Evidence map›Paper›PMID 24932535›Full record

ArticleRadiation research2014

Association of chromosome translocation rate with low dose occupational radiation exposures in U.S. radiologic technologists.

Mark P Little, Deukwoo Kwon, Kazataka Doi, Steven L Simon, Dale L Preston, Michele M Doody, Terrence Lee, Jeremy S Miller, Diane M Kampa, Parveen Bhatti and 3 more

Abstract read
In one paragraph

Article in Radiation research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
3.5field-weighted citation impact, top 8% 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

30 citing papers in PubMed, 1 synthesis or guideline pooled it, 50 citations in OpenAlex.

  1. Pooled it
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  10. Preleukemic Fusion Genes Induced via Ionizing Radiation.International journal of molecular sciences · 2023
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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

13 authors at 9 institutions in 4 countries.

Mark P Littlea  Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland 20892;
Deukwoo Kwon
Kazataka Doi
Steven L Simon
Dale L Preston
Michele M Doody
Terrence Lee
Jeremy S Miller
Diane M Kampa
Parveen Bhatti
James D Tucker
Martha S Linet
Alice J Sigurdson
National Cancer Institute · USNational Cancer Institute · UAAssociated Management Services (United States) · USCape Town HVTN Immunology Laboratory / Hutchinson Centre Research Institute of South Africa · ZADivision of Cancer Epidemiology and GeneticsINTRASOFT International (Luxembourg) · LUSylvester Comprehensive Cancer Center · USUniversity of Minnesota · USWayne State University · US

Funding

Studies of Populations Exposed to Occupational Sources of RadiationZIACP010133 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI KITAHARA, CARI · 2009 to 2025
$34.2M
Intramural NIH HHS Z99 CA999999
6 · The paper itself

Abstract

Chromosome translocations are a well-recognized biological marker of radiation exposure and cancer risk. However, there is uncertainty about the lowest dose at which excess translocations can be detected, and whether there is temporal decay of induced translocations in radiation-exposed populations. Dosimetric uncertainties can substantially alter the shape of dose-response relationships; although regression-calibration methods have been used in some datasets, these have not been applied in radio-occupational studies, where there are also complex patterns of shared and unshared errors that these methods do not account for. In this article we evaluated the relationship between estimated occupational ionizing radiation doses and chromosome translocation rates using fluorescent in situ hybridization in 238 U.S. radiologic technologists selected from a large cohort. Estimated cumulative red bone marrow doses (mean 29.3 mGy, range 0-135.7 mGy) were based on available badge-dose measurement data and on questionnaire-reported work history factors. Dosimetric assessment uncertainties were evaluated using regression calibration, Bayesian and Monte Carlo maximum likelihood methods, taking account of shared and unshared error and adjusted for overdispersion. There was a significant dose response for estimated occupational radiation exposure, adjusted for questionnaire-based personal diagnostic radiation, age, sex and study group (5.7 translocations per 100 whole genome cell equivalents per Gy, 95% CI 0.2, 11.3, P = 0.0440). A significant increasing trend with dose continued to be observed for individuals with estimated doses <100 mGy. For combined estimated occupational and personal-diagnostic-medical radiation exposures, there was a borderline-significant modifying effect of age (P = 0.0704), but little evidence (P > 0.5) of temporal decay of induced translocations. The three methods of analysis to adjust for dose uncertainty gave similar results. In summary, chromosome translocation dose-response slopes were detectable down to <100 mGy and were compatible with those observed in other radiation-exposed populations. However, there are substantial uncertainties in both occupational and other (personal-diagnostic-medical) doses that may be imperfectly taken into account in our analysis.

Indexed as

AgedAged, 80 and overCohort StudiesDose-Response Relationship, RadiationFemaleHumansIn Situ Hybridization, FluorescenceMaleMiddle AgedMonte Carlo MethodOccupational ExposureProbabilityRiskTechnology, RadiologicTime FactorsTranslocation, Genetic

Identifiers

PMID24932535
PMCPMC4829936
OpenAlexW2111939524

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Read underepoch 390

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.