Dataset Information

Emulating Control Arms for Cancer Clinical Trials Using External Cohorts Created From Electronic Health Record-Derived Real-World Data.

ABSTRACT: Electronic health record (EHR)-derived real-world data (RWD) can be sourced to create external comparator cohorts to oncology clinical trials. This exploratory study assessed whether EHR-derived patient cohorts could emulate select clinical trial control arms across multiple tumor types. The impact of analytic decisions on emulation results was also evaluated. By digitizing Kaplan-Meier curves, we reconstructed published control arm results from 15 trials that supported drug approvals from January 1, 2016, to April 30, 2018. RWD cohorts were constructed using a nationwide EHR-derived de-identified database by aligning eligibility criteria and weighting to trial baseline characteristics. Trial data and RWD cohorts were compared using Kaplan-Meier and Cox proportional hazards regression models for progression-free survival (PFS) and overall survival (OS; individual cohorts) and multitumor random effects models of hazard ratios (HRs) for median endpoint correlations (across cohorts). Post hoc, the impact of specific analytic decisions on endpoints was assessed using a case study. Comparing trial data and weighted RWD cohorts, PFS results were more similar (HR range = 0.63-1.18, pooled HR = 0.84, correlation of median = 0.91) compared to OS (HR range = 0.36-1.09, pooled HR = 0.76, correlation of median = 0.85). OS HRs were more variable and trended toward worse for RWD cohorts. The post hoc case study had OS HR ranging from 0.67 (95% confidence interval (CI): 0.56-0.79) to 0.92 (95% CI: 0.78-1.09) depending on specific analytic decisions. EHR-derived RWD can emulate oncology clinical trial control arm results, although with variability. Visibility into clinical trial cohort characteristics may shape and refine analytic approaches.

SUBMITTER: Tan K

PROVIDER: S-EPMC9292216 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Emulating Control Arms for Cancer Clinical Trials Using External Cohorts Created From Electronic Health Record-Derived Real-World Data.

Tan Katherine K Bryan Jonathan J Segal Brian B Bellomo Lawrence L Nussbaum Nate N Tucker Melisa M Torres Aracelis Z AZ Bennette Carrie C Capra William W Curtis Melissa M Miksad Rebecca A RA

Clinical pharmacology and therapeutics 20210731 1

Electronic health record (EHR)-derived real-world data (RWD) can be sourced to create external comparator cohorts to oncology clinical trials. This exploratory study assessed whether EHR-derived patient cohorts could emulate select clinical trial control arms across multiple tumor types. The impact of analytic decisions on emulation results was also evaluated. By digitizing Kaplan-Meier curves, we reconstructed published control arm results from 15 trials that supported drug approvals from Janua ...[more]

PMID: 34197637

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Project description:BackgroundRegulators are evaluating the use of noninterventional real-world evidence (RWE) studies to assess the effectiveness of medical products. The RCT DUPLICATE initiative (Randomized, Controlled Trials Duplicated Using Prospective Longitudinal Insurance Claims: Applying Techniques of Epidemiology) uses a structured process to design RWE studies emulating randomized, controlled trials (RCTs) and compare results. We report findings of the first 10 trial emulations, evaluating cardiovascular outcomes of antidiabetic or antiplatelet medications.MethodsWe selected 3 active-controlled and 7 placebo-controlled RCTs for replication. Using patient-level claims data from US commercial and Medicare payers, we implemented inclusion and exclusion criteria, selected primary end points, and comparator populations to emulate those of each corresponding RCT. Within the trial-mimicking populations, we conducted propensity score matching to control for >120 preexposure confounders. All study measures were prospectively defined and protocols registered before hazard ratios and 95% CIs were computed. Success criteria for the primary analysis were prespecified for each replication.ResultsDespite attempts to emulate RCT design as closely as possible, differences between the RCT and corresponding RWE study populations remained. The regulatory conclusions were equivalent in 6 of 10. The RWE emulations achieved a hazard ratio estimate that was within the 95% CI from the corresponding RCT in 8 of 10 studies. In 9 of 10, either the regulatory or estimate agreement success criteria were fulfilled. The largest differences in effect estimates were found for RCTs where second-generation sulfonylureas were used as a proxy for placebo regarding cardiovascular effects. Nine of 10 replications had a standardized difference between effect estimates of <2, which suggests differences within expected random variation.ConclusionsAgreement between RCT and RWE findings varies depending on which agreement metric is used. Interim findings indicate that selection of active comparator therapies with similar indications and use patterns enhances the validity of RWE. Even in the context of active comparators, concordance between RCT and RWE findings is not guaranteed, partially because trials are not emulated exactly. More trial emulations are needed to understand how often and in what contexts RWE findings match RCTs. Registration: URL: https://www.clinicaltrials.gov; Unique identifiers: NCT03936049, NCT04215523, NCT04215536, NCT03936010, NCT03936036, NCT03936062, NCT03936023, NCT03648424, NCT04237935, NCT04237922.

Project description:BackgroundEmulating randomized controlled trials (RCTs) by real-world evidence (RWE) studies would benefit future clinical and regulatory decision-making by balancing the limitations of RCT. We aimed to evaluate whether the findings from RWE studies can support regulatory decisions derived from RCTs of non-vitamin K antagonist oral anticoagulants (NOACs) in patients with venous thromboembolism (VTE).MethodsFive landmark trials (AMPLIFY, RE-COVER II, Hokusai-VTE, EINSTEIN-DVT, and EINSTEIN-PE) of NOACs were emulated using the South Korean nationwide claims database (January 2012 to August 2020). We applied an active comparator and new-user design to include patients who initiated oral anticoagulants within 28 days from their VTE diagnoses. The prespecified eligibility criteria, exposure (each NOAC, such as apixaban, rivaroxaban, dabigatran, and edoxaban), comparator (conventional therapy, defined as subcutaneous heparin followed by warfarin), and the definition of outcomes from RCTs were emulated as closely as possible in each separate emulation cohort. The primary outcome was identical to each trial, which was defined as recurrent VTE or VTE-related death. The safety outcome was major bleeding. Propensity score matching was conducted to balance 69 covariates between the exposure groups. Effect estimates for outcomes were estimated using the Mantel-Haenszel method and Cox proportional hazards model and subsequently compared with the corresponding RCT estimates.ResultsCompared to trial populations, real-world study populations were older (range: 63-69 years [RWE] vs. 54-59 years [RCT]), with more females (55-60.5% vs. 39-48.3%) and had a higher prevalence of active cancer (4.2-15.4% vs. 2.5-9.5%). The emulated estimates for effectiveness outcomes showed superior effectiveness of NOAC (AMPLIFY: relative risk 0.81, 95% confidence interval 0.70-0.94; RE-COVER II: hazard ratio [HR] 0.60, 0.37-0.96; Hokusai-VTE: 0.49, 0.31-0.78; EINSTEIN-DVT: 0.54, 0.33-0.89; EINSTEIN-PE: 0.50, 0.34-0.74), when contrasted with trials that showed non-inferiority. For safety outcomes, all emulations except for AMPLIFY and EINSTEIN-DVT yielded results consistent with their corresponding RCTs.ConclusionsThis study revealed the feasibility of complementing RCTs with RWE studies by using claims data in patients with VTE. Future studies to consider the different demographic characteristics between RCT and RWE populations are needed.

Project description:IntroductionHyperkalemia is often managed in the emergency department (ED) and it is important to understand how ED management and post-discharge outcomes vary by hyperkalemia severity. This study was conducted to characterize ED management and post-discharge outcomes across hyperkalemia severities.MethodsAdults with an ED visit with hyperkalemia (at least one serum potassium lab measure above 5.0 mEq/L) were selected from US electronic medical record data (2012-2018). Patient characteristics, potassium levels, treatments, and monitoring prior to and during the ED visit were compared by hyperkalemia severity (mild [> 5.0-5.5 mEq/L], moderate [> 5.5-6.0], severe [> 6.0]) using unadjusted analyses. Death, immediate inpatient admission, 30-day hyperkalemia recurrence, and 30-day inpatient admission were also assessed by severity.ResultsOf 6222 patients included, 4432 (71.2%) had mild hyperkalemia, 1085 (17.4%) had moderate, and 705 (11.3%) had severe hyperkalemia. Chronic kidney disease (39.9-50.1%) and heart failure (21.6-24.3%) were common. In the ED, electrocardiograms (mild, 56.5%; moderate, 69.6%; severe, 81.0%) and patients with at least two potassium laboratory values increased with severity (15.0%; 40.4%; 75.5%). Among patients with at least two potassium laboratory values, over half of patients (60.4%) had potassium levels ≤ 5.0 mEq/L prior to discharge. Use of potassium-binding treatments (sodium polystyrene sulfonate: mild = 4.1%; moderate = 17.1%; severe = 27.4%), temporizing agents (5.6%; 15.5%; 31.6%), or dialysis (0.4%; 0.8%; 3.0%) increased with severity; treatment at discharge was not common. Death (1.1%; 3.7%; 10.6%), immediate admission to inpatient care (5.8%; 8.7%; 12.7%), 30-day hyperkalemia recurrence (2.9%; 19.0%; 32.5%), 30-day inpatient admission with hyperkalemia (6.5%; 7.9%; 9.3%) also increased with severity.ConclusionPatients with moderate and severe hyperkalemia experienced elevated risk of hyperkalemia recurrence and hyperkalemia-related inpatient readmission following discharge from the ED from a descriptive analysis. Future research to assess strategies to reduce hyperkalemia recurrence and inpatient admission in this patient population would be beneficial.

Project description:PurposeExternal control (EC) arms derived from electronic health records (EHRs) can provide appropriate comparison groups when randomized control arms are not feasible, but have not been explored for metastatic colorectal cancer (mCRC) trials. We constructed EC arms from two patient-level EHR-derived databases and evaluated them against the control arm from a phase III, randomized controlled mCRC trial.MethodsIMblaze370 evaluated atezolizumab with or without cobimetinib versus regorafenib in patients with mCRC. EC arms were constructed from the Flatiron Health (FH) EHR-derived de-identified database and the combined FH/Foundation Medicine Clinico-Genomic Database (CGDB). IMblaze370 eligibility criteria were applied to the EC cohorts. Propensity scores and standardized mortality ratio weighting were used to balance baseline characteristics between the IMblaze370 and EC arms; balance was assessed using standardized mean differences. Kaplan-Meier method estimated median overall survival (OS). Cox proportional hazards models estimated hazard ratios with bootstrapped 95% CIs to compare differences in OS between study arms.ResultsThe FH EC included 184 patients; the CGDB EC included 108 patients. Most characteristics were well-balanced (standardized mean difference < 0.1) between each EC arm and the IMblaze370 population. Median OS was similar between the IMblaze370 control arm (8.5 months [95% CI, 6.41 to 10.71]) and both EC arms: FH (8.5 months [6.93 to 9.92]) and CGDB (8.8 months [7.85 to 9.92]). OS comparisons between the IMblaze370 experimental arm and the FH EC (hazard ratio, 0.85 [0.64 to 1.14]) and CGDB EC (0.86 [0.65 to 1.18]) yielded similar results as the comparison with the IMblaze370 control arm (1.01 [0.75 to 1.37]).ConclusionEC arms constructed from the FH database and the CGDB closely replicated the control arm from IMblaze370. EHR-derived EC arms can provide meaningful comparators in mCRC trials when recruiting a randomized control arm is not feasible.

Dataset Information

Emulating Control Arms for Cancer Clinical Trials Using External Cohorts Created From Electronic Health Record-Derived Real-World Data.

Publications

Emulating Control Arms for Cancer Clinical Trials Using External Cohorts Created From Electronic Health Record-Derived Real-World Data.

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