ArticleJournal of cystic fibrosis : official journal of the European Cystic Fibrosis Society2022
A new path for CF clinical trials through the use of historical controls.
Article in Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Evaluating Long-Term Effectiveness of Cystic Fibrosis Modulator Therapies after Rapid Adoption: A Dual-Approach Study.Annals of the American Thoracic Society · 2026Article
- Statistical approaches for the integration of external controls in a cystic fibrosis clinical trial: a simulation and an application.American journal of epidemiology · 2024Article
- Article
- Advancing the pipeline of cystic fibrosis clinical trials: a new roadmap with a global trial network perspective.The Lancet. Respiratory medicine · 2023Review
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundGiven future challenges in conducting large randomized, placebo controlled trials for future CF therapeutics development, we evaluated the potential for using external historical controls to either enrich or replace traditional concurrent placebo groups in CF trials.
methodsThe study included data from sequentially completed, randomized, controlled clinical trials, EPIC and OPTIMIZE respectively, evaluating optimal antibiotic therapy to reduce the risk of pulmonary exacerbation in children with early Pseudomonas aeruginosa infection. The primary treatment effect in OPTIMIZE, the risk of pulmonary exacerbation associated with azithromycin, was re-estimated in alternative designs incorporating varying numbers of participants from the earlier trial (EPIC) as historical controls. Bias and precision of these estimates were characterized. Propensity scores were derived to adjust for baseline differences across study populations, and both Poisson and Cox regression were used to estimate treatment efficacy.
resultsReplacing 86 OPTIMIZE placebo participants with 304 controls from EPIC to mimic a fully historically controlled trial resulted an 8% reduction in risk of pulmonary exacerbations (Hazard ratio (HR):0.92 95% CI 0.61, 1.34) when not adjusting for key baseline differences between study populations. After adjustment, a 37% decrease in risk of exacerbation (HR:0.63, 95% CI 0.50, 0.80) was estimated, comparable to the estimate from the original trial comparing the 86 placebo participants to 77 azithromycin participants on azithromycin (45%, HR:0.55, 95% CI: 0.34, 0.86). Other adjusted approaches provided similar estimates for the efficacy of azithromycin in reducing exacerbation risk: pooling all controls from both studies provided a HR of 0.60 (95% x`CI 0.46, 0.77) and augmenting half the OPTIMIZE placebo participants with EPIC controls gave a HR 0.63 (95% CI 0.48, 0.82).
conclusionsThe potential exists for future CF trials to utilize historical control data. Careful consideration of both the comparability of controls and of optimal methods can reduce the potential for biased estimation of treatment effects.
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Registered trials
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