Evidence map›Paper›PMID 24489667›Full record

ArticlePloS one2014

Impact of uncertainties in exposure assessment on estimates of thyroid cancer risk among Ukrainian children and adolescents exposed from the Chernobyl accident.

Mark P Little, Alexander G Kukush, Sergii V Masiuk, Sergiy Shklyar, Raymond J Carroll, Jay H Lubin, Deukwoo Kwon, Alina V Brenner, Mykola D Tronko, Kiyohiko Mabuchi and 12 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 1 pooled it
5.1field-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

37 citing papers in PubMed, 1 synthesis or guideline pooled it, 47 citations in OpenAlex.

  1. Somatic health effects of Chernobyl: 30 years on.European journal of epidemiology · 2017
    Pooled it
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  18. Thyroid doses in Ukraine due toRadiation and environmental biophysics · 2021
    Article
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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

22 authors at 7 institutions in 2 countries.

Mark P LittleRadiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.
Alexander G KukushUkrainian Radiation Protection Institute, Kyiv, Ukraine ; Taras Shevchenko National University of Kyiv, Kyiv, Ukraine.
Sergii V MasiukUkrainian Radiation Protection Institute, Kyiv, Ukraine.
Sergiy ShklyarUkrainian Radiation Protection Institute, Kyiv, Ukraine ; Taras Shevchenko National University of Kyiv, Kyiv, Ukraine.
Raymond J CarrollDepartment of Statistics, Blocker Building, Texas A&M University, College Station, Texas, United States of America.
Jay H LubinBiostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.
Deukwoo KwonRadiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America ; Sylvester Comprehensive Cancer Center, University of Miami, Miami, Florida, United States of America.
Alina V BrennerRadiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.
Mykola D TronkoState Institution "Institute of Endocrinology and Metabolism of Academy of Medical Sciences of Ukraine", Kyiv, Ukraine.
Kiyohiko MabuchiRadiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.
Tetiana I BogdanovaState Institution "Institute of Endocrinology and Metabolism of Academy of Medical Sciences of Ukraine", Kyiv, Ukraine.
Maureen HatchRadiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.
Lydia B ZablotskaDepartment of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, United States of America.
Valeriy P TereshchenkoState Institution "Institute of Endocrinology and Metabolism of Academy of Medical Sciences of Ukraine", Kyiv, Ukraine.
Evgenia OstroumovaRadiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.
André C BouvilleRadiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.
Vladimir DrozdovitchRadiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.
Mykola I ChepurnyUkrainian Radiation Protection Institute, Kyiv, Ukraine.
Lina N KovganUkrainian Radiation Protection Institute, Kyiv, Ukraine.
Steven L SimonRadiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.
Victor M ShpakState Institution "Institute of Endocrinology and Metabolism of Academy of Medical Sciences of Ukraine", Kyiv, Ukraine.
Ilya A LikhtarevUkrainian Radiation Protection Institute, Kyiv, Ukraine.
National Cancer Institute · USRadiation Protection Institute · UANational Institutes of Health · USTaras Shevchenko National University of Kyiv · UATexas A&M University · USUniversity of California, San Francisco · USUniversity of Miami · US

Funding

Measurement Error, Nutrition and Breast/Colon CancerR37CA057030 · NCI · TEXAS A&M UNIVERSITY SYSTEM · PI CARROLL, RAYMOND J. · 2005 to 2014
$3.3M
MEASUREMENT ERROR, NUTRITION AND BREAST/COLON CANCERR01CA057030 · NCI · TEXAS A&M UNIVERSITY SYSTEM · PI CARROLL, RAYMOND J. · 1992 to 2004
$1.3M
Intramural NIH HHSNCI NIH HHS R01 CA057030NCI NIH HHS R37 CA057030NCI NIH HHS R37-CA057030
6 · The paper itself

Abstract

The 1986 accident at the Chernobyl nuclear power plant remains the most serious nuclear accident in history, and excess thyroid cancers, particularly among those exposed to releases of iodine-131 remain the best-documented sequelae. Failure to take dose-measurement error into account can lead to bias in assessments of dose-response slope. Although risks in the Ukrainian-US thyroid screening study have been previously evaluated, errors in dose assessments have not been addressed hitherto. Dose-response patterns were examined in a thyroid screening prevalence cohort of 13,127 persons aged <18 at the time of the accident who were resident in the most radioactively contaminated regions of Ukraine. We extended earlier analyses in this cohort by adjusting for dose error in the recently developed TD-10 dosimetry. Three methods of statistical correction, via two types of regression calibration, and Monte Carlo maximum-likelihood, were applied to the doses that can be derived from the ratio of thyroid activity to thyroid mass. The two components that make up this ratio have different types of error, Berkson error for thyroid mass and classical error for thyroid activity. The first regression-calibration method yielded estimates of excess odds ratio of 5.78 Gy(-1) (95% CI 1.92, 27.04), about 7% higher than estimates unadjusted for dose error. The second regression-calibration method gave an excess odds ratio of 4.78 Gy(-1) (95% CI 1.64, 19.69), about 11% lower than unadjusted analysis. The Monte Carlo maximum-likelihood method produced an excess odds ratio of 4.93 Gy(-1) (95% CI 1.67, 19.90), about 8% lower than unadjusted analysis. There are borderline-significant (p = 0.101-0.112) indications of downward curvature in the dose response, allowing for which nearly doubled the low-dose linear coefficient. In conclusion, dose-error adjustment has comparatively modest effects on regression parameters, a consequence of the relatively small errors, of a mixture of Berkson and classical form, associated with thyroid dose assessment.

Indexed as

Chernobyl Nuclear AccidentEnvironmental ExposureIodine RadioisotopesAdolescentChildChild, PreschoolDose-Response Relationship, RadiationFemaleHumansIncidenceInfantInfant, NewbornLikelihood FunctionsMaleMonte Carlo MethodNeoplasms, Radiation-InducedIodine Radioisotopes

Identifiers

PMID24489667
PMCPMC3906013
OpenAlexW1963751503

What OpenQuestion holds

Textmetadata
LicenceCC0
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.