Evidence map›Paper›PMID 37386450›Full record

ArticleBMC medical research methodology2023

Looking ahead in early-phase trial design to improve the drug development process: examples in oncology.

Alyssa M Vanderbeek, Robert A Redd, Steffen Ventz, Lorenzo Trippa

Abstract read
In one paragraph

Article in BMC medical research methodology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Alyssa M Vanderbeek *Department of Data Science, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02115, USA.
Robert A Redd *Department of Data Science, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02115, USA.
Steffen VentzDivision of Biostatistics, University of Minnesota, Minneapolis, MN, USA.
Lorenzo TrippaDepartment of Data Science, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02115, USA. ltrippa@jimmy.harvard.edu.

Funding

Women's CancerP30CA077598 · NCI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI Jeffrey S. Miller · 1998 to 2026
$100.4M
Statistical Methods and Validation Analyses for the Integration of External Data in Clinical TrialsR01LM013352 · NLM · DANA-FARBER CANCER INST · PI TRIPPA, LORENZO · 2021 to 2024
$1.5M
NCI NIH HHS P30 CA077598NLM NIH HHS R01 LM013352
6 · The paper itself

Abstract

backgroundClinical trial design must consider the specific resource constraints and overall goals of the drug development process (DDP); for example, in designing a phase I trial to evaluate the safety of a drug and recommend a dose for a subsequent phase II trial. Here, we focus on design considerations that involve the sequence of clinical trials, from early phase I to late phase III, that constitute the DDP.

methodsWe discuss how stylized simulation models of clinical trials in an oncology DDP can quantify important relationships between early-phase trial designs and their consequences for the remaining phases of development. Simulations for three illustrative settings are presented, using stylized models of the DDP that mimic trial designs and decisions, such as the potential discontinuation of the DDP.

resultsWe describe: (1) the relationship between a phase II single-arm trial sample size and the likelihood of a positive result in a subsequent phase III confirmatory trial; (2) the impact of a phase I dose-finding design on the likelihood that the DDP will produce evidence of a safe and effective therapy; and (3) the impact of a phase II enrichment trial design on the operating characteristics of a subsequent phase III confirmatory trial.

conclusionsStylized models of the DDP can support key decisions, such as the sample size, in the design of early-phase trials. Simulation models can be used to estimate performance metrics of the DDP under realistic scenarios; for example, the duration and the total number of patients enrolled. These estimates complement the evaluation of the operating characteristics of early-phase trial design, such as power or accuracy in selecting safe and effective dose levels.

Indexed as

BenchmarkingDrug DevelopmentClinical Trials as TopicComputer SimulationHumansMedical OncologyProbabilityClinical trial designDrug development processOncologySimulation

Identifiers

PMID37386450
PMCPMC10308797

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