Chemotherapy is the main treatment for diffuse large B-cell lymphoma (DLBCL); yet 30-40% of patients are considered relapsed or refractory (R/R) to initial therapy and have second-line therapy (2 L). There is a need to study real-world outcomes to address the changing treatment landscape for R/R DLBCL patients. This study examined treatment patterns, healthcare utilization and costs, and survival among Medicare R/R DLBCL patients from 2016 to 2022. Study patients (n = 3,191) were an average of 75.7 years old and only 30.6% of patients initiated 3 L. Patients with 3 L incurred higher costs ($15,133 per-patient per-month [PPPM]) than all patients ($9,487 PPPM). Half of patients died within 6.7 months from start of 2 L. Patients with older age and elevated comorbidity burden had significantly shorter survival times within 3 years after 2 L initiation. Our analyses indicate a high disease burden among R/R DLBCL patients, highlighting the need for new treatments.

One obstacle to adopting instrumental variable (IV) methods in pharmacoepidemiology is their reliance on strong, unverifiable assumptions. We can falsify IV assumptions by leveraging the causal structure, which can strengthen or refute their plausibility and increase the validity of effect estimates. We illustrate a systematic approach to evaluate calendar-time IV assumptions in estimating the known effect of thiazolidinediones on hospitalized heart failure. Using cohort entry time before and after September 2010, when the US Food and Drug Administration issued a safety communication, as a proposed IV, we estimated IV and propensity score-weighted 2-year risk differences (RDs) using Medicare data (2008-2014). We (1) performed inequality tests, (2) identified the negative control IV/outcome using causal assumptions, (3) estimated RDs after narrowing the calendar time range and excluding patients likely associated with unmeasured confounding, (4) derived bounds for RDs, and (5) estimated the proportion of compliers and their characteristics. The findings revealed that IV assumptions were violated and RDs were extreme, but the assumptions became more plausible upon narrowing the calendar time range and restricting the cohort by excluding prevalent heart failure (the strongest measured predictor of outcome). Systematically evaluating IV assumptions could help detect bias in IV estimators and increase their validity.This article is part of a Special Collection on Pharmacoepidemiology.

Background: A growing interest in long-term sequelae of COVID-19 has prompted several systematic literature reviews (SLRs) to evaluate long-COVID-19 effects. However, many of these reviews lack in-depth information on the timing, duration, and severity of these conditions. Objectives: Our aim was to synthesize both qualitative and quantitative evidence on prevalence and outcomes of long-term effect of COVID-19 through an umbrella review. Design: Umbrella review of relevant SLRs on long-COVID-19 in terms of prolonged symptoms and clinical conditions, and comprehensively synthesized the latest existing evidence. Data Sources and Methods: We systematically identified and appraised prior systematic reviews/meta-analyses using MEDLINE, Embase, and Cochrane database of systematic review from 2020 to 2021 following the preferred reporting items for systematic reviews and meta-analyses guidance. We summarized and categorized all relevant clinical symptoms and outcomes in adults with COVID-19 using the Medical Dictionary for Regulatory Activities System Organ Class (MedDRA SOC). Results: We identified 967 systematic reviews/meta-analyses; 36 were retained for final data extraction. The most prevalent SOC were social circumstances (40%), blood and lymphatic system disorders (39%), and metabolism and nutrition disorder (38%). The most frequently reported SOC outcomes within each MedDRA category were poor quality of life (59%), wheezing and dyspnea (19−49%), fatigue (30−64%), chest pain (16%), decreased or loss of appetite (14–17%), abdominal discomfort or digestive disorder (12−18%), arthralgia with or without myalgia (16–24%), paresthesia (27%) and hair loss (14–25%), and hearing loss or tinnitus (15%). Conclusion: This study confirmed a high prevalence of several long COVID-19 outcomes according to the MedDRA categories and indicated that the majority of evidence was rated as moderate to low. Registration: The review was registered at PROSPERO ( https://www.crd.york.ac.uk/prospero/ ) (CRD42022303557).

During the coronavirus disease 2019 (COVID-19) pandemic, the urgency for updated evidence to inform public health and clinical care placed systematic literature reviews (SLRs) at the cornerstone of research. We aimed to summarize evidence on prognostic factors for COVID-19 outcomes through published SLRs and to critically assess quality elements in the findings' interpretation. An umbrella review was conducted via electronic databases from January 2020 to April 2022. All SLRs (and meta-analyses) in English were considered. Data screening and extraction were conducted by two independent reviewers. AMSTAR 2 tool was used to assess SLR quality. The study was registered with PROSPERO (CRD4202232576). Out of 4,564 publications, 171 SLRs were included of which 3 were umbrella reviews. Our primary analysis included 35 SLRs published in 2022, which incorporated studies since the beginning of the pandemic. Consistent findings showed that, for adults, older age, obesity, heart disease, diabetes, and cancer were more strongly predictive of risk of hospitalization, intensive care unit admission, and mortality due to COVID-19. Male sex was associated with higher risk of short-term adverse outcomes, but female sex was associated with higher risk of long COVID. For children, socioeconomic determinants that may unravel COVID-19 disparities were rarely reported. This review highlights key prognostic factors of COVID-19, which can help clinicians and health officers identify high-risk groups for optimal care. Findings can also help optimize confounding adjustment and patient phenotyping in comparative effectiveness research. A living SLR approach may facilitate dissemination of new findings. This paper is endorsed by the International Society for Pharmacoepidemiology.

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).

Purpose Supplementing investigator-specified variables with large numbers of empirically identified features that collectively serve as 'proxies' for unspecified or unmeasured factors can often improve confounding control in studies utilizing administrative healthcare databases. Consequently, there has been a recent focus on the development of data-driven methods for high-dimensional proxy confounder adjustment in pharmacoepidemiologic research. In this paper, we survey current approaches and recent advancements for high-dimensional proxy confounder adjustment in healthcare database studies. Methods We discuss considerations underpinning three areas for high-dimensional proxy confounder adjustment: (1) feature generation-transforming raw data into covariates (or features) to be used for proxy adjustment; (2) covariate prioritization, selection, and adjustment; and (3) diagnostic assessment. We discuss challenges and avenues of future development within each area. Results There is a large literature on methods for high-dimensional confounder prioritization/selection, but relatively little has been written on best practices for feature generation and diagnostic assessment. Consequently, these areas have particular limitations and challenges. Conclusions There is a growing body of evidence showing that machine-learning algorithms for high-dimensional proxy-confounder adjustment can supplement investigator-specified variables to improve confounding control compared to adjustment based on investigator-specified variables alone. However, more research is needed on best practices for feature generation and diagnostic assessment when applying methods for high-dimensional proxy confounder adjustment in pharmacoepidemiologic studies.

Confounding can cause substantial bias in nonexperimental studies that aim to estimate causal effects. Propensity score methods allow researchers to reduce bias from measured confounding by summarizing the distributions of many measured confounders in a single score based on the probability of receiving treatment. This score can then be used to mitigate imbalances in the distributions of these measured confounders between those who received the treatment of interest and those in the comparator population, resulting in less biased treatment effect estimates. This methodology was formalized by Rosenbaum and Rubin in 1983 and, since then, has been used increasingly often across a wide variety of scientific disciplines. In this review article, we provide an overview of propensity scores in the context of real-world evidence generation with a focus on their use in the setting of single treatment decisions, that is, choosing between two therapeutic options. We describe five aspects of propensity score analysis: alignment with the potential outcomes framework, implications for study design, estimation procedures, implementation options, and reporting. We add context to these concepts by highlighting how the types of comparator used, the implementation method, and balance assessment techniques have changed over time. Finally, we discuss evolving applications of propensity scores.

Asthma is associated with significant economic burden. Inhaled corticosteroid and long-acting beta2-agonist (ICS/LABA) combination therapies are considered mainstays of treatment. We describe real-world use of ICS/LABAs by comparing treatment persistence and adherence among patients with asthma in the United Kingdom initiating fluticasone furoate/vilanterol (FF/VI) versus budesonide/formoterol (BUD/FM) or beclometasone dipropionate/formoterol (BDP/FM). A retrospective new-user active comparator database study was conducted in the IQVIA Medical Research Database. Propensity score (PS) matching was performed for FF/VI versus BUD/FM, and FF/VI versus BDP/FM. The primary objective was to compare patient treatment persistence (time to discontinuation), while secondary objectives included assessing adherence (mean proportion of days covered [PDC] with medication in the study period) and the proportions of patients achieving ≥ 50% and ≥ 80% PDC. New users of FF/VI (N = 966), BUD/FM (N = 5931) and BDP/FM (N = 9607) were identified and PS-matched: FF/VI (n = 945) versus BUD/FM (n = 3272), and FF/VI (n = 902) versus BDP/FM (n = 3465). At 12 months, treatment persistence was 69% (FF/VI), 53% (BUD/FM) and 57% (BDP/FM). The likelihood of treatment discontinuation within 12 months after initiation with FF/VI was 35% lower than with BUD/FM and 31% lower than for BDP/FM (both p < 0.001). Mean PDC was higher for FF/VI compared with BUD/FM (77.7 vs 72.4; p < 0.0001) and BDP/FM (78.2 vs 71.0; p < 0.0001). The odds of achieving ≥ 50% and ≥ 80% PDC were greater for FF/VI than for BUD/FM and BDP/FM. In this study, patients who initiated FF/VI were less likely to discontinue treatment and showed greater treatment adherence versus patients who initiated BUD/FM or BDP/FM.

Abstract Background Data on asthma burden in pediatric patients are limited; this real‐world study investigated exacerbation frequency and health care resource utilization (HCRU) in pediatric asthma patients from the US and England. Methods Data from pediatric patients (aged 6‐17 years) in the Optum claims database (US) or Clinical Practice Research Datalink with linkage to Hospital Episode Statistics (England) were analyzed. Patients were categorized into four hierarchical groups: treated asthma (patients with ≥1 baseline asthma medication), severe asthma (plus Global Initiative for Asthma Step 4/5), severe refractory asthma ([SRA] plus ≥2 baseline severe asthma exacerbations), and eosinophilic SRA (SRA plus blood eosinophil count ≥150 cells/µL). Exacerbation frequency and HCRU during the 12 months postindex were described. Results Of 151 549 treated asthma patients in the US, 18 086 had severe asthma, 2099 SRA, and 109 eosinophilic SRA. There were 32 893 treated asthma patients in England, of whom 2711 had severe asthma, 265 SRA, and 8 eosinophilic SRA. In the 12 months postindex, ≥1 exacerbation occurred in 12.4% and 10.8% of patients with severe asthma, and 32.6% and 42.6% with SRA in the US and England, respectively. The proportions of patients with ≥1 asthma hospitalization in the 30 days after the first asthma exacerbation were 2.7% and 4.4% (treated), 3.5% and 8.2% (severe asthma), and 6.0% and 16.8% (SRA) in the US and England, respectively. Conclusion This study provides insights into current asthma management practices in the US and England and indicates that some patients with severe disease have an unmet need for effective management.

PURPOSE:To provide guidance on data linkage appropriateness and feasibility to plan purposeful and sustainable new linkages that advance pharmacoepidemiology and healthcare research. Planning a new data linkage requires careful evaluation to weigh the resources required with the potential overall benefits.METHODS:In response to an International Society for Pharmacoepidemiology (ISPE) call for manuscripts, a working group comprised of members from academic, industry, and government determined priority content areas; appropriateness and feasibility of data linkage was selected. Within this topic, scientific and operational considerations were determined, reviewed, and formulated into key areas, and translated into 12 consensus recommendations.RESULTS:Guidance for feasibility assessment was categorized into five key areas: (1) research objectives and justification; (2) data quality and completeness; (3) the linkage process; (4) data ownership and governance; and (5) overall value added by linkage. Within these key areas, recommendations to consider prior to initiation were developed to evaluate suitability of the linkage to meet research objectives, assess source data completeness and population coverage, and ensure well-defined data governance standards and protections. When creating novel linked datasets, researchers must assess the feasibility of both scientific (data quality and linkage methods) and operational (access, data use and transfer, governance, and cost) aspects.CONCLUSIONS:The data linkage feasibility assessment considerations outlined can be used as a guide when designing sustainable linked data resources to generate actionable evidence in healthcare research. These recommendations were constructed for wide applicability and can be adapted depending on the geographic, structural, and data components of the linkage.

Objectives: Using the 2016 Medicare part D coverage gap as an example, we explored effects of increased out-of-pocket costs on adherence to branded dipeptidyl peptidase-4 inhibitors (DPP-4i) in patients without financial subsidies, relative to subsidized patients who do not experience increased spending during the gap. We also explored seasonality of re-initiation, as discontinuers may be more likely to reinitiate in January when benefits reset. Methods: DPP-4i or sulfonylureas initiators, aged >66 years, from a 20% sample of 2015-2016 Medicare claims were identified. We used difference-in-differences Poisson regression to compare adherence before and after entering the coverage gap between non-subsidized and subsidized patients. Among discontinuers, monthly hazard ratios (HRs) for re-initiation relative to January 2016 were derived with Cox models. As a second control, we repeated analyses using sulfonylureas, generic low-cost alternatives. Results: In 2016, 8,096 subsidized and 6,173 non-subsidized DPP-4i initiators entered the coverage gap. Non-subsidized patients, copayment in the coverage gap was 45% ($227 per DPP-4i prescription), and adherence decreased from 68.4% to 49.0% after gap entry. Accounting for adherence differences in subsidized patients, non-subsidized patients demonstrated reduced adherence to DPP-4is [Difference-in-difference:-16.9%;CI(-18.7%,-15.1%)] but not sulfonylureas [-1.6%(-3.4%,0.2%)]. Re-initiation was lowest in the months before January (HR=0.4-0.5) among non-subsidized DPP-4i patients, demonstrating a strong seasonal pattern. Conclusions: Increased out-of-pocket costs negatively affect adherence and re-initiation of branded antihyperglycemic drugs among patients without financial subsidies. Despite closure of the coverage gap, affordability remains a concern given increasing list prices for many drugs on Medicare and the growing use of deductibles and coinsurance by commercial health plans.

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.

Aim The aim of the study was to empirically demonstrate the effect of varying study designs when evaluating the safety of pioglitazone in treating bladder cancer. Methods We identified Medicare beneficiaries above 65 years of age with diabetes between 2008 and 2015 and with classified exposure (at least two claims within 180 days) to glucose-lowering drugs (GLD), pioglitazone or another drug. The effects of varying the following study design parameters on bladder cancer risk were assessed: use of a new vs existing drug, choice of referent (all non-users and users of GLDs, non-insulin GLDs and DPP-4s) and whether or not censoring accounted for treatment change. We used the Cox proportional hazards model to obtain adjusted HRs and 95% CIs. Results We included 1,510,212 patients classified as pioglitazone users (N = 135,188) or non-users (N = 1,375,024). Users had more diabetic complications than non-users, but fewer than insulin users. The HR ranged from 1.10 (1.01-1.20) to 1.13 (0.99-1.29) when censoring ignored treatment change, suggesting a weak association or none between pioglitazone and bladder cancer, probably under-estimating risk. However, the HR was 1.20 (1.01-1.42) when cohorts were restricted to new users, censored upon treatment change, and when DPP-4 was used as the referent, suggesting an increased risk of bladder cancer associated with pioglitazone. Conclusions The continued demand for new GLDs indicates the need for more robust observational methods to improve the value of generating real-world evidence in equipping clinicians to make informed prescribing decisions. Although there is no one-size-fits-all approach, we recommend active comparator new user study designs that compare therapeutically equivalent drugs and account for treatment changes during follow-up to present the least biased comparative safety estimates.

Objective To estimate the prevalence and associated disease burden of eosinophilic granulomatosis with polyangiitis (EGPA) in patients with asthma from a US claims database. Methods Two cohorts were defined using enrollees (aged >= 18 years) from the Optum deidentified Clinformatics Datamart claims database 2010-2014, based on validated EGPA case definitions with varying specificity: EGPA 1 (main cohort; more specific; patients with 2 codes [in any combination] within 12 months of each other for eosinophilia, vasculitis, or mononeuritis multiplex) and EGPA 2 (sensitivity analysis cohort; less specific; patients with 2 codes of above conditions and/or neurologic symptoms within 12 months of each other). Patients had 3 or more asthma medications in the 12-month baseline before index date (date of the second code). Eosinophilic granulomatosis with polyangiitis prevalence, asthma severity during the baseline period, oral corticosteroid (OCS) use, and health care utilization during the 12-month follow-up period were determined. Results Overall, 88 and 604 patients were included in main cohort EGPA 1 and sensitivity analysis cohort EGPA 2, respectively; corresponding annual EGPA prevalence rates were 3.2 to 5.9 and 23.4 to 30.7 cases/million patients. Approximately 75% of patients were prescribed OCS and similar to 30% experienced 1 or more hospitalization; 75% in EGPA 1 and 52% in EGPA 2 with 1 or more non-OCS prescription in the 90 days before index date had severe asthma. Conclusions Eosinophilic granulomatosis with polyangiitis prevalence estimates varied based on specificity of the case definition but were generally consistent with previous country-specific estimates. Despite differences in prevalence, both cohorts displayed a generally similar, high burden of OCS use and health care utilization, highlighting the substantial disease burden among patients with EGPA and the need for specific treatments.

Aims To examine the outcomes of dipeptidyl peptidase-4 (DPP-4) inhibitor initiation with and without concurrent metformin treatment. Materials and methods We identified Medicare enrollees initiating a DPP-4 inhibitor, a sulphonylurea or a thiazolidinedione. Using propensity-score-weighted Poisson models, we evaluated 1-year cardiovascular (CV) outcome incidence among initiators of DPP-4 inhibitors versus comparators in subgroups with and without concurrent metformin use, and assessed the interaction between initiation drug and metformin. Outcomes included mortality, non-fatal myocardial infarction (MI), stroke, and a composite outcome. Results For the DPP-4 inhibitor (n = 13 391) versus sulphonylurea (n = 33 206) comparison, rate differences in composite outcome incidence favoured DPP-4 inhibitors: -2.0/100 person-years among metformin users (95% confidence interval [CI] -2.7 to -1.3) and - 1.0/100 person-years (95% CI -1.8 to -0.2) among metformin non-users. Similar rate difference trends among metformin users and non-users were seen for mortality (-1.5/100 person-years [95% CI -2.1 to -0.9] and -0.7/100 person-years [95% CI -1.4 to 0.0]) and non-fatal MI (-0.5/100 person-years [95% CI -0.8, -0.3] and 0.1/100 person-years [95% CI -0.2 to 0.4]). The interaction between DPP-4 inhibitor initiation and metformin was statistically significant for non-fatal MI (P = 0.008). For the DPP-4 inhibitor (n = 22 210) versus thiazolidinedione (n = 9517) comparison, rate differences in composite outcome incidence for DPP-4 inhibitor initiation were -0.6/100 person-years (95% CI -1.5 to 0.2) among metformin users and 1.0 (95% CI 0.0 to 2.0) among metformin non-users. Similar rate difference trends among metformin users and non-users were seen for mortality (-0.5/100 person-years [95% CI -1.3 to 0.1] and 0.8/100 person-years [95% CI -0.0 to 1.7]) and non-fatal MI (-0.1/100 person-years [95% CI -0.4 to 0.2] and 0.2/100 person-years [95% CI -0.1 to 0.6]). The interaction between DPP-4 inhibitor initiation and metformin was statistically significant for the composite outcome (P = 0.024) and mortality (P = 0.023). Conclusion Incidence rate differences in multiple CV outcomes appeared more favourable when DPP-4 inhibitor initiation occurred in the presence of metformin, suggesting a possible interaction between DPP-4 inhibitors and metformin.

ObjectiveIn recent years, second-line diabetes treatment with dipeptidyl peptidase-4 inhibitors (DPP-4i) increased with a corresponding decrease in thiazolidinediones (TZDs). Using hospitalization for heart failure (HF) as a positive control outcome, we explored the use of calendar time as an instrumental variable (IV) and compared this approach to an active comparator new-user study. MethodsWe identified DPP-4i or TZD initiators after a 6-month washout using Medicare claims 2006-2013. The IV was defined as a binary variable comparing initiators during October 2010 to December 2013 (postperiod) versus January 2008 to May 2010 (preperiod). We examined IV strength and estimated risk differences (RDs) for HF using Kaplan-Meier curves, which were compared with propensity score (PS)-weighted RD for DPP-4i versus TZD. ResultsThe IV compared 22 696 initiators (78% DPP-4i) in the postperiod versus 20 283 initiators (38% DPP-4i) in the preperiod, resulting in 40% compliance. The active-comparator (PS-weighted) approach compared 26198 DPP-4i and 18842 TZD initiators. Covariate balance across IV levels was slightly better than across treatments (standardized difference, 3% vs 4.5%). The 1- and 2-year local average treatment effects of RD of HF per 100 patients in the compliers (95% confidence intervals) were -0.62 (-0.99 to -0.25) and -0.88 (-1.46 to -0.25). Corresponding PS-weighted results were -0.20 (-0.33 to -0.05) and -0.18 (-0.30 to 0.03). ConclusionBoth approaches indicated lesser risk of HF hospitalizations among DPP-4i vs TZD initiators. The magnitude of the estimated effects may differ due to differences in the target populations and assumptions. Calendar time can be leveraged as an IV when market dynamics lead to profound changes in treatments.