures

The occurrence of 1 among 6 cardiovascular events (myocardial infarction, atrial fibrillation, cardiomyopathy, heart failure, hypotension, and myocarditis or pericarditis), 2 neurological events (Bell palsy and Guillain-Barré syndrome), and 3 immunological events (sepsis, thrombocytopenia, and anaphylaxis) during the risk and control periods. The risk and control intervals were defined as 1 to 28 and 57 to 112 days after PPSV23 vaccination, respectively. Conditional Poisson regression was used to estimate the incidence rate ratio (IRR) with a 95% CI.

Results

Altogether, 4355 of the 1 802 739 individuals who received PPSV23 vaccination and experienced at least 1 outcome event were included (mean [SD] age, 72.4 [8.2] years; 2272 male participants [52.1%]). For cardiovascular events, there were no significant associations for myocardial infarction (IRR, 0.96; 95% CI, 0.81-1.15), heart failure (IRR, 0.85; 95% CI, 0.70-1.04), and stroke (IRR, 0.92; 95% CI, 0.84-1.02). Similarly, no increased risks were observed for neurological and immunological outcomes: Bell palsy (IRR, 0.95; 95% CI, 0.72-1.26), Guillain-Barré syndrome (IRR, 0.27; 95% CI, 0.06-1.17), sepsis (IRR, 0.99; 95% CI, 0.74-1.32), and thrombocytopenia (IRR, 1.18; 95% CI, 0.60-2.35).

Conclusions and Relevance

In this self-controlled risk interval study, there was no appreciable increase in risk for most cardiovascular, neurological, or immunological adverse events following PPSV23. The updated safety profile of PPSV23 provides supportive evidence for the establishment of immunization strategies for older adults.

Translation of a Claims-Based Frailty Index From the International Classification of Diseases, Ninth Revision, Clinical Modification to the Tenth Revision

The Faurot frailty index (FFI) is a validated algorithm that uses enrollment and International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM)-based billing information from Medicare claims data as a proxy for frailty. In October 2015, the US health-care system transitioned from the ICD-9-CM to the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM). Applying the Centers for Medicare and Medicaid Services General Equivalence Mappings, we translated diagnosis-based frailty indicator codes from the ICD-9-CM to the ICD-10-CM, followed by manual review. We used interrupted time-series analysis of Medicare data to assess the comparability of the pre- and posttransition FFI scores. In cohorts of beneficiaries enrolled in January 2015-2017 with 8-month frailty look-back periods, we estimated associations between the FFI and 1-year risk of aging-related outcomes (mortality, hospitalization, and admission to a skilled nursing facility). Updated indicators had similar prevalences as pretransition definitions. The median FFI scores and interquartile ranges (IQRs) for the predicted probability of frailty were similar before and after the International Classification of Diseases transition (pretransition: median, 0.034 (IQR, 0.02-0.07); posttransition: median, 0.038 (IQR, 0.02-0.09)). The updated FFI was associated with increased risks of mortality, hospitalization, and skilled nursing facility admission, similar to findings from the ICD-9-CM era. Studies of medical interventions in older adults using administrative claims should use validated indices, like the FFI, to mitigate confounding or assess effect-measure modification by frailty.

Ticagrelor vs Clopidogrel in Acute Myocardial Infarction Patients With a History of Ischemic Stroke

OBJECTIVE

To investigate whether use of ticagrelor compared to clopidogrel is associated with different risks for thrombotic events or major bleeding among acute myocardial infarction (AMI) patients with a prior history of acute ischemic stroke.

PATIENTS AND METHODS

This retrospective cohort study used the Health and Welfare Database in Taiwan. Stroke patients prescribed ticagrelor plus aspirin or clopidogrel plus aspirin after a primary hospitalization for AMI between July 1, 2013, and December 31, 2018, were included. Inverse probability of treatment weighting was applied to balance covariates between treatment groups. The primary effectiveness outcome included a composite measure of AMI, acute ischemic stroke, or all-cause mortality. The primary safety outcome included a composite measure of intracranial hemorrhage (ICH) and major gastrointestinal bleeding. The secondary effectiveness and safety outcomes comprised each of the individual components that make up the primary effectiveness and safety outcomes, respectively.

RESULTS

A total of 1691 eligible patients were included in the study, of whom 734 (43.4%) received ticagrelor plus aspirin and 957 received clopidogrel plus aspirin. There were no significant differences observed in the primary and secondary effectiveness outcomes between the two study groups. However, the use of ticagrelor was associated with a higher risk of ICH (ticagrelor: 8.68 per 1000 person-year; clopidogrel: 2.17 per 1,000 person-year; HR, 3.34; 95% CI, 1.27 to 8.81, P = .01) compared with clopidogrel.

CONCLUSION

In AMI patients with a history of acute ischemic stroke, the risks of cardiovascular events were comparable between ticagrelor plus aspirin and clopidogrel plus aspirin. However, ticagrelor was associated with a higher risk of ICH. Ticagrelor should be used cautiously in AMI patients with a history of acute ischemic stroke.

How therapeutic advances have transformed the medical landscape: a primer for clinicians

Novel medicines are entering the market rapidly and are increasingly being used alone or in combination to treat illnesses of every sort. While transforming the lives of many patients, these new therapies have also forced us to reconsider the way we evaluate, use and fund medicines. This article offers a primer to help practitioners understand how the therapeutic landscape is changing and how this might impact the evidence generation, access to interventions, patient experience and quality of care.

Comparative Effectiveness of Sodium-Glucose Cotransporter-2 Inhibitors for Recurrent Gout Flares and Gout-Primary Emergency Department Visits and Hospitalizations : A General Population Cohort Study

BACKGROUND

Sodium-glucose cotransporter-2 inhibitors (SGLT2is) decrease serum urate levels, but whether this translates into prevention of recurrent flares among patients with gout and gout-primary emergency department (ED) visits or hospitalizations is unknown.

OBJECTIVE

To compare gout flares and cardiovascular events among patients with gout initiating SGLT2is versus dipeptidyl peptidase 4 inhibitors (DPP-4is), another second-line glucose-lowering agent not associated with serum urate levels or cardiovascular risk.

DESIGN

Propensity score-matched, new-user cohort study.

SETTING

General population database from 1 January 2014 to 30 June 2022.

PARTICIPANTS

Patients with gout and type 2 diabetes.

MEASUREMENTS

The primary outcome was recurrent gout flare counts ascertained by ED, hospitalization, outpatient, and medication dispensing records. Secondary outcomes included myocardial infarction and stroke; genital infection (positive control) and osteoarthritis encounter (negative control) were also assessed. Poisson and Cox proportional hazards regressions were used with 1:1 propensity score matching (primary analysis) and overlap weighting (sensitivity analysis).

RESULTS

After propensity score matching, the flare rate was lower among SGLT2i initiators than DPP-4i initiators (52.4 and 79.7 events per 1000 person-years, respectively), with a rate ratio (RR) of 0.66 (95% CI, 0.57 to 0.75) and a rate difference (RD) of -27.4 (CI, -36.0 to -18.7) per 1000 person-years. The corresponding RR and RD for gout-primary ED visits and hospitalizations were 0.52 (CI, 0.32 to 0.84) and -3.4 (CI, -5.8 to -0.9) per 1000 person-years, respectively. The corresponding hazard ratio (HR) and RD for myocardial infarction were 0.69 (CI, 0.54 to 0.88) and -7.6 (CI, -12.4 to -2.8) per 1000 person-years; the HR for stroke was 0.81 (CI, 0.62 to 1.05). Those who initiated SGLT2is showed higher risk for genital infection (HR, 2.15 [CI, 1.39 to 3.30]) and no altered risk for osteoarthritis encounter (HR, 1.07 [CI, 0.95 to 1.20]). Results were similar when propensity score overlap weighting was applied.

LIMITATION

Participants had concurrent type 2 diabetes.

CONCLUSION

Among patients with gout, SGLT2is may reduce recurrent flares and gout-primary ED visits and hospitalizations and may provide cardiovascular benefits.

PRIMARY FUNDING SOURCE

National Institute of Arthritis and Musculoskeletal and Skin Diseases.

Real-world effect of a potential drug-drug interaction between topiramate and oral contraceptives on unintended pregnancy outcomes

OBJECTIVE

To evaluate the association of concomitant topiramate and oral hormonal contraceptive use with unintended pregnancies.

STUDY DESIGN

We conducted a retrospective cohort design in MarketScan Research Databases (2005-2018) on women aged 12-48 who had migraines or chronic headaches and concomitantly used topiramate and oral contraceptives. We used a cohort of patients with oral contraceptives and concomitant use of other migraine prevention therapies (propranolol, metoprolol, amitriptyline, venlafaxine, or verapamil) as a comparator. We followed patients for up to 1 year from cohort entry to assess the occurrence of unintended pregnancy (i.e., contraception failure). Pregnancy events were measured via an algorithm harnessing medical encounters information with live births, terminations, or prenatal visits. Statistical models accounted for multiple cohort entries and adjusted for measured confounders via a propensity score weighting method.

RESULTS

We identified 63,649 episodes of oral contraceptives+topiramateand 59,012 episodes of oral contraceptives+other maintenance therapies. The mean age was 29.2±9.0 and 29.0±9.3 years in the study cohorts. In the adjusted analysis, the contraception failure rate (95% confidence interval) was 1.3 (1.1, 1.6) per 100 person-years in the oral contraceptives+topiramate cohort and 1.3 (1.1, 1.6) in the oral contraceptives+other maintenance therapies cohort. The adjusted rate ratio and rate difference measures were 1.00 (0.80, 1.26) and 0.00 (-0.3, 0.3).

CONCLUSION

Concomitant use of low-dose topiramate and oral contraceptives among patients with migraines was not associated with a higher risk for unintended pregnancies.

IMPLICATIONS

Our real-world findings confirm clinical pharmacology trials, suggesting that low-dose (≤200 mg/d) topiramate may not influence oral contraceptive effectiveness.

Trastuzumab emtansine vs lapatinib and capecitabine in HER2-positive metastatic breast cancer brain metastases: A real-world study

BACKGROUND

Trastuzumab emtansine (T-DM1) has demonstrated improvements in survival and neurological symptoms in patients with breast cancer with brain metastases (BCBM). This real-world study investigated the effectiveness of T-DM1 versus lapatinib plus capecitabine (LC) in patients with BCBM.

METHODS

This retrospective, observational study evaluated patients with HER2-positive BCBM using a real-world database. Eligible patients had initiated T-DM1 or LC with a prior diagnosis of brain metastasis and ≥1 prior metastatic breast cancer treatment. The primary endpoint was overall survival (OS); secondary endpoints were time to next relevant treatment or death (TTNT) and real-world progression-free survival (rwPFS). An inverse probability of treatment weighting (IPTW) approach was used to account for differences in potential baseline characteristics between treatment groups. Outcomes were described using the Kaplan-Meier method, and the average treatment effect of initiating T-DM1 versus LC was estimated using weighted Cox proportional hazard models and hazard ratio (HR).

RESULTS

A total of 214 patients were available for analysis (T-DM1, n = 161; LC, n = 53). Demographics and baseline characteristics were generally well-balanced between treatment groups after weighting. After weighting, median OS was 17.7 (T-DM1) versus 9.6 (LC) months (HR, 0.55 [95% CI, 0.34-0.89]; P=0.013). Median TTNT was 9.0 (T-DM1) versus 6.0 (LC) months (HR, 0.55 [95% CI, 0.36-0.85]; P = 0.005). After weighting, median rwPFS was 6.0 (T-DM1) versus 4.0 (LC) months (HR, 0.50 [95% CI, 0.36-0.69]; P < 0.001).

CONCLUSIONS

These results support the superior effectiveness and clinical relevance of T-DM1 versus LC in patients with HER2-positive BCBM in the real world.

An overview of methodological flaws of real-world studies investigating drug safety in the post-marketing setting

INTRODUCTION

The evaluation of the post-marketing safety profile of drugs is a continuous monitoring process for approved and marketed medicines and it is crucial for detecting new adverse drug reactions. As such, real-world studies are essential to complement pre-marketing evidence with information concerning drug risk-benefit profile and use in wider patient populations and they have a great potential to support post-marketing drug safety evaluations.

AREAS COVERED

A detailed description of the main limitations of real-world data sources (i.e. claims databases, electronic healthcare records, drug/disease registers and spontaneous reporting system databases) and of the main methodological challenges of real-world studies in generating real-world evidence is provided.

EXPERT OPINION

Real-world evidence biases can be ascribed to both the methodological approach and the specific limitations of the different real-world data sources used to carry out the study. As such, it is crucial to characterize the quality of real-world data, by establishing guidelines and best practices for the assessment of data fitness for purpose. On the other hand, it is important that real-world studies are conducted using a rigorous methodology, aimed at minimizing the risk of bias.

Noninterventional studies in the COVID-19 era: methodological considerations for study design and analysis

The global COVID-19 pandemic has generated enormous morbidity and mortality, as well as large health system disruptions including changes in use of prescription medications, outpatient encounters, emergency department admissions, and hospitalizations. These pandemic-related disruptions are reflected in real-world data derived from electronic medical records, administrative claims, disease or medication registries, and mobile devices. We discuss how pandemic-related disruptions in healthcare utilization may impact the conduct of noninterventional studies designed to characterize the utilization and estimate the effects of medical interventions on health-related outcomes. Using hypothetical studies, we highlight consequences that the pandemic may have on study design elements including participant selection and ascertainment of exposures, outcomes, and covariates. We discuss the implications of these pandemic-related disruptions on possible threats to external validity (participant selection) and internal validity (for example, confounding, selection bias, missing data bias). These concerns may be amplified in populations disproportionately impacted by COVID-19, such as racial/ethnic minorities, rural residents, or people experiencing poverty. We propose a general framework for researchers to carefully consider during the design and analysis of noninterventional studies that use real-world data from the COVID-19 era.

ISPE-Endorsed Guidance in Using Electronic Health Records for Comparative Effectiveness Research in COVID-19: Opportunities and Trade-Offs

As the scientific research community along with healthcare professionals and decision makers around the world fight tirelessly against the coronavirus disease 2019 (COVID-19) pandemic, the need for comparative effectiveness research (CER) on preventive and therapeutic interventions for COVID-19 is immense. Randomized controlled trials markedly under-represent the frail and complex patients seen in routine care, and they do not typically have data on long-term treatment effects. The increasing availability of electronic health records (EHRs) for clinical research offers the opportunity to generate timely real-world evidence reflective of routine care for optimal management of COVID-19. However, there are many potential threats to the validity of CER based on EHR data that are not originally generated for research purposes. To ensure unbiased and robust results, we need high-quality healthcare databases, rigorous study designs, and proper implementation of appropriate statistical methods. We aimed to describe opportunities and challenges in EHR-based CER for COVID-19-related questions and to introduce best practices in pharmacoepidemiology to minimize potential biases. We structured our discussion into the following topics: (1) study population identification based on exposure status; (2) ascertainment of outcomes; (3) common biases and potential solutions; and (iv) data operational challenges specific to COVID-19 CER using EHRs. We provide structured guidance for the proper conduct and appraisal of drug and vaccine effectiveness and safety research using EHR data for the pandemic. This paper is endorsed by the International Society for Pharmacoepidemiology (ISPE).

Effectiveness and Safety of Clopidogrel vs Aspirin in Elderly Patients With Ischemic Stroke

OBJECTIVE

To evaluate the risks of recurrent stroke and major bleeding events with clopidogrel and aspirin use among patients aged 80 years or older.

PATIENTS AND METHODS

This retrospective cohort study was conducted using the Full Population Data of the Health and Welfare Database in Taiwan. Patients aged 80 years or older who received monotherapy with clopidogrel or aspirin following hospitalization for primary acute ischemic stroke between January 1, 2009, and December 31, 2018, were included. Inverse probability of treatment weighting was used to balance measured covariates between clopidogrel and aspirin users. Measured outcomes included recurrent acute ischemic stroke, acute myocardial infarction, composite cardiovascular events (recurrent stroke or acute myocardial infarction), intracranial hemorrhage, major gastrointestinal tract bleeding, and composite major bleeding events (intracranial hemorrhage or major gastrointestinal tract bleeding).

RESULTS

A total of 15,045 patients were included in the study, 1979 of whom used clopidogrel and 13,066 who used aspirin following hospitalization for primary acute ischemic stroke. Clopidogrel use was associated with significantly lower risk of recurrent acute ischemic stroke (hazard ratio [HR], 0.89; 95% CI, 0.83 to 0.96; P=.002), composite cardiovascular events (HR, 0.88; 95% CI, 0.82 to 0.95; P<.001), intracranial hemorrhage (HR, 0.71; 95% CI, 0.56 to 0.90; P=.005), and composite major bleeding events (HR, 0.89; 95% CI, 0.80 to 0.99; P=.04) compared with aspirin use.

CONCLUSION

In patients aged 80 years or older with primary acute ischemic stroke, clopidogrel users had lower risks of recurrent stroke and the composite cardiovascular events compared with aspirin users. Clopidogrel users also had lower risks of intracranial hemorrhage and the composite major bleeding events compared with aspirin users.

Serious Cardiovascular Adverse Events Associated with Hydroxychloroquine/Chloroquine Alone or with Azithromycin in Patients with COVID-19: A Pharmacovigilance Analysis of the FDA Adverse Event Reporting System (FAERS)

BACKGROUND

The use of hydroxychloroquine or chloroquine (HCQ/CQ) as monotherapy or combined with azithromycin for the treatment of coronavirus disease 2019 (COVID-19) may increase the risk of serious cardiovascular adverse events (SCAEs).

OBJECTIVE

Our objective was to describe and evaluate the risk of SCAEs with HCQ/CQ as monotherapy or combined with azithromycin compared with that for therapeutic alternatives.

METHODS

We performed a disproportionality analysis and descriptive case series using the US FDA Adverse Event Reporting System.

RESULTS

Compared with remdesivir, HCQ/CQ was associated with increased reporting of SCAEs (reporting odds ratio [ROR] 2.1; 95% confidence interval [CI] 1.8-2.5), torsade de pointes (TdP)/QTc prolongation (ROR 35.4; 95% CI 19.4-64.5), and ventricular arrhythmia (ROR 2.5; 95% CI 1.6-3.9); similar results were found in comparison with other therapeutic alternatives. Compared with lopinavir/ritonavir, HCQ/CQ was associated with increased reporting of ventricular arrhythmia (ROR 10.5; 95% CI 3.3-33.4); RORs were larger when HCQ/CQ was used in combination with azithromycin. In 2020, 312 of the 575 reports of SCAEs listed concomitant use of HCQ/CQ and azithromycin, including QTc prolongation (61.4%), ventricular arrhythmia (12.0%), atrial fibrillation (8.2%), TdP (4.9%), and cardiac arrest (4.4%); 88 (15.3%) cases resulted in hospitalization and 79 (13.7%) resulted in death. In total, 122 fatal QTc prolongation-related cardiovascular reports were associated with 1.4 times higher odds of reported death than those induced by SCAEs; 87 patients received more than one QTc-prolonging agent.

CONCLUSIONS

Patients treated with HCQ/CQ monotherapy or HCQ/CQ + azithromycin may be at increased risk of SCAEs, TdP/QTc prolongation, and ventricular arrhythmia. Cardiovascular risks need to be considered when evaluating the benefit/harm balance of treatment with HCQ/CQ, especially with the concurrent use of QTc-prolonging agents and cytochrome P450 3A4 inhibitors when treating COVID-19.

Validity of Administrative Data for Identifying Birth-Related Outcomes with the End Date of Pregnancy in a Japanese University Hospital

This study aimed to develop and validate claims-based algorithms for identifying live birth, fetal death, and cesarean section by utilizing administrative data from a university hospital in Japan. We included women who visited the Department of Obstetrics at a university hospital in 2018. The diagnosis, medical procedures, and medication data were used to identify potential cases of live birth, fetal death, and cesarean section. By reviewing electronic medical records, we evaluated the positive predictive values (PPVs) and the accuracy of the end date of pregnancy for each claims datum. “Selected algorithm 1” based on PPVs and “selected algorithm 2” based on both the PPVs and the accuracy of the end date of pregnancy were developed. A total of 1757 women were included, and the mean age was 32.8 years. The PPVs of “selected algorithm 1” and “selected algorithm 2” were both 98.1% for live birth, 99.0% and 98.9% for fetal death, and 99.7% and 100.0% for cesarean section, respectively. These findings suggest that the developed algorithms are useful for future studies for evaluating live birth, fetal death, and cesarean section with an accurate end date of pregnancy.

Framework for the synthesis of non-randomised studies and randomised controlled trials: a guidance on conducting a systematic review and meta-analysis for healthcare decision making

INTRODUCTION

High-quality randomised controlled trials (RCTs) provide the most reliable evidence on the comparative efficacy of new medicines. However, non-randomised studies (NRS) are increasingly recognised as a source of insights into the real-world performance of novel therapeutic products, particularly when traditional RCTs are impractical or lack generalisability. This means there is a growing need for synthesising evidence from RCTs and NRS in healthcare decision making, particularly given recent developments such as innovative study designs, digital technologies and linked databases across countries. Crucially, however, no formal framework exists to guide the integration of these data types.

OBJECTIVES AND METHODS

To address this gap, we used a mixed methods approach (review of existing guidance, methodological papers, Delphi survey) to develop guidance for researchers and healthcare decision-makers on when and how to best combine evidence from NRS and RCTs to improve transparency and build confidence in the resulting summary effect estimates.

RESULTS

Our framework comprises seven steps on guiding the integration and interpretation of evidence from NRS and RCTs and we offer recommendations on the most appropriate statistical approaches based on three main analytical scenarios in healthcare decision making (specifically, 'high-bar evidence' when RCTs are the preferred source of evidence, 'medium,' and 'low' when NRS is the main source of inference).

CONCLUSION

Our framework augments existing guidance on assessing the quality of NRS and their compatibility with RCTs for evidence synthesis, while also highlighting potential challenges in implementing it. This manuscript received endorsement from the International Society for Pharmacoepidemiology.

Association of Type of Oral Anticoagulant Dispensed With Adverse Clinical Outcomes in Patients Extending Anticoagulation Therapy Beyond 90 Days After Hospitalization for Venous Thromboembolism

IMPORTANCE

Guidelines for managing venous thromboembolism (VTE) recommend at least 90 days of therapy with oral anticoagulants. Limited evidence exists about the optimal drug for continuing therapy beyond 90 days.

OBJECTIVE

To compare having prescriptions dispensed for apixaban, rivaroxaban, or warfarin after an initial 90 days of anticoagulation therapy for the outcomes of hospitalization for recurrent VTE, major bleeding, and death.

DESIGN, SETTING, AND PARTICIPANTS

This exploratory retrospective cohort study used data from fee-for-service Medicare (2009-2017) and from 2 commercial health insurance (2004-2018) databases and included 64 642 adults who initiated oral anticoagulation following hospitalization discharge for VTE and continued treatment beyond 90 days.

EXPOSURES

Apixaban, rivaroxaban, or warfarin prescribed after an initial 90-day treatment for VTE.

MAIN OUTCOMES AND MEASURES

Primary outcomes included hospitalization for recurrent VTE and hospitalization for major bleeding. Analyses were adjusted using propensity score weighting. Patients were followed up from the end of the initial 90-day treatment episode until treatment cessation, outcome, death, disenrollment, or end of available data. Weighted Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% CIs.

RESULTS

The study included 9167 patients prescribed apixaban (mean [SD] age, 71 [14] years; 5491 [59.9%] women), 12 468 patients prescribed rivaroxaban (mean [SD] age, 69 [14] years; 7067 [56.7%] women), and 43 007 patients prescribed warfarin (mean [SD] age, 70 [15] years; 25 404 [59.1%] women). The median (IQR) follow-up was 109 (59-228) days for recurrent VTE and 108 (58-226) days for major bleeding outcome. After propensity score weighting, the incidence rate of hospitalization for recurrent VTE was significantly lower for apixaban compared with warfarin (9.8 vs 13.5 per 1000 person-years; HR, 0.69 [95% CI, 0.49-0.99]), but the incidence rates were not significantly different between apixaban and rivaroxaban (9.8 vs 11.6 per 1000 person-years; HR, 0.80 [95% CI, 0.53-1.19]) or rivaroxaban and warfarin (HR, 0.87 [95% CI, 0.65-1.16]). Rates of hospitalization for major bleeding were 44.4 per 1000 person-years for apixaban, 50.0 per 1000 person-years for rivaroxaban, and 47.1 per 1000 person-years for warfarin, yielding HRs of 0.92 (95% CI, 0.78-1.09) for apixaban vs warfarin, 0.86 (95% CI, 0.71-1.04) for apixaban vs rivaroxaban, and 1.07 (95% CI, 0.93-1.24) for rivaroxaban vs warfarin.

CONCLUSIONS AND RELEVANCE

In this exploratory analysis of patients prescribed extended-duration oral anticoagulation therapy after hospitalization for VTE, prescription dispenses for apixaban beyond 90 days, compared with warfarin beyond 90 days, were significantly associated with a modestly lower rate of hospitalization for recurrent VTE, but no significant difference in rate of hospitalization for major bleeding. There were no significant differences for comparisons of apixaban vs rivaroxaban or rivaroxaban vs warfarin.

Effects of Chinese Medicine on the Survival of AIDS Patients Administered Second-Line ART in Rural Areas of China: A Retrospective Cohort Study Based on Real-World Data

Objectives

Chinese medicine (CM) improves the symptoms of patients with acquired immune deficiency syndrome (AIDS) and prolongs their survival. This real-world study aimed to evaluate the effects of CM on the survival of AIDS patients administered second-line antiretroviral therapy (ART).

Methods

We conducted a retrospective cohort study of the medical records of patients with AIDS who switched to second-line ART between January 2009 and December 2014. Patients were divided into ART and CM + ART groups. Propensity score matching (PSM) was performed to correct for biases between groups. Kaplan–Meier analysis and the log-rank test were used to compare survival rates, and Cox regression models were employed to identify factors significantly associated with survival.

Results

The study population (n = 4180) was comprised of the CM + ART group (n = 855) and the ART group (n = 3325). After 1 : 2 PSM, 855 patients in the CM + ART group and 1699 in the ART group were selected for analysis. Patients in the CM + ART group were followed for 4246.8 person-years, and the mortality rate was 2.12/100 person-years. Patients in the ART group were followed for 8381.2 person-years, and the mortality rate was 2.91/100 person-years. Cox regression model analysis revealed that patients in the CM + ART group survived significantly longer than those in the ART group (hazard ratio: 0.73 and 95% confidence interval: 0.57–0.93). Gender, age, symptoms, CD4 cell counts, and viral loads were independently associated with the survival of AIDS patients treated with second-line ART.

Conclusions

CM significantly improved the survival rate of AIDS patients treated with second-line ART.

Longitudinal Methods for Modeling Exposures in Pharmacoepidemiologic Studies in Pregnancy

In many perinatal pharmacoepidemiologic studies, exposure to a medication is classified as "ever exposed" versus "never exposed" within each trimester or even over the entire pregnancy. This approach is often far from real-world exposure patterns, may lead to exposure misclassification, and does not to incorporate important aspects such as dosage, timing of exposure, and treatment duration. Alternative exposure modeling methods can better summarize complex, individual-level medication use trajectories or time-varying exposures from information on medication dosage, gestational timing of use, and frequency of use. We provide an overview of commonly used methods for more refined definitions of real-world exposure to medication use during pregnancy, focusing on the major strengths and limitations of the techniques, including the potential for method-specific biases. Unsupervised clustering methods, including k-means clustering, group-based trajectory models, and hierarchical cluster analysis, are of interest because they enable visual examination of medication use trajectories over time in pregnancy and complex individual-level exposures, as well as providing insight into comedication and drug-switching patterns. Analytical techniques for time-varying exposure methods, such as extended Cox models and Robins' generalized methods, are useful tools when medication exposure is not static during pregnancy. We propose that where appropriate, combining unsupervised clustering techniques with causal modeling approaches may be a powerful approach to understanding medication safety in pregnancy, and this framework can also be applied in other areas of epidemiology.

Prevalence of Avoidable and Bias-Inflicting Methodological Pitfalls in Real-World Studies of Medication Safety and Effectiveness

Many real-word evidence (RWE) studies that utilize existing healthcare data to evaluate treatment effects incur substantial but avoidable bias from methodologically flawed study design; however, the extent of preventable methodological pitfalls in current RWE is unknown. To characterize the prevalence of avoidable methodological pitfalls with potential for bias in published claims-based studies of medication safety or effectiveness, we conducted an English-language search of PubMed for articles published from January 1, 2010 to May 20, 2019 and randomly selected 75 studies (10 case-control and 65 cohort studies) that evaluated safety or effectiveness of cardiovascular, diabetes, or osteoporosis medications using US health insurance claims. General and methodological study characteristics were extracted independently by two reviewers, and potential for bias was assessed across nine bias domains. Nearly all studies (95%) had at least one avoidable methodological issue known to incur bias, and 81% had potentially at least one of the four issues considered major due to their potential to undermine study validity: time-related bias (57%), potential for depletion of outcome-susceptible individuals (44%), inappropriate adjustment for postbaseline variables (41%), or potential for reverse causation (39%). The median number of major issues per study was 2 (interquartile range (IQR), 1-3) and was lower in cohort studies with a new-user, active-comparator design (median 1, IQR 0-1) than in cohort studies of prevalent users with a nonuser comparator (median 3, IQR 3-4). Recognizing and avoiding known methodological study design pitfalls could substantially improve the utility of RWE and confidence in its validity.

Aspirin, metformin, and statin use on the risk of gastric cancer: A nationwide population-based cohort study in Korea with systematic review and meta-analysis

BACKGROUND/AIMS

Although several chemopreventive drugs against gastric cancer have been proposed, their effects have not been fully evaluated. We examined the impacts of aspirin, metformin, and statin use on gastric cancer development in a population-based cohort in Korea.

METHODS

We analyzed the association between potential chemopreventive drugs-aspirin, metformin, and statin-and gastric cancer through the Observational Medical Outcomes Partnership Common Data Model-based Korean nationwide cohort. Use of aspirin, metformin, and statin was defined by ≥365 days of prescriptions for each drug in the general population. To summarize the current evidence, we further performed a systematic review and meta-analysis of the impact of aspirin, metformin, and statin on gastric cancer development.

RESULTS

After propensity score matching, 31,839, 6764, and 10,251 subjects were observed for medians of 4.7, 4.2, and 4.2 years for aspirin, metformin, and statin analysis, respectively. Use of aspirin or statin was associated with lower risks of gastric cancer compared to their non-use, respectively (hazard ratio [HR] [95% confidence interval [CI]]: aspirin, 0.72 [0.60-0.85], p < 0.01; statin, 0.67 [0.49-0.92], p = 0.01). However, no association was observed between metformin use and gastric cancer development (HR [95% CI]: 0.85 [0.59-1.23], p = 0.40). A subgroup of subjects with diabetes mellitus showed a lower risk of gastric cancer development with statin use. The meta-analysis showed the highest effect size of gastric cancer development for statin, followed by aspirin and metformin.

CONCLUSIONS

Statin and aspirin use were associated with significantly reduced risks of gastric cancer development, while the use of metformin was not associated with the gastric cancer risk. The protective effect of statin against gastric cancer was also significant in patients with diabetes mellitus.

Analysing and reporting of observational data: a systematic review informing the EULAR points to consider when analysing and reporting comparative effectiveness research with observational data in rheumatology

OBJECTIVES

To evaluate the analysis and reporting of comparative effectiveness research with observational data in rheumatology, informing European Alliance of Associations for Rheumatology points to consider.

METHODS

We performed a systematic literature review searching Ovid MEDLINE for original articles comparing drug effectiveness in longitudinal observational studies, published in key rheumatology journals between 2008 and 2019. The extracted information focused on reporting and types of analyses. We evaluated if year of publication impacted results.

RESULTS

From 9969 abstracts reviewed, 211 articles fulfilled the inclusion criteria. Ten per cent of studies did not adjust for confounding factors. Some studies did not explain how they chose covariates for adjustment (9%), used bivariate screening (21%) and/or stepwise selection procedures (18%). Only 33% studies reported the number of patients lost to follow-up and 25% acknowledged attrition (drop-out or treatment cessation). To account for attrition, studies used non-responder imputation, followed by last observation carried forward (LOCF) and complete case (CC) analyses. Most studies did not report the number of missing data on covariates (83%), and when addressed, 49% used CC and 11% LOCF. Date of publication did not influence the results.

CONCLUSION

Most studies did not acknowledge missing data and attrition, and a tenth did not adjust for any confounding factors. When attempting to account for them, several studies used methods which potentially increase bias (LOCF, CC analysis, bivariate screening…). This study shows that there is no improvement over the last decade, highlighting the need for recommendations for the assessment and reporting of comparative drug effectiveness in observational data in rheumatology.

Association between proton pump inhibitor use and gastric cancer: a population-based cohort study using two different types of nationwide databases in Korea

OBJECTIVE

The association between proton pump inhibitor (PPI) use and gastric cancer related to Helicobacter pylori eradication has not been fully investigated in geographical regions with high risk of gastric cancer. We aimed to evaluate the association between PPIs and gastric cancer in Korea.

DESIGN

This study analysed the original and common data model versions of the Korean National Health Insurance Service database from 2002 to 2013. We compared the incidence rates of gastric cancer after 1-year drug exposure, between new users of PPIs and other drugs excluding PPIs, by Cox proportional hazards model. We also analysed the incidence of gastric cancer among PPI users after H. pylori eradication.

RESULTS

The analysis included 11 741 patients in matched PPI and non-PPI cohorts after large-scale propensity score matching. During a median follow-up of 4.3 years, PPI use was associated with a 2.37-fold increased incidence of gastric cancer (PPI≥30 days vs non-PPI; 118/51 813 person-years vs 40/49 729 person-years; HR 2.37, 95% CI 1.56 to 3.68, p=0.001). The incidence rates of gastric cancer showed an increasing trend parallel to the duration of PPI use. In H. pylori-eradicated subjects, the incidence of gastric cancer was significantly associated with PPI use over 180 days compared with the non-PPI group (PPI≥180 days vs non-PPI; 30/12 470 person-years vs 9/7814 person-years; HR 2.22, 95% CI 1.05 to 4.67, p=0.036).

CONCLUSION

PPI use was associated with gastric cancer, regardless of H. pylori eradication status. Long-term PPIs should be used with caution in high-risk regions for gastric cancer.

Looking in the medicine cabinet: methods for using real-world data to assess the impact of measles, mumps and rubella (MMR) and recombinant adjuvanted varicella-zoster vaccines on coronavirus disease 2019 (COVID-19) prevention and case fatality

Background: Analysis of real-world data can be used to identify promising leads and dead ends among products being repurposed for clinical practice for coronavirus disease 2019 (COVID-19).  This paper uses real-world data from Cerner Labs collected from 90 source institutions in the United States to assess the potential impact of two viral vaccines on COVID-19 case fatality rates. Methods: We identified 373,032 polymerase chase reaction (PCR)-positive COVID-19 cases in the Cerner Labs database between 01-MAR-2020 and 31-DEC-2020 and identified patients that had received measles, mumps and rubella (MMR) or a recombinant adjuvanted varicella-zoster vaccine within the previous 5 years. We calculated heterogeneity scores to support interpretation of results across institutions, and used stepwise forward variable selection to construct covariable-based propensity scores. These scores were used to match cases and control for biasing and confounding issues inherent in observational data. Results: Neither the recombinant adjuvanted varicella-zoster vaccine nor MMR showed significant efficacy in prevention of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We could not derive clinically significant results on the impact of MMR for case fatality rates due to persistently high rates of heterogeneity between institutions. However, we were able to achieve acceptable levels of heterogeneity for the analysis of the recombinant adjuvanted varicella-zoster vaccine, and found a clinically meaningful benefit of reduced case fatality rate, with an odds ratio of 0.43 (95% confidence interval [CI]: 0.38 – 0.48). Conclusions: Using propensity score matching and heterogeneity statistics can help guide our interpretation of real-world data, and rigorous statistical methods are needed to reduce bias or disparities in data interpretation. Applying these methods to the impact of viral vaccines on COVID-19 case fatalities yields actionable findings for further analysis.

Association of Adverse Events with Antibiotic Treatment for Urinary Tract Infection

BACKGROUND

Little is known about the relative harms of different antibiotic regimens prescribed to treat uncomplicated urinary tract infection (UTI). We sought to compare the risk of adverse events associated with commonly-used oral antibiotic regimens for the outpatient treatment of uncomplicated UTI.

METHODS

We identified 1,169,033 otherwise healthy, non-pregnant women aged 18-44 years with uncomplicated UTI who initiated an oral antibiotic with activity against common uropathogens from July 1, 2006 to September 30, 2015. We used propensity score-weighted Kaplan-Meier methods and Cox proportional hazards regression models to estimate the association between antibiotic agent and adverse events.

RESULTS

Of two first-line agents, TMP/SMX (versus nitrofurantoin) was associated with higher risk of several adverse drug events including hypersensitivity reaction (hazard ratio [HR] 2.62, 95% CI 2.30-2.98), acute renal failure (HR 2.56, 95% CI 1.55-4.25), skin rash (HR 2.42, 95% CI 2.13-2.75), urticaria (HR 1.37, 95% CI 1.19-1.57), abdominal pain (HR 1.14, 95% CI 1.09-1.19), and nausea / vomiting (HR 1.18, 95% CI 1.10-1.28), but similar risk of potential microbiome-related adverse events. Compared to nitrofurantoin, non-first-line agents were associated with higher risk of several adverse drug events and potential microbiome-related adverse events including non-C. difficile diarrhea, C. difficile infection, vaginitis / vulvovaginal candidiasis, and pneumonia. Treatment duration modified the risk of potential microbiome-related adverse events.

CONCLUSIONS

The risks of adverse drug events and potential microbiome-related events differ widely by antibiotic agent and duration. These findings underscore the utility of using real-world data to fill evidentiary gaps related to antibiotic safety.

Consistent use of lipid lowering therapy in HIV infection is associated with low mortality

BACKGROUND

In people living with HIV (PLWH), statins may be disproportionately effective but remain underutilized. A large prospective trial in patients with low to moderate cardiovascular (ASCVD) risk will reveal whether they should be considered in all PLWH. But its effect size may not apply to real-world PLWH with higher ASCVD and mortality risk. Also, the clinical role of non-statin lipid-lowering therapy (LLT) and LLT adherence in this population is unknown.

METHODS

Comparative multi-level marginal structural model for all-cause mortality examining four time-updated exposure levels to LLT, antihypertensives, and aspirin in a virtual cohort of older PLWH. Incident coronary, cerebrovascular, and overall ASCVD events, serious infections, and new cancer diagnoses served as explanatory outcomes.

RESULTS

In 23,276 HIV-infected US-veterans who were followed for a median of 5.2 years after virologic suppression overall mortality was 33/1000 patient years: > 3 times higher than in the US population. Use of antihypertensives or aspirin was associated with increased mortality. Past LLT use (> 1 year ago) had no effect on mortality. LLT exposure in the past year was associated with a reduced hazard ratio (HR) of death: 0.59, 95% confidence interval (CI) 0.51-0.69, p < 0.0001 for statin containing LLT and 0.71 (CI: 0.54-0.93), p = 0.03 for statin-free LLT. For consistent LLT use (> 11/12 past months) the HR of death was 0.48 (CI: 0.35-0.66) for statin-only LLT, 0.34 (CI: 0.23-0.52) for combination LLT, and 0.27 (CI: 0.15-0.48) for statin-free LLT (p < 0.0001 for all). The ASCVD risk in these patients was reduced in similar fashion. Use of statin containing LLT was also associated with reduced infection and cancer risk. Multiple contrasting subgroup analyses yielded comparable results. Confounding is unlikely to be a major contributor to our findings.

CONCLUSIONS

In PLWH, ongoing LLT use may lead to substantially lower mortality, but consistent long-term adherence may be required to reduce ASCVD risk. Consistent non-statin LLT may be highly effective and should be studied prospectively.

A Narrative Review of Methods for Causal Inference and Associated Educational Resources

BACKGROUND AND OBJECTIVES

Root cause analysis involves evaluation of causal relationships between exposures (or interventions) and adverse outcomes, such as identification of direct (eg, medication orders missed) and root causes (eg, clinician's fatigue and workload) of adverse rare events. To assess causality requires either randomization or sophisticated methods applied to carefully designed observational studies. In most cases, randomized trials are not feasible in the context of root cause analysis. Using observational data for causal inference, however, presents many challenges in both the design and analysis stages. Methods for observational causal inference often fall outside the toolbox of even well-trained statisticians, thus necessitating workforce training.

METHODS

This article synthesizes the key concepts and statistical perspectives for causal inference, and describes available educational resources, with a focus on observational clinical data. The target audience for this review is clinical researchers with training in fundamental statistics or epidemiology, and statisticians collaborating with those researchers.

RESULTS

The available literature includes a number of textbooks and thousands of review articles. However, using this literature for independent study or clinical training programs is extremely challenging for numerous reasons. First, the published articles often assume an advanced technical background with different notations and terminology. Second, they may be written from any number of perspectives across statistics, epidemiology, computer science, or philosophy. Third, the methods are rapidly expanding and thus difficult to capture within traditional publications. Fourth, even the most fundamental aspects of causal inference (eg, framing the causal question as a target trial) often receive little or no coverage. This review presents an overview of (1) key concepts and frameworks for causal inference and (2) online documents that are publicly available for better assisting researchers to gain the necessary perspectives for functioning effectively within a multidisciplinary team.

CONCLUSION

A familiarity with causal inference methods can help risk managers empirically verify, from observed events, the true causes of adverse sentinel events.

Improving rheumatoid arthritis comparative effectiveness research through causal inference principles: systematic review using a target trial emulation framework

OBJECTIVES

Target trial emulation is an intuitive design framework that encourages investigators to formulate their comparative effectiveness research (CER) question as a hypothetical randomised controlled trial (RCT). Our aim was to systematically review CER studies in rheumatoid arthritis (RA) to provide examples of design limitations that could be avoided using target trial emulation, and how these limitations might introduce bias.

METHODS

We searched for head-to-head CER studies of biologic disease modifying anti-rheumatic drugs (DMARDs) in RA. Study designs were reviewed for seven components of the target trial emulation framework: eligibility criteria, treatment strategies, assignment procedures, follow-up period, outcome, causal contrasts of interest (ie, intention-to-treat (ITT) or per-protocol effect) and analysis plan. Hypothetical trials corresponding to the reported methods were assessed to identify design limitations that would have been avoided with an explicit target trial protocol. Analysis of the primary effectiveness outcome was chosen where multiple analyses were performed.

RESULTS

We found 31 CER studies, of which 29 (94%) had at least one design limitation belonging to seven components. The most common limitations related to: (1) eligibility criteria: 19/31 (61%) studies used post-baseline information to define baseline eligibility; (2) causal contrasts: 25 (81%) did not define whether ITT or per-protocol effects were estimated and (3) assignment procedures: 13 (42%) studies did not account for confounding by indication or relied solely on statistical confounder selection.

CONCLUSIONS

Design limitations were found in 94% of observational CER studies in RA. Target trial emulation is a structured approach for designing observational CER studies that helps to avoid potential sources of bias.