Evidence map›Paper›PMID 30485322›Full record

ArticlePloS one2018

A statistical framework for radiation dose estimation with uncertainty quantification from the γ-H2AX assay.

Jochen Einbeck, Elizabeth A Ainsbury, Rachel Sales, Stephen Barnard, Felix Kaestle, Manuel Higueras

Abstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
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  7. Article
  8. BPIFA2 as a Novel Early Biomarker to Identify Fatal Radiation Injury After Radiation Exposure.Dose-response : a publication of International Hormesis Society
    Article
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

6 authors.

Jochen EinbeckDepartment of Mathematical Sciences, Durham University, Durham, United Kingdom.ORCID 0000-0002-9457-2020
Elizabeth A AinsburyPublic Health England, Chemical and Environmental Hazards, Chilton, Didcot, United Kingdom.
Rachel SalesDepartment of Mathematical Sciences, Durham University, Durham, United Kingdom.
Stephen BarnardPublic Health England, Chemical and Environmental Hazards, Chilton, Didcot, United Kingdom.
Felix KaestleBundesamt für Strahlenschutz, Fachbereich Strahlenschutz und Gesundheit, Oberschleissheim, Germany.
Manuel HiguerasDepartamento de Matemáticas y Computación, Universidad de La Rioja, Logroño, La Rioja, Spain.

Funding

Sample Engineering CoreU19AI067773 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI FORNACE, ALBERT J · 2005 to 2024
$105.4M
NIAID NIH HHS U19 AI067773
6 · The paper itself

Abstract

Over the last decade, the γ-H2AX focus assay, which exploits the phosphorylation of the H2AX histone following DNA double-strand-breaks, has made considerable progress towards acceptance as a reliable biomarker for exposure to ionizing radiation. While the existing literature has convincingly demonstrated a dose-response effect, and also presented approaches to dose estimation based on appropriately defined calibration curves, a more widespread practical use is still hampered by a certain lack of discussion and agreement on the specific dose-response modelling and uncertainty quantification strategies, as well as by the unavailability of implementations. This manuscript intends to fill these gaps, by stating explicitly the statistical models and techniques required for calibration curve estimation and subsequent dose estimation. Accompanying this article, a web applet has been produced which implements the discussed methods.

Indexed as

Models, BiologicalRadiation DosageRadiation ExposureHistonesHumansH2AX protein, humanHistones

Identifiers

PMID30485322
PMCPMC6261578

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.