Evidence map›Paper›PMID 25574587›Full record

ArticleRadiation research2015

Accounting for shared and unshared dosimetric uncertainties in the dose response for ultrasound-detected thyroid nodules after exposure to radioactive fallout.

Charles E Land, Deukwoo Kwon, F Owen Hoffman, Brian Moroz, Vladimir Drozdovitch, André Bouville, Harold Beck, Nicholas Luckyanov, Robert M Weinstock, Steven L Simon

Open access · greenAbstract read
In one paragraph

Article in Radiation research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
4.9field-weighted citation impact, top 5% 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

38 citing papers in PubMed, 62 citations in OpenAlex.

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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

10 authors at 4 institutions in 1 country.

Charles E Land *National Cancer Institute (retired), Bethesda, Maryland.
Deukwoo Kwon *Sylvester Comprehensive Cancer Center, University of Miami, Miami, Florida.
F Owen HoffmanOak Ridge Center for Risk Analysis, Oak Ridge, Tennessee.
Brian MorozNational Cancer Institute, Bethesda, Maryland.
Vladimir DrozdovitchNational Cancer Institute, Bethesda, Maryland.
André BouvilleNational Cancer Institute (retired), Bethesda, Maryland.
Harold BeckNew York, New York (DOE retired).
Nicholas LuckyanovNational Cancer Institute (retired), Bethesda, Maryland.
Robert M WeinstockNational Cancer Institute (retired), Bethesda, Maryland.
Steven L SimonNational Cancer Institute, Bethesda, Maryland.
National Cancer Institute · USOak Ridge National Laboratory · USSylvester Comprehensive Cancer Center · USVehicle Technologies Office · US

Funding

Studies of Populations Exposed to Environmental Sources of RadiationZIACP010132 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI CAHOON, ELIZABETH · 2009 to 2025
$35.2M
NCI NIH HHS Y03 CO005117NCI NIH HHS Y3-CO-5117PHS HHS Y2-AL-5077
6 · The paper itself

Abstract

Dosimetic uncertainties, particularly those that are shared among subgroups of a study population, can bias, distort or reduce the slope or significance of a dose response. Exposure estimates in studies of health risks from environmental radiation exposures are generally highly uncertain and thus, susceptible to these methodological limitations. An analysis was published in 2008 concerning radiation-related thyroid nodule prevalence in a study population of 2,994 villagers under the age of 21 years old between August 1949 and September 1962 and who lived downwind from the Semipalatinsk Nuclear Test Site in Kazakhstan. This dose-response analysis identified a statistically significant association between thyroid nodule prevalence and reconstructed doses of fallout-related internal and external radiation to the thyroid gland; however, the effects of dosimetric uncertainty were not evaluated since the doses were simple point "best estimates". In this work, we revised the 2008 study by a comprehensive treatment of dosimetric uncertainties. Our present analysis improves upon the previous study, specifically by accounting for shared and unshared uncertainties in dose estimation and risk analysis, and differs from the 2008 analysis in the following ways: 1. The study population size was reduced from 2,994 to 2,376 subjects, removing 618 persons with uncertain residence histories; 2. Simulation of multiple population dose sets (vectors) was performed using a two-dimensional Monte Carlo dose estimation method; and 3. A Bayesian model averaging approach was employed for evaluating the dose response, explicitly accounting for large and complex uncertainty in dose estimation. The results were compared against conventional regression techniques. The Bayesian approach utilizes 5,000 independent realizations of population dose vectors, each of which corresponds to a set of conditional individual median internal and external doses for the 2,376 subjects. These 5,000 population dose vectors reflect uncertainties in dosimetric parameters, partly shared and partly independent, among individual members of the study population. Risk estimates for thyroid nodules from internal irradiation were higher than those published in 2008, which results, to the best of our knowledge, from explicitly accounting for dose uncertainty. In contrast to earlier findings, the use of Bayesian methods led to the conclusion that the biological effectiveness for internal and external dose was similar. Estimates of excess relative risk per unit dose (ERR/Gy) for males (177 thyroid nodule cases) were almost 30 times those for females (571 cases) and were similar to those reported for thyroid cancers related to childhood exposures to external and internal sources in other studies. For confirmed cases of papillary thyroid cancers (3 in males, 18 in females), the ERR/Gy was also comparable to risk estimates from other studies, but not significantly different from zero. These findings represent the first reported dose response for a radiation epidemiologic study considering all known sources of shared and unshared errors in dose estimation and using a Bayesian model averaging (BMA) method for analysis of the dose response.

Indexed as

Dose-Response Relationship, RadiationModels, StatisticalAdolescentBody BurdenChildChild, PreschoolComputer SimulationEnvironmental ExposureFemaleHumansIncidenceInfantInfant, NewbornKazakhstanMaleNeoplasms, Radiation-InducedRadioactive Fallout

Identifiers

PMID25574587
PMCPMC4423551
OpenAlexW1985491973

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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.