Evidence map›Paper›PMID 29036330›Full record

ArticleBiostatistics (Oxford, England)2018

Adding experimental arms to platform clinical trials: randomization procedures and interim analyses.

Steffen Ventz, Matteo Cellamare, Giovanni Parmigiani, Lorenzo Trippa

Abstract read
In one paragraph

Article in Biostatistics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Predicting clinical trial success forFrontiers in artificial intelligence · 2024
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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.

Steffen VentzDepartment of Computer Science and Statistics, University of Rhode Island, 9 Greenhouse Road, Kingston, RI 02881, USA.
Matteo CellamareHarvard T. H. Chan School of Public Health, 655 Huntington Ave, Boston, MA 02115, USA, Department of Statistical Sciences, Sapienza University, Piazzale Aldo Moro 5, 00185 Roma, Italy, and Department of Biostatistics, Harvard T. H. Chan School of Public Health, 655 Huntington Ave, Boston, MA, 02115, USA.
Giovanni ParmigianiDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 450 Brookline Ave., Boston, MA 02115, USA and Department of Biostatistics, Harvard T. H. Chan School of Public Health, 655 Huntington Ave, Boston, MA, 02115, USA.
Lorenzo TrippaDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 450 Brookline Ave., Boston, MA 02115, USA and Department of Biostatistics, Harvard T. H. Chan School of Public Health, 655 Huntington Ave, Boston, MA, 02115, USA.

Funding

VectorP30CA006516 · NCI · DANA-FARBER CANCER INSTITUTE · PI A. Heather Eliassen · 1985 to 2026
$330.6M
NCI NIH HHS P30 CA006516
6 · The paper itself

Abstract

Multi-arm clinical trials use a single control arm to evaluate multiple experimental treatments. In most cases this feature makes multi-arm studies considerably more efficient than two-arm studies. A bottleneck for implementation of a multi-arm trial is the requirement that all experimental treatments have to be available at the enrollment of the first patient. New drugs are rarely at the same stage of development. These limitations motivate our study of statistical methods for adding new experimental arms after a clinical trial has started enrolling patients. We consider both balanced and outcome-adaptive randomization methods for experimental designs that allow investigators to add new arms, discuss their application in a tuberculosis trial, and evaluate the proposed designs using a set of realistic simulation scenarios. Our comparisons include two-arm studies, multi-arm studies, and the proposed class of designs in which new experimental arms are added to the trial at different time points.

Indexed as

Data Interpretation, StatisticalModels, StatisticalRandom AllocationAdaptive Clinical Trials as TopicAntitubercular AgentsClinical Trials as TopicComputer SimulationHumansRandomized Controlled Trials as TopicResearch DesignTuberculosisAntitubercular Agents

Identifiers

PMID29036330
PMCPMC5862294

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.