ArticleClinical cancer research : an official journal of the American Association for Cancer Research2019
Design and Evaluation of an External Control Arm Using Prior Clinical Trials and Real-World Data.
Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
53 citing papers in PubMed.
- Treatment Effect Reanalysis of the Randomized Individual Screening Trial of Innovative Glioblastoma Therapy in Newly Diagnosed Glioblastoma With External Control Data.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2026Trial
- Prospectively shared control data across concurrent randomised clinical trials.European journal of cancer (Oxford, England : 1990) · 2023Trial
- Temporal Trends in Clinical Evidence of 5-Year Survival Within Electronic Health Records Among Patients With Early-Stage Colon Cancer Managed With Laparoscopy-Assisted Colectomy vs Open Colectomy.JAMA network open · 2022Trial
- A Frequentist Approach Using Weighted Estimating Equations for Survival Analysis of Randomized Controlled Trial With External Control Arm.Biometrical journal. Biometrische Zeitschrift · 2026Article
- Review
- Harmonized Estimation of Subgroup-Specific Treatment Effects in Randomized Trials: The Use of External Control Data.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2026Article
- Leveraging External Data for Testing Experimental Therapies with Biomarker Interactions in Randomized Clinical Trials.Biometrika · 2026Article
- Biomarkers for predicting immunotherapy response and resistance in glioblastoma.Frontiers in immunology · 2026Review
- Clinical trial design for primary brain tumors: a problem-based framework for neuro-oncology practice.Frontiers in oncology · 2026Review
- Acceptability of external control-arm use in nononcology health technology assessment submissions.Journal of comparative effectiveness research · 2026Article
- Real-World Data as External Control in Assessing the Efficacy of Allogeneic Adipose-Derived Stem Cells Therapy for Advanced Chronic Kidney Disease.Clinical and translational science · 2025Article
- Design, Conduct, and Analysis of Externally Controlled Trials.JAMA network open · 2025Article
- FedECA: federated external control arms for causal inference with time-to-event data in distributed settings.Nature communications · 2025Article
- Identifying appropriate external control datasets in support of future glioblastoma clinical trials leveraging external data.Neuro-oncology · 2025Article
- Safe inference outside of randomized trials: Application of the stability-controlled quasi-experiment to the effects of three COVID-19 therapies.Observational studies · 2025Article
- Informative censoring in externally controlled clinical trials: a potential source of bias.ESMO open · 2025Article
- Design and conduct of theranostic trials in neuro-oncology: Challenges and opportunities.Neuro-oncology · 2024Review
- Glioblastoma Vaccines as Promising Immune-Therapeutics: Challenges and Current Status.Vaccines · 2024Review
- Leveraging external control data in the design and analysis of neuro-oncology trials: Pearls and perils.Neuro-oncology · 2024Review
- Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
purposeWe discuss designs and interpretable metrics of bias and statistical efficiency of "externally controlled" trials (ECT) and compare ECT performance to randomized and single-arm designs. EXPERIMENTAL
designWe specify an ECT design that leverages information from real-world data (RWD) and prior clinical trials to reduce bias associated with interstudy variations of the enrolled populations. We then used a collection of clinical studies in glioblastoma (GBM) and RWD from patients treated with the current standard of care to evaluate ECTs. Validation is based on a "leave one out" scheme, with iterative selection of a single-arm from one of the studies, for which we estimate treatment effects using the remaining studies as external control. This produces interpretable and robust estimates on ECT bias and type I errors.
resultsWe developed a model-free approach to evaluate ECTs based on collections of clinical trials and RWD. For GBM, we verified that inflated false positive error rates of standard single-arm trials can be considerably reduced (up to 30%) by using external control data.
conclusionsThe use of ECT designs in GBM, with adjustments for the clinical profiles of the enrolled patients, should be preferred to single-arm studies with fixed efficacy thresholds extracted from published results on the current standard of care.
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