Evidence map›Paper›PMID 37327124›Full record

ReviewRadiation research2023

Feasibility of Reducing Animal Numbers in Radiation Countermeasure Experiments from Historic Levels when using Sample Size Calculations.

Reid D Landes, Kimberly J Jurgensen, William K J Skinner, Horace J Spencer, Lynnette Cary

Abstract readReview
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
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

5 authors.

Reid D LandesDepartment of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, Arkansas 72205.
Kimberly J JurgensenScientific Research Department, Armed Forces Radiobiology Research Institute, Uniformed Services University of the Health Sciences, Bethesda, Maryland 20889.
William K J SkinnerDepartment of Radiation Oncology, Walter Reed National Military Medical Center, Bethesda, Maryland 20814.
Horace J SpencerDepartment of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, Arkansas 72205.
Lynnette CaryScientific Research Department, Armed Forces Radiobiology Research Institute, Uniformed Services University of the Health Sciences, Bethesda, Maryland 20889.

Funding

Expanding Translational Research in ArkansasUL1TR003107 · NCATS · UNIV OF ARKANSAS FOR MED SCIS · PI JAMES, LAURA P · 2019 to 2023
$21.6M
The Role o f Tetrahydrobiopterin (BH4) Bioavailability in Radiation-induced Skin InjuryP20GM109005 · NIGMS · UNIV OF ARKANSAS FOR MED SCIS · PI BOERMA, MARJAN · 2015 to 2024
$21.1M
The Role of the Mitochondrion in the Metabolic Stress Response to Burn TraumaP20GM109096 · NIGMS · ARKANSAS CHILDREN'S HOSPITAL RES INST · PI PORTER, CRAIG · 2016 to 2025
$20.7M
Algorithms to generate designs of potency experiments that use far fewer animalsR21CA184756 · NCI · UNIV OF ARKANSAS FOR MED SCIS · PI LANDES, REID D. · 2015 to 2016
$356k
NCATS NIH HHS UL1 TR003107NCI NIH HHS R21 CA184756NIGMS NIH HHS P20 GM109005NIGMS NIH HHS P20 GM109096
6 · The paper itself

Abstract

Historically, animal numbers have most often been in the hundreds for experiments designed to estimate the dose reduction factor (DRF) of a radiation countermeasure treatment compared to a control treatment. Before 2010, researchers had to rely on previous experience, both from others and their own, to determine the number of animals needed for a DRF experiment. In 2010, a formal sample size formula was developed by Kodell et al. This theoretical work showed that sample sizes for realistic, yet hypothetical, DRF experiments could be less than a hundred animals and still have sufficient power to detect clinically meaningful DRF values. However, researchers have been slow to use the formula for their DRF experiments, whether from ignorance to its existence or hesitancy to depart from "tried and true" sample sizes. Here, we adapt the sample size formula to better fit usual DRF experiments, and, importantly, we provide real experimental evidence from two independent DRF experiments that sample sizes smaller than what have typically been used can still statistically detect clinically meaningful DRF values. In addition, we update a literature review of DRF experiments which can be used to inform future DRF experiments, provide answers to questions that researchers have asked when considering sample size calculations rather than solely relying on previous experience, whether their own or others', and, in the supplementary material, provide R code implementing the formula, along with several exercises to familiarize the user with the adapted formula.

Indexed as

Sample SizeAnimalsFeasibility Studies

Identifiers

PMID37327124
PMCPMC10513753

What OpenQuestion holds

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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.