ArticleClinical pharmacology and therapeutics2022
Emulating Control Arms for Cancer Clinical Trials Using External Cohorts Created From Electronic Health Record-Derived Real-World Data.
Article in Clinical pharmacology and therapeutics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed.
- Emulating VIEW 1 and VIEW 2 Clinical Trial Outcome Data Using the American Academy of Ophthalmology IRIS Registry.Ophthalmic surgery, lasers & imaging retina · 2023Trial
- AI-based augmentation of oncology clinical trials.Nature reviews. Clinical oncology · 2026Review
- Exploring the discrepancies between clinical trials and real-world data: A small-cell lung cancer study.Clinical and translational science · 2024Article
- Examining external control arms in oncology: A scoping review of applications to date.Cancer medicine · 2024Article
- Enriching single-arm clinical trials with external controls: possibilities and pitfalls.Blood advances · 2023Article
- Effectiveness of tisagenlecleucel versus real-world standard of care in relapsed/refractory follicular lymphoma.Journal of comparative effectiveness research · 2023Article
- Augmenting control arms with real-world data for cancer trials: Hybrid control arm methods and considerations.Contemporary clinical trials communications · 2022Article
- A novel analytical framework for risk stratification of real-world data using machine learning: A small cell lung cancer study.Clinical and translational science · 2022Article
- Replication of Overall Survival, Progression-Free Survival, and Overall Response in Chemotherapy Arms of Non-Small Cell Lung Cancer Trials Using Real-World Data.Clinical cancer research : an official journal of the American Association for Cancer Research · 2022Article
- Considerations for the Utility of Real-World Evidence Beyond Trial Data in Advanced NSCLC: The Case of Frontline Tyrosine Kinase Inhibitors.Cancer management and research · 2022Article
- Oncology Drug Effectiveness from Electronic Health Record Data Calibrated Against RCT Evidence: The PARSIFAL Trial Emulation.Clinical epidemiology · 2022Article
- Comparison of Methods of Clinical Trial Emulation Utilizing Data From the Comparison of AMD Treatment Trial (CATT) and the IRIS® Registry.Ophthalmology scienceArticle
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Authors and funding
11 authors.
Funding
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.
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