ArticlePloS one2019
Comparison between continuous and discrete doses for model based designs in cancer dose finding.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- A Novel Method for Inserting Dose Levels Mid-Trial in Early-Phase Oncology Combination Studies.Statistics in medicine · 2026Article
- The Correlated Beta Dose Optimisation Approach: Optimal Vaccine Dosing Using Mathematical Modelling and Adaptive Trial Design.Vaccines · 2022Article
- Utility based approach in individualized optimal dose selection using machine learning methods.Statistics in medicine · 2022Article
- Mathematical Modelling for Optimal Vaccine Dose Finding: Maximising Efficacy and Minimising Toxicity.Vaccines · 2022Article
- A phase I study of sirolimus in combination with metronomic therapy (CHOAnome) in children with recurrent or refractory solid and brain tumors.Pediatric blood & cancer · 2020Article
- Pooling individual participant data from randomized controlled trials: Exploring potential loss of information.PloS one · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Despite of an extensive statistical literature showing that discretizing continuous variables results in substantial loss of information, categorization of continuous variables has been a common practice in clinical research and in cancer dose finding (phase I) clinical trials. The objective of this study is to quantify the loss of information incurred by using a discrete set of doses to estimate the maximum tolerated dose (MTD) in phase I trials, instead of a continuous dose support. Escalation With Overdose Control and Continuous Reassessment Method were used because they are model-based designs where dose can be specified either as continuous or as a set of discrete levels. Five equally spaced sets of doses with different interval lengths and three sample sizes with sixteen scenarios were evaluated to compare the operating characteristics between continuous and discrete dose designs by Monte Carlo simulation. Loss of information was quantified by safety and efficiency measures. We conclude that if there is insufficient knowledge about the true MTD value, as commonly happens in phase I clinical trials, a continuous dose scheme minimizes information loss. If one is required to implement a design using discrete doses, then a scheme with 9 to 11 doses may yield similar results to the continuous dose scheme.
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Registered trials
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