ArticleBMC cancer2020
A web application for the design of multi-arm clinical trials.
Article in BMC cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05376189 (The Effect of Vitamin D Supplementation on Toll-Like Receptor), which is not on this map. Cited by 21 papers, 1 of them a synthesis that pooled 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.
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.
The Effect of Vitamin D Supplementation on Toll-Like Receptor (TLR) 2, 4, and Clinical Outcomes of Spondylitis Tuberculosis
Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review of available software for multi-arm multi-stage and platform clinical trial design.Trials · 2021Pooled it
- Trial
- Trial
- Effect of a test-and-treat approach to vitamin D supplementation on risk of all cause acute respiratory tract infection and covid-19: phase 3 randomised controlled trial (CORONAVIT).BMJ (Clinical research ed.) · 2022Trial
- Clinical Trial Simulation: Planning With the OCTAVE Framework, Implementation and Validation Principles.Statistics in medicine · 2026Article
- The Effect of an Immersive Virtual Reality Physical Activity Intervention on Anthropometric Variables, Physical Fitness, and Blood Pressure in College Students: A Randomized Controlled Trial.Healthcare (Basel, Switzerland) · 2026Article
- Nuts4Brain-RCT: Protocol for a Three-Arm Randomized Controlled Trial Examining the Dose-Response Effects of Nut Consumption on Mental Health in Young Adults.Healthcare (Basel, Switzerland) · 2026Article
- A cluster randomised controlled trial, process and economic evaluation of two large-scale quality improvement interventions embedded with a national clinical audit to improve the care for young adults with type 2 diabetes (EQUIPD2): study protocol.Implementation science : IS · 2026Article
- Effects of a Walking-Based Physical Activity Intervention on Health Indicators in University Students: Protocol for a Randomized Controlled Trial.JMIR research protocols · 2025Article
- Article
- Impact of three-dimensional prostate models during robot-assisted radical prostatectomy on surgical margins and functional outcomes.BJU international · 2025Article
- Impact of Endpoint Delay on the Efficiency of Multi Arm Multi Stage Trials.Statistics in medicine · 2025Article
- Evidence-Based Approaches to Quality Improvement: A Narrative Review of Integrating Bayesian Adaptive Trials Into Health Services.Journal of evaluation in clinical practice · 2025Review
- An efficient vaccine clinical trial: ACTG A5379 hepatitis B vaccine trial in persons with HIV.Vaccine · 2025Article
- Effectiveness of high-intensity inspiratory muscle training, and resistance and aerobic exercise for cardiovascular health in chronic obstructive pulmonary disease (HIRAC-COPD): a randomized controlled trial protocol.BMC pulmonary medicine · 2024Article
- Article
- Statistical Considerations for the Design and Analysis of Pragmatic Trials in Aging Research.Geriatrics (Basel, Switzerland) · 2024Review
- Article
- Article
- The benefits of covariate adjustment for adaptive multi-arm designs.Statistical methods in medical research · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
backgroundMulti-arm designs provide an effective means of evaluating several treatments within the same clinical trial. Given the large number of treatments now available for testing in many disease areas, it has been argued that their utilisation should increase. However, for any given clinical trial there are numerous possible multi-arm designs that could be used, and choosing between them can be a difficult task. This task is complicated further by a lack of available easy-to-use software for designing multi-arm trials.
resultsTo aid the wider implementation of multi-arm clinical trial designs, we have developed a web application for sample size calculation when using a variety of popular multiple comparison corrections. Furthermore, the application supports sample size calculation to control several varieties of power, as well as the determination of optimised arm-wise allocation ratios. It is built using the Shiny package in the R programming language, is free to access on any device with an internet browser, and requires no programming knowledge to use. It incorporates a variety of features to make it easier to use, including help boxes and warning messages. Using design parameters motivated by a recently completed phase II oncology trial, we demonstrate that the application can effectively determine and evaluate complex multi-arm trial designs.
conclusionsThe application provides the core information required by statisticians and clinicians to review the operating characteristics of a chosen multi-arm clinical trial design. The range of designs supported by the application is broader than other currently available software solutions. Its primary limitation, particularly from a regulatory agency point of view, is its lack of validation. However, we present an approach to efficiently confirming its results via simulation.
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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.