Effectiveness and safety of empagliflozin: final results from the EMPRISE study.

AIMS/HYPOTHESIS: Limited evidence exists on the comparative safety and effectiveness of empagliflozin against alternative glucose-lowering medications in individuals with type 2 diabetes with the broad spectrum of cardiovascular risk. The EMPagliflozin compaRative effectIveness and SafEty (EMPRISE) cohort study was designed to monitor the safety and effectiveness of empagliflozin periodically for a period of 5 years with data collection from electronic healthcare databases. METHODS: We identified individuals ≥18 years old with type 2 diabetes who initiated empagliflozin or dipeptidyl peptidase-4 inhibitors (DPP-4i) from 2014 to 2019 using US Medicare and commercial claims databases. After 1:1 propensity score matching using 143 baseline characteristics, we identified four a priori-defined effectiveness outcomes: (1) myocardial infarction (MI) or stroke; (2) hospitalisation for heart failure (HHF); (3) major adverse cardiovascular events (MACE); and (4) cardiovascular mortality or HHF. Safety outcomes included lower-limb amputations, non-vertebral fractures, diabetic ketoacidosis (DKA), acute kidney injury (AKI), severe hypoglycaemia, retinopathy progression, and short-term kidney and bladder cancers. We estimated HRs and rate differences (RDs) per 1000 person-years, overall and stratified by age, sex, baseline atherosclerotic cardiovascular disease (ASCVD) and heart failure. RESULTS: We identified 115,116 matched pairs. Compared with DPP-4i, empagliflozin was associated with lower risks of MI/stroke (HR 0.88 [95% CI 0.81, 0.96]; RD -2.08 [95% CI (-3.26, -0.90]), HHF (HR 0.50 [0.44, 0.56]; RD -5.35 [-6.22, -4.49]), MACE (HR 0.73 [0.62, 0.86]; RD -6.37 [-8.98, -3.77]) and cardiovascular mortality/HHF (HR 0.57 [0.47, 0.69]; RD -10.36 [-12.63, -8.12]). Absolute benefits were larger in older individuals and in those with ASCVD/heart failure. Empagliflozin was associated with an increased risk of DKA (HR 1.78 [1.44, 2.19]; RD 1.59 [1.08, 2.09]); decreased risks of AKI (HR 0.62 [0.54, 0.72]; RD -2.39 [-3.08, -1.71]), hypoglycaemia (HR 0.75 [0.67, 0.84]; RD -2.46 [-3.32, -1.60]) and retinopathy progression (HR 0.78 [0.63, 0.96)]; RD -9.49 [-16.97, -2.10]); and similar risks of other safety events. CONCLUSIONS/INTERPRETATION: Empagliflozin relative to DPP-4i was associated with risk reductions of MI or stroke, HHF, MACE and the composite of cardiovascular mortality or HHF. Absolute risk reductions were larger in older individuals and in those who had history of ASCVD or heart failure. Regarding the safety outcomes, empagliflozin was associated with an increased risk of DKA and lower risks of AKI, hypoglycaemia and progression to proliferative retinopathy, with no difference in the short-term risks of lower-extremity amputation, non-vertebral fractures, kidney and renal pelvis cancer, and bladder cancer.

Invited commentary: A future of data-rich pharmacoepidemiology studies- transitioning to large-scale linked EHR+claims data.

Electronic health record (EHR) data are seen as an important source for Pharmacoepidemiology studies. In the US healthcare system, EHR systems often only identify fragments of patients' health information across the care continuum, including primary care, specialist care, hospitalizations, and pharmacy dispensing. This leads to unobservable information in longitudinal evaluations of medication effects causing unmeasured confounding, misclassification, and truncated follow-up times. A remedy is to link EHR data with longitudinal claims data which record all encounters during a defined enrollment period across all care settings. We evaluate EHR and claims data sources in three aspects relevant to etiologic studies of medical products: data continuity, data granularity, and data chronology. Reflecting on the strengths and limitations of EHR and insurance claims data, it becomes obvious that they complement each other. The combination of both will improve the validity of etiologic studies and expand the range of questions that can be answered. As the research community transitions towards a future state with access to large-scale combined EHR+claims data, we outline analytic templates to improve the validity and broaden the scope of pharmacoepidemiology studies in the current environment where EHR data are available only for a subset of patients with claims data.

Emulating Randomized Trials by Observational Database Studies: The RCT-DUPLICATE Initiative in COPD and Asthma.

Observational studies are increasingly used to provide real-world evidence in regulatory decision-making. The RCT-DUPLICATE initiative conducted observational studies emulating two trials in patients with asthma and three in COPD. For each trial, new-user cohorts were constructed from two US healthcare claims databases, comparing initiators of the study and comparator drugs, matched on propensity scores. Proportional hazards models were used to compare the treatments on study outcomes. The observational studies involved more subjects than the corresponding trials, with treatment arms well-matched on baseline characteristics. An asthma example involved emulation of the 26-week FDA-mandated D5896 trial. With 6,494 asthma patients per arm, the hazard ratio (HR) of a serious asthma-related event with budesonide-formoterol versus budesonide was 1.29 (95% CI: 0.63-2.65), compared with 1.07 (95% CI: 0.70-1.65) in the trial. A COPD example is the emulation of the one-year IMPACT trial. With 4,365 COPD patients per arm, the HR of a COPD exacerbation with triple therapy versus dual bronchodilators was 1.08 (95% CI: 1.00-1.17), compared with 0.84 (95% CI: 0.78-0.91) in the trial. We found mainly discordant results between observational analyses and randomized trials, likely from the forced discontinuation of treatments prior to randomization in the trials, not mimicable in the observational analyses.

A simulation-based bias analysis to assess the impact of unmeasured confounding when designing nonrandomized database studies.

Unmeasured confounding is often raised as a source of potential bias during the design of nonrandomized studies, but quantifying such concerns is challenging. We developed a simulation-based approach to assess the potential impact of unmeasured confounding during the study design stage. The approach involved generation of hypothetical individual-level cohorts using realistic parameters, including a binary treatment (prevalence 25%), a time-to-event outcome (incidence 5%), 13 measured covariates, a binary unmeasured confounder (u1; 10%), and a binary measured "proxy" variable (p1) correlated with u1. Strengths of unmeasured confounding and correlations between u1 and p1 were varied in simulation scenarios. Treatment effects were estimated with (1) no adjustment, (2) adjustment for measured confounders (level 1), and (3) adjustment for measured confounders and their proxy (level 2). We computed absolute standardized mean differences in u1 and p1 and relative bias with each level of adjustment. Across all scenarios, level 2 adjustment led to improvement in the balance of u1, but this improvement was highly dependent on the correlation between u1 and p1. Level 2 adjustments also had lower relative bias than level 1 adjustments (in strong u1 scenarios: relative bias of 9.2%, 12.2%, and 13.5% at correlations of 0.7, 0.5, and 0.3, respectively, vs 16.4%, 15.8%, and 15.0% for level 1). An approach using simulated individual-level data is useful to explicitly convey the potential for bias due to unmeasured confounding while designing nonrandomized studies, and can be helpful in informing design choices. This article is part of a Special Collection on Pharmacoepidemiology.

Cardiorenal effectiveness of empagliflozin vs. glucagon-like peptide-1 receptor agonists: final-year results from the EMPRISE study.

BACKGROUND: No randomized clinical trials have directly compared the cardiorenal effectiveness of empagliflozin and GLP-1RA agents with demonstrated cardioprotective effects in patients with a broad spectrum of cardiovascular risk. We reported the final-year results of the EMPRISE study, a monitoring program designed to evaluate the cardiorenal effectiveness of empagliflozin across broad patient subgroups. METHODS: We identified patients ≥ 18 years old with type 2 diabetes who initiated empagliflozin or GLP-1RA from 2014 to 2019 using US Medicare and commercial claims databases. After 1:1 propensity score matching using 143 baseline characteristics, we evaluated risks of outcomes including myocardial infarction (MI) or stroke, hospitalization for heart failure (HHF), major adverse cardiovascular events (MACE - MI, stroke, or cardiovascular mortality), a composite of HHF or cardiovascular mortality, and progression to end-stage kidney disease (ESKD) (in patients with chronic kidney disease stages 3-4). We estimated hazard ratios (HR) and rate differences (RD) per 1,000 person-years, overall and within subgroups of age, sex, baseline atherosclerotic cardiovascular disease (ASCVD), and heart failure (HF). RESULTS: We identified 141,541 matched pairs. Compared with GLP-1RA, empagliflozin was associated with similar risks of MI or stroke [HR: 0.99 (0.92, 1.07); RD: -0.23 (-1.25, 0.79)], and lower risks of HHF [HR: 0.50 (0.44, 0.56); RD: -2.28 (-2.98, -1.59)], MACE [HR: 0.90 (0.82, 0.99); RD: -2.54 (-4.76, -0.32)], cardiovascular mortality or HHF [HR: 0.77 (0.69, 0.86); RD: -4.11 (-5.95, -2.29)], and ESKD [0.75 (0.60, 0.94); RD: -6.77 (-11.97, -1.61)]. Absolute risk reductions were larger in older patients and in those with baseline ASCVD/HF. They did not differ by sex. CONCLUSIONS: The cardiovascular benefits of empagliflozin vs. cardioprotective GLP-1RA agents were larger in older patients and in patients with history of ASCVD or HF, while they did not differ by sex. In patients with advanced CKD, empagliflozin was associated with risk reductions of progression to ESKD.

Hydroxychloroquine lowers Alzheimer's disease and related dementias risk and rescues molecular phenotypes related to Alzheimer's disease.

We recently nominated cytokine signaling through the Janus-kinase-signal transducer and activator of transcription (JAK/STAT) pathway as a potential AD drug target. As hydroxychloroquine (HCQ) has recently been shown to inactivate STAT3, we hypothesized that it may impact AD pathogenesis and risk. Among 109,124 rheumatoid arthritis patients from routine clinical care, HCQ initiation was associated with a lower risk of incident AD compared to methotrexate initiation across 4 alternative analyses schemes addressing specific types of biases including informative censoring, reverse causality, and outcome misclassification (hazard ratio [95% confidence interval] of 0.92 [0.83-1.00], 0.87 [0.81-0.93], 0.84 [0.76-0.93], and 0.87 [0.75-1.01]). We additionally show that HCQ exerts dose-dependent effects on late long-term potentiation (LTP) and rescues impaired hippocampal synaptic plasticity prior to significant accumulation of amyloid plaques and neurodegeneration in APP/PS1 mice. Additionally, HCQ treatment enhances microglial clearance of Aß1-42, lowers neuroinflammation, and reduces tau phosphorylation in cell culture-based phenotypic assays. Finally, we show that HCQ inactivates STAT3 in microglia, neurons, and astrocytes suggesting a plausible mechanism associated with its observed effects on AD pathogenesis. HCQ, a relatively safe and inexpensive drug in current use may be a promising disease-modifying AD treatment. This hypothesis merits testing through adequately powered clinical trials in at-risk individuals during preclinical stages of disease progression.

Bariatric surgery and all-cause mortality: A methodological review of studies using a non-surgical comparator.

AIM: Non-randomized studies on bariatric surgery have reported large reductions in mortality within 6-12 months after surgery compared with non-surgical patients. It is unclear whether these findings are the result of bias. STUDY DESIGN AND SETTING: We searched PubMed to identify all non-randomized studies investigating the effect of bariatric surgery on all-cause mortality compared with non-surgical patients. We assessed these studies for potential confounding and time-related biases. We conducted bias analyses to quantify the effect of these biases. RESULTS: We identified 21 cohort studies that met our inclusion criteria. Among those, 11 were affected by immortal time bias resulting from the misclassification or exclusion of relevant follow-up time. Five studies were subject to potential confounding bias because of a lack of adjustment for body mass index (BMI). All studies used an inadequate comparator group that lacked indications for bariatric surgery. Bias analyses to correct for potential confounding from BMI shifted the effect estimates towards the null [reported hazard ratio (HR): 0.78 vs. bias-adjusted HR: 0.92]. Bias analyses to correct for the presence of immortal time also shifted the effect estimates towards the null (adjustment for 2-year wait time: reported HR: 0.57 vs. bias-adjusted HR: 0.81). CONCLUSION: Several important sources of bias were identified in non-randomized studies of the effectiveness of bariatric surgery versus non-surgical comparators on mortality. Future studies should ensure that confounding by BMI is accounted for, considering the choice of the comparator group, and that the design or analysis avoids immortal time bias from the misclassification or exclusion.

Emulation of randomized trials of direct oral anticoagulants with claims data and implications for new Factor XI inhibitors.

Direct oral anticoagulants (DOACs) revolutionized the management of thromboembolic disorders. Clinical care may be further improved as Factor XIs undergo large-scale outcome trials. What role can non-randomized database studies play in expediting understanding of these drugs in clinical practice? The RCT-DUPLICATIVE Initiative emulated the design of eight DOAC randomized clinical trials (RCT) using non-randomized claims database studies. RCT study design parameters and measurements were closely emulated by the database studies and produced highly concordant results. The results of the single database study that did not meet all agreement metrics with the specific RCT it was emulating were aligned with a meta-analysis of six trials studying similar questions, suggesting the trial result was an outlier. Well-designed database studies using fit-for-purpose data came to the same conclusions as DOAC trials, illustrating how database studies could complement RCTs for Factor XI inhibitors-by accelerating insights in underrepresented populations, demonstrating effectiveness and safety in clinical practice, and testing broader indications.

Stratified analysis in comparative effectiveness studies that emulate randomized trials.

PURPOSE: For observational cohort studies that employ matching by propensity scores (PS), preliminary stratification by consequential predictors of outcome better emulates stratified randomization and potentially reduces variance and bias through relaxed dependence on modeling assumptions. We assessed the impact of pre-stratification in two real-life examples. For both, prior evidence from placebo-controlled randomized clinical trials (RCTs) suggested small or no risk reduction, but observational analysis suggested protection, presumably the result of confounding bias. STUDY DESIGN AND SETTING: The study populations consisted of Medicare beneficiaries (2014-18) with type 2 diabetes initiating either (i) empagliflozin versus dipeptidyl peptidase-4 inhibitors (DPP-4i) or (ii) empagliflozin versus glucagon-like peptide-1 receptor agonists (GLP-1RA). The outcome was myocardial infarction or stroke. We estimated hazard ratios (HR) and rate differences (RD) after controlling for 143 pre-exposure covariates via 1:1 PS matching after (1) PS estimation in the total cohort (total-cohort PS-matching) and (2) PS estimation separately by baseline cardiovascular disease (stratified PS matching). RESULTS: Stratified PS matching resulted in HRs that exceeded those from total-cohort PS-matching by 13% and 9%, respectively, for the comparisons of empagliflozin to DPP-4i and GLP-1RA. Against both comparators, HRs and RDs after stratified PS matching were closer to the null, with slightly higher variances (2%-3%) than those after total-cohort PS matching. CONCLUSION: Stratified PS matching produced effect estimates closer to the expected trial findings than total-cohort PS matching. The price paid in increased variance was minimal.

Validation of alopecia coding in US claims data among women of childbearing age.

BACKGROUND: Accurately identifying alopecia in claims data is important to study this rare medication side effect. OBJECTIVES: To develop and validate a claims-based algorithm to identify alopecia in women of childbearing age. METHODS: We linked electronic health records from a large healthcare system in Massachusetts (Mass General Brigham) with Medicaid claims data from 2016 through 2018 to identify all women aged 18 to 50 years with an ICD-10 code for alopecia, including alopecia areata, androgenic alopecia, non-scarring alopecia, or cicatricial alopecia, from a visit to the MGB system. Using eight predefined algorithms to identify alopecia in Medicaid claims data, we randomly selected 300 women for whom we reviewed their charts to validate the alopecia diagnosis. Positive predictive values (PPVs) were computed for the primary algorithm and seven algorithm variations, stratified by race. RESULTS: Out of 300 patients with at least 1 ICD-10 code for alopecia in the Medicaid claims, 286 had chart-confirmed alopecia (PPV = 95.3%). The algorithm requiring two diagnosis codes plus one prescription claim for alopecia treatment identified 55 patients (PPV = 100%). The algorithm requiring 1 diagnosis code for alopecia plus 1 procedure claim for intralesional triamcinolone injection identified 35 patients (PPV = 100%). Across all 8 algorithms tested, the PPV varied between 95.3% and 100%. The PPV for alopecia ranged from 94% to 100% in White and 96%-100% in 48 non-White women. The exact date of alopecia onset was difficult to determine in charts. CONCLUSION: At least one recorded ICD-10 code for alopecia in claims data identified alopecia in women of childbearing age with high accuracy.

Sharing Is Caring? International Society for Pharmacoepidemiology Review and Recommendations for Sharing Programming Code.

PURPOSE: There is increasing recognition of the importance of transparency and reproducibility in scientific research. This study aimed to quantify the extent to which programming code is publicly shared in pharmacoepidemiology, and to develop a set of recommendations on this topic. METHODS: We conducted a literature review identifying all studies published in Pharmacoepidemiology and Drug Safety (PDS) between 2017 and 2022. Data were extracted on the frequency and types of programming code shared, and other key open science practices (clinical codelist sharing, data sharing, study preregistration, and stated use of reporting guidelines and preprinting). We developed six recommendations for investigators who choose to share code and gathered feedback from members of the International Society for Pharmacoepidemiology (ISPE). RESULTS: Programming code sharing by articles published in PDS ranged from 1.8% in 2017 to 9.5% in 2022. It was more prevalent among articles with a methodological focus, simulation studies, and papers which also shared record-level data. CONCLUSION: Programming code sharing is rare but increasing in pharmacoepidemiology studies published in PDS. We recommend improved reporting of whether code is shared and how available code can be accessed. When sharing programming code, we recommend the use of permanent digital identifiers, appropriate licenses, and, where possible, adherence to good software practices around the provision of metadata and documentation, computational reproducibility, and data privacy.

The FDA Sentinel Real World Evidence Data Enterprise (RWE-DE).

PURPOSE: The US Food and Drug Administration's Sentinel Innovation Center aimed to establish a query-ready, quality-checked distributed data network containing electronic health records (EHRs) linked with insurance claims data for at least 10 million individuals to expand the utility of real-world data for regulatory decision-making. METHODS: In this report, we describe the resulting network, the Real-World Evidence Data Enterprise (RWE-DE), including data from two commercial EHR-claims linked assets collectively termed the Commercial Network covering 21 million lives, and four academic partner institutions collectively termed the Development Network covering 4.5 million lives. RESULTS: We discuss provenance and completeness of the data converted in the Sentinel Common Data Model (SCDM), describe patient populations, and report on EHR-claims linkage characterization for all contributing data sources. Further, we introduce a standardized process to store free-text notes in the Development Network for efficient retrieval as needed. CONCLUSIONS: Finally, we outline typical use cases for the RWE-DE where it can broaden the reach of the types of questions that can be addressed by the Sentinel system.

Sodium-glucose cotransporter 2 inhibitors vs. sitagliptin in heart failure and type 2 diabetes: an observational cohort study.

AIMS: The effectiveness of sodium-glucose cotransporter 2 inhibitors (SGLT2i) in patients with heart failure (HF) in routine clinical practice is not extensively studied. This study aimed to evaluate the comparative effectiveness of SGLT2i vs. sitagliptin in older adults with HF and type 2 diabetes and to investigate whether there were any differences between agents within the SGLT2i class or for reduced and preserved ejection fraction. METHODS AND RESULTS: Using Medicare claims data (April 2013 to December 2019), 16 253 SGLT2i initiators vs. 43 352 initiators of sitagliptin aged ≥65 years with type 2 diabetes and HF were included. The primary outcome was a composite of all-cause mortality, hospitalization for HF or urgent visit requiring intravenous diuretics; secondary outcomes included its individual components. Propensity score fine stratification weighted Cox regression was used to adjust for 100 pre-exposure characteristics. Mean age was 74 years; 49.8% were women. Initiation of SGLT2i vs. sitagliptin was associated with a lower risk of the primary composite outcome [adjusted hazard ratio (HR) 0.72; 95% confidence interval 0.67-0.77]. The adjusted HRs were 0.70 (0.63-0.78) for all-cause mortality, 0.64 (0.58-0.70) for hospitalization for HF, and 0.77 (0.69-0.86) for urgent visit requiring intravenous diuretics. Similar associations with the primary composite outcome were observed for all three agents within the SGLT2i class, for reduced and preserved ejection fraction, and subgroups based on demographics, comorbidities, and other HF treatments. Bias-calibrated HRs for the primary endpoint using negative and positive control outcomes ranged between 0.81 and 0.89, suggesting that the observed benefit could not be fully explained by residual confounding. CONCLUSION: In routine US clinical practice, SGLT2i demonstrated robust clinical effectiveness in older adults with HF and type 2 diabetes compared with sitagliptin, with no evidence of heterogeneity across the SGLT2i class or across ejection fraction.

Use patterns of systemic immunomodulators in the United States before and after dupilumab approval in adults with atopic dermatitis.

PURPOSE: The patterns of dupilumab use, the first systemic drug approved for the treatment of atopic dermatitis (AD), is not well understood in the context of off-label systemic medications. OBJECTIVE: To describe patterns of prescribing, switching and discontinuing systemic AD drugs, before and after the approval of dupilumab and understand variables associated with dupilumab prescription. METHODS: Using longitudinal claims data, we identified patients with AD who initiated a systemic therapy (dupilumab, cyclosporine, methotrexate, azathioprine, mycophenolate) from March 2015 to February 2021, with a washout period of 1 year. We used Sankey plots to visualize longitudinal patterns of use at 3, 6, and 12 months and logistic regression to determine associates of dupilumab prescription. RESULTS: The number of patients starting systemic treatment increased from 319 before dupilumab approval to 1358 after. Dupilumab use increased from 72% to 84%. In 2019-2020, 36% of patients discontinued systemic treatment within a year compared to 62% in 2015-2016. 92% of patients who started dupilumab in 2020-2021 had received no other systemic treatment before. Patients <60 years and those who used steroid-sparing topical treatments were more likely to receive dupilumab. CONCLUSION: Among new users of a systemic treatment for AD, dupilumab was most used treatment by far.

Effectiveness research in oncology with electronic health record data: A retrospective cohort study emulating the PALOMA-2 trial.

PURPOSE: Oncology electronic health record (EHR) databases have increased in quality and availability over the past decade, yet it remains unclear whether these clinical practice data can be used to conduct reliable comparative effectiveness studies. We sought to emulate a clinical trial with EHR data in the advanced breast cancer population and compare our results against the trial. METHODS: This cohort study used EHR data from US oncology practices. All elements of the study were defined to mimic the PALOMA-2 trial as closely as possible. Patients with hormone-positive, HER-2 negative metastatic breast cancer with no prior treatment for metastatic disease were included. Patients initiating palbociclib and letrozole on the same day following the earliest record of metastasis were compared to those initiating letrozole only. The primary associational measure was the conditional hazard ratio for time-to-next treatment (TTNT). TTNT is well-measured in our data source and amenable for calibration against the randomized study results of the PALOMA-2 trial. We used multiple imputation for several patient characteristics with missing values. RESULTS: There were 3836 study-eligible women with advanced breast cancer. The hazard ratio for TTNT in the observational study (HR: 0.62; 95% CI: 0.56-0.68) was closely aligned with that of the randomized trial (HR: 0.64; 95% CI: 0.52-0.78). CONCLUSIONS: Under our assumptions on missing data and comparability of the two study populations, results from our non-randomized study closely matched that of the randomized trial. Further studies are needed to determine whether EHR data can yield reliable conclusions on treatment effects in oncology.

High-dimensional propensity scores for empirical covariate selection in secondary database studies: Planning, implementation, and reporting.

Real-world evidence used for regulatory, payer, and clinical decision-making requires principled epidemiology in design and analysis, applying methods to minimize confounding given the lack of randomization. One technique to deal with potential confounding is propensity score (PS) analysis, which allows for the adjustment for measured preexposure covariates. Since its first publication in 2009, the high-dimensional propensity score (hdPS) method has emerged as an approach that extends traditional PS covariate selection to include large numbers of covariates that may reduce confounding bias in the analysis of healthcare databases. hdPS is an automated, data-driven analytic approach for covariate selection that empirically identifies preexposure variables and proxies to include in the PS model. This article provides an overview of the hdPS approach and recommendations on the planning, implementation, and reporting of hdPS used for causal treatment-effect estimations in longitudinal healthcare databases. We supply a checklist with key considerations as a supportive decision tool to aid investigators in the implementation and transparent reporting of hdPS techniques, and to aid decision-makers unfamiliar with hdPS in the understanding and interpretation of studies employing this approach. This article is endorsed by the International Society for Pharmacoepidemiology.

HARmonized Protocol Template to Enhance Reproducibility of hypothesis evaluating real-world evidence studies on treatment effects: A good practices report of a joint ISPE/ISPOR task force.

PROBLEM: Ambiguity in communication of key study parameters limits the utility of real-world evidence (RWE) studies in healthcare decision-making. Clear communication about data provenance, design, analysis, and implementation is needed. This would facilitate reproducibility, replication in independent data, and assessment of potential sources of bias. WHAT WE DID: The International Society for Pharmacoepidemiology (ISPE) and ISPOR-The Professional Society for Health Economics and Outcomes Research (ISPOR) convened a joint task force, including representation from key international stakeholders, to create a harmonized protocol template for RWE studies that evaluate a treatment effect and are intended to inform decision-making. The template builds on existing efforts to improve transparency and incorporates recent insights regarding the level of detail needed to enable RWE study reproducibility. The overarching principle was to reach for sufficient clarity regarding data, design, analysis, and implementation to achieve 3 main goals. One, to help investigators thoroughly consider, then document their choices and rationale for key study parameters that define the causal question (e.g., target estimand), two, to facilitate decision-making by enabling reviewers to readily assess potential for biases related to these choices, and three, to facilitate reproducibility. STRATEGIES TO DISSEMINATE AND FACILITATE USE: Recognizing that the impact of this harmonized template relies on uptake, we have outlined a plan to introduce and pilot the template with key international stakeholders over the next 2 years. CONCLUSION: The HARmonized Protocol Template to Enhance Reproducibility (HARPER) helps to create a shared understanding of intended scientific decisions through a common text, tabular and visual structure. The template provides a set of core recommendations for clear and reproducible RWE study protocols and is intended to be used as a backbone throughout the research process from developing a valid study protocol, to registration, through implementation and reporting on those implementation decisions.

Longitudinal utilization of systemic immunomodulators before and after dupilumab approval in children with atopic dermatitis.

In our cohort study, we sought to describe the utilization patterns of systemic immunomodulators in children with atopic dermatitis (AD) and how utilization changed after approval of dupilumab, the first systemic drug approved for the treatment of AD. Using US nationwide claims data, we identified children with AD who initiated a systemic therapy (dupilumab, cyclosporine, methotrexate, azathioprine, and mycophenolate mofetil) from March 2015 to February 2021 and used Sankey plots to describe patterns of starting, switching, and discontinuing these drugs. Dupilumab use among children increased from 19.4% before approval in children to 88.3% after approval in 2019-20. Adherence to dupilumab may suggest better tolerance and improved outcomes in children with AD.

Cardiovascular Outcomes in Patients Initiating First-Line Treatment of Type 2 Diabetes With Sodium-Glucose Cotransporter-2 Inhibitors Versus Metformin : A Cohort Study.

BACKGROUND: Evidence on the risk for cardiovascular events associated with use of first-line sodium-glucose cotransporter-2 inhibitors (SGLT-2i) compared with metformin is limited. OBJECTIVE: To assess cardiovascular outcomes among adults with type 2 diabetes (T2D) who initiated first-line treatment with SGLT-2i versus metformin. DESIGN: Population-based cohort study. SETTING: Claims data from 2 large U.S. commercial and Medicare databases (April 2013 to March 2020). PARTICIPANTS: Patients with T2D aged 18 years and older (>65 years in Medicare) initiating treatment with SGLT-2i or metformin during April 2013 to March 2020, without any use of antidiabetic medications before cohort entry, were identified. After 1:2 propensity score matching in each database, pooled hazard ratios (HRs) and 95% CIs were reported. INTERVENTION: First-line SGLT-2i (canagliflozin, empagliflozin, or dapagliflozin) or metformin. MEASUREMENTS: Primary outcomes were a composite of hospitalization for myocardial infarction (MI), hospitalization for ischemic or hemorrhagic stroke or all-cause mortality (MI/stroke/mortality), and a composite of hospitalization for heart failure (HHF) or all-cause mortality (HHF/mortality). Safety outcomes including genital infections were assessed. RESULTS: Among 8613 first-line SGLT-2i initiators matched to 17 226 metformin initiators, SGLT-2i initiators had a similar risk for MI/stroke/mortality (HR, 0.96; 95% CI, 0.77 to 1.19) and a lower risk for HHF/mortality (HR, 0.80; CI, 0.66 to 0.97) during a mean follow-up of 12 months. Initiators receiving SGLT-2i showed a lower risk for HHF (HR, 0.78; CI, 0.63 to 0.97), a numerically lower risk for MI (HR, 0.70; CI, 0.48 to 1.00), and similar risk for stroke, mortality, and MI/stroke/HHF/mortality compared with metformin. Initiators receiving SGLT-2i had a higher risk for genital infections (HR, 2.19; CI, 1.91 to 2.51) and otherwise similar safety as those receiving metformin. LIMITATION: Treatment selection was not randomized. CONCLUSION: As first-line T2D treatment, initiators receiving SGLT-2i showed a similar risk for MI/stroke/mortality, lower risk for HHF/mortality and HHF, and a similar safety profile except for an increased risk for genital infections compared with those receiving metformin. PRIMARY FUNDING SOURCE: Brigham and Women's Hospital and Harvard Medical School.

Emulation of Randomized Clinical Trials With Nonrandomized Database Analyses: Results of 32 Clinical Trials.

Importance: Nonrandomized studies using insurance claims databases can be analyzed to produce real-world evidence on the effectiveness of medical products. Given the lack of baseline randomization and measurement issues, concerns exist about whether such studies produce unbiased treatment effect estimates. Objective: To emulate the design of 30 completed and 2 ongoing randomized clinical trials (RCTs) of medications with database studies using observational analogues of the RCT design parameters (population, intervention, comparator, outcome, time [PICOT]) and to quantify agreement in RCT-database study pairs. Design, Setting, and Participants: New-user cohort studies with propensity score matching using 3 US claims databases (Optum Clinformatics, MarketScan, and Medicare). Inclusion-exclusion criteria for each database study were prespecified to emulate the corresponding RCT. RCTs were explicitly selected based on feasibility, including power, key confounders, and end points more likely to be emulated with real-world data. All 32 protocols were registered on ClinicalTrials.gov before conducting analyses. Emulations were conducted from 2017 through 2022. Exposures: Therapies for multiple clinical conditions were included. Main Outcomes and Measures: Database study emulations focused on the primary outcome of the corresponding RCT. Findings of database studies were compared with RCTs using predefined metrics, including Pearson correlation coefficients and binary metrics based on statistical significance agreement, estimate agreement, and standardized difference. Results: In these highly selected RCTs, the overall observed agreement between the RCT and the database emulation results was a Pearson correlation of 0.82 (95% CI, 0.64-0.91), with 75% meeting statistical significance, 66% estimate agreement, and 75% standardized difference agreement. In a post hoc analysis limited to 16 RCTs with closer emulation of trial design and measurements, concordance was higher (Pearson r, 0.93; 95% CI, 0.79-0.97; 94% meeting statistical significance, 88% estimate agreement, 88% standardized difference agreement). Weaker concordance occurred among 16 RCTs for which close emulation of certain design elements that define the research question (PICOT) with data from insurance claims was not possible (Pearson r, 0.53; 95% CI, 0.00-0.83; 56% meeting statistical significance, 50% estimate agreement, 69% standardized difference agreement). Conclusions and Relevance: Real-world evidence studies can reach similar conclusions as RCTs when design and measurements can be closely emulated, but this may be difficult to achieve. Concordance in results varied depending on the agreement metric. Emulation differences, chance, and residual confounding can contribute to divergence in results and are difficult to disentangle.