ArticlePloS one
Optimizing Trial Designs for Targeted Therapies.
Article in PloS one. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Systematic evaluation of subgroup analyses of inhaled treprostinil in pulmonary hypertension due to interstitial lung disease.PloS one · 2025Article
- Two-stage Adaptive Enrichment Designs with Survival Outcomes and Adjustment for Misclassification in Predictive Biomarkers.Statistics in biopharmaceutical research · 2025Article
- Article
- Selecting predictive biomarkers from genomic data.PloS one · 2022Article
- Collaborative Platform Trials to Fight COVID-19: Methodological and Regulatory Considerations for a Better Societal Outcome.Clinical pharmacology and therapeutics · 2021Review
- Optimizing subgroup selection in two-stage adaptive enrichment and umbrella designs.Statistics in medicine · 2021Article
- Optimized adaptive enrichment designs.Statistical methods in medical research · 2019Article
- Design of experiments for a confirmatory trial of precision medicine.Journal of statistical planning and inference · 2019Article
- Recent advances in methodology for clinical trials in small populations: the InSPiRe project.Orphanet journal of rare diseases · 2018Review
- Point estimation following two-stage adaptive threshold enrichment clinical trials.Statistics in medicine · 2018Article
- Lessons learned from IDeAl - 33 recommendations from the IDeAl-net about design and analysis of small population clinical trials.Orphanet journal of rare diseases · 2018Review
- PIPELINEs: Creating Comparable Clinical Knowledge Efficiently by Linking Trial Platforms.Clinical pharmacology and therapeutics · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An important objective in the development of targeted therapies is to identify the populations where the treatment under consideration has positive benefit risk balance. We consider pivotal clinical trials, where the efficacy of a treatment is tested in an overall population and/or in a pre-specified subpopulation. Based on a decision theoretic framework we derive optimized trial designs by maximizing utility functions. Features to be optimized include the sample size and the population in which the trial is performed (the full population or the targeted subgroup only) as well as the underlying multiple test procedure. The approach accounts for prior knowledge of the efficacy of the drug in the considered populations using a two dimensional prior distribution. The considered utility functions account for the costs of the clinical trial as well as the expected benefit when demonstrating efficacy in the different subpopulations. We model utility functions from a sponsor's as well as from a public health perspective, reflecting actual civil interests. Examples of optimized trial designs obtained by numerical optimization are presented for both perspectives.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.