Evidence map›Paper›PMID 36680572›Full record

ArticleRadiation and environmental biophysics2023

Comparison and multi-model inference of excess risks models for radiation-related solid cancer.

Alberto Stabilini, Luana Hafner, Linda Walsh

Open access · hybridAbstract read
In one paragraph

Article in Radiation and environmental biophysics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.6field-weighted citation impact, top 17% of its field
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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Radiation-Related Thyroid Cancer.Endocrine reviews · 2024
    Review
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

3 authors at 2 institutions in 1 country.

Alberto StabiliniSwiss Federal Nuclear Safety Inspectorate ENSI, Industriestrasse 19, 5201, Brugg, Switzerland.ORCID 0000-0001-9823-1250
Luana HafnerSwiss Federal Nuclear Safety Inspectorate ENSI, Industriestrasse 19, 5201, Brugg, Switzerland. luana.hafner@ensi.ch.ORCID 0000-0002-5218-9293
Linda WalshDepartment of Physics, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland.ORCID 0000-0001-7399-9191
Swiss Federal Nuclear Safety Inspectorate · CHUniversity of Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In assessments of detrimental health risks from exposures to ionising radiation, many forms of risk to dose-response models are available in the literature. The usual practice is to base risk assessment on one specific model and ignore model uncertainty. The analysis illustrated here considers model uncertainty for the outcome all solid cancer incidence, when modelled as a function of colon organ dose, using the most recent publicly available data from the Life Span Study on atomic bomb survivors of Japan. Seven recent publications reporting all solid cancer risk models currently deemed plausible by the scientific community have been included in a model averaging procedure so that the main conclusions do not depend on just one type of model. The models have been estimated with different baselines and presented for males and females at various attained ages and ages at exposure, to obtain specially computed model-averaged Excess Relative Risks (ERR) and Excess Absolute Risks (EAR). Monte Carlo simulated estimation of uncertainty on excess risks was accounted for by applying realisations including correlations in the risk model parameters. Three models were found to weight the model-averaged risks most strongly depending on the baseline and information criteria used for the weighting. Fitting all excess risk models with the same baseline, one model dominates for both information criteria considered in this study. Based on the analysis presented here, it is generally recommended to take model uncertainty into account in future risk analyses.

Indexed as

Neoplasms, Radiation-InducedNuclear WarfareFemaleHumansIncidenceJapanMaleRadiation, IonizingRisk AssessmentSurvivorsModel comparisonMulti-model inferenceRadiation epidemiologyRadiation-induced cancer risk

Identifiers

PMID36680572
PMCPMC9950237
OpenAlexW4317659293

What OpenQuestion holds

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LicenceCC BY
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.