Post-Chornobyl Thyroid Cancers in Ukraine. Report 2: Risk Analysis

Likhtarov, Illya; Kovgan, L.; Vavilov, Sergey; Chepurny, Mykola; Ron, Elaine; Lubin, Jay H.; Bouville, André; Тronko, М.D.; Bogdanova, Tetiana; Gulak, L.; Zablotska, Lydia B.; Howe, Geoffrey R.

doi:10.1667/rr3593.1

Cited by 50 publications

(48 citation statements)

References 31 publications

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“…• The radiation risk parameters used are close to the quantities obtained in Jacob, et al (2006), Likhtarev, et al (2006a and . • The risk model is the simplest but quite popular generalized linear model of absolute risk with binary response (see below) that makes it possible to verify and compare the results with estimates obtained by the well-known program package EPICURE.…”

Section: Introductionsupporting

confidence: 57%

“…• In the second scenario, at the preliminary stage the cutoff was not performed, and the subpopulation was artificially enlarged to N = 70 770 persons (see Figure 2). The true parameters of the absolute risk model (1) were given by the values close to the estimates obtained in the epidemiological studies of the thyroid cancers in Ukraine (Jacob, et al, 2006;Likhtarev, et al, 2006a • f i is the estimate from the ecological dosimetric model, see Likhtarev et al (2006b), • for Q tr i we took the thyroid activity measured in 1986, see Likhtarev et al (1993), • and M mes i is the median of the thyroid mass distribution for corresponding age-sex-region group, see Chornobyl: A Decade (1997).…”

Section: Two Simulation Scenariosmentioning

confidence: 52%

“…We performed a simulation study based on data from epidemiological investigations (see Jacob, et al, 2006;Likhtarev, et al, 2005;Likhtarev, et al, 2006a;Likhtarev, et al, 2006b). For the simulation of doses a real subpopulation of 7077 children and teenagers up to 18 years was used; these persons resided in settlements of Zhitomir, Kyiv, and Chernigov Oblasts of Ukraine at the time of the Chornobyl accident and had direct measurements of thyroid activity in May-June 1986.…”

Section: Simulation 61 Simulation Setupmentioning

confidence: 99%

“…The current methods of risk estimation (see Health Risks from Exposure to Low Levels of Ionizing Radiation, 2006;Jacob et al, 2006;Likhtarev et al, 2006a) take into account uncertainties related to health effects, but assume that the doses are known with perfect precision and accuracy, something that is not true (Kopecky et al, 2006;Likhtarev et al, 1993;Likhtarev et al, 2003;Ron and Hoffman, 1999). Although many attempts have been made to develop mathematical tools which take into account the dose uncertainty (see Carroll et al, 2006;Hofer, 2008;Kopecky et al, 2006;Li et al, 2007;Masiuk et al, 2008), the problem has yet to be solved in a satisfactory manner.…”

Section: Introductionmentioning

confidence: 99%

“…It is our opinion that one of the reasons an accurate model is so hard to create is because the dose estimates are almost inevitably associated with a mixture of classical and Berkson errors (Reeves et al, 1998;Carroll et al, 2006;Li et al, 2007), which leads to difficulties in evaluating the influence of the mixed errors in the estimated dose on risk analysis, which is usually expressed in terms of relative (ERR) or absolute (EAR) risk (see Health Risks from Exposure to Low Levels of Ionizing Radiation, 2006). One such example is the analysis of epidemiological investigations of thyroid cancer among children exposed to radioiodines in fallout from the Chornobyl accident (Jacob et al, 2006;Likhtarev et al, 2006a;Tronko et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

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Methods for Estimation of Radiation Risk in Epidemiological Studies Accounting for Classical and Berkson Errors in Doses

Kukush¹,

Shklyar²,

Masiuk³

et al. 2011

The International Journal of Biostatistics

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With a binary response Y, the dose-response model under consideration is logistic in flavor with pr(Y=1 | D) = R (1+R) By means of Parametric Full Maximum Likelihood and Regression Calibration (under the assumption that the data set of true doses has lognormal distribution), Nonparametric Full Maximum Likelihood, Nonparametric Regression Calibration, and by properly tuned SIMEX method we study the influence of measurement errors in thyroid dose on the estimates of λ 0 and EAR. The simulation study is presented based on a real sample from the epidemiological studies. The doses were reconstructed in the framework of the Ukrainian-American project on the investigation of Post-Chernobyl thyroid cancers in Ukraine, and the underlying subpolulation was artificially enlarged in order to increase the statistical power. The true risk parameters were given by the values to earlier epidemiological studies, and then the binary response was simulated according to the dose-response model.-

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Section: Introductionsupporting

confidence: 57%

Section: Two Simulation Scenariosmentioning

confidence: 52%

Section: Simulation 61 Simulation Setupmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Methods for Estimation of Radiation Risk in Epidemiological Studies Accounting for Classical and Berkson Errors in Doses

Kukush¹,

Shklyar²,

Masiuk³

et al. 2011

The International Journal of Biostatistics

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Long‐term Adverse Health Consequences from Exposure to Products Generated from Major Disaster Sites

Mauer

2009

General, Applied and Systems Toxicology

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Major disasters have been a constant reality since ancient times, repeatedly causing disruption, illness and death. This review presents epidemiological evidence regarding long‐term health effects from a selection of major disasters, which represent some of the more thoroughly studied events in history. The World Trade Center disaster, Bhopal and Seveso chemical releases, Chernobyl nuclear accident and Mount St. Helens and Soufriere Hills volcanic eruptions are discussed in some detail. While this review provides an overview of potential long‐term health outcomes from several types of disasters, it also illustrates the gaps in knowledge that exist for some of these events. There exists a relative lack of research on long‐term health effects for many types of disasters. By illuminating these issues, this review may help to emphasize the importance of focussing efforts and available resources on the study of long‐term health effects related to future disasters.

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Epigenetic Effects of Ionizing Radiation

Kovalchuk

2013

Environmental Epigenomics in Health and Disease

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Pancreatic cancer is associated with a high mortality rate, owing to de novo and acquired drug resistance, thereby leading to highly invasive and metastatic pancreatic cancer cells. Therefore, targeting pancreatic cancer stem cells (CSCs) may be a novel therapeutic strategy for the treatment of pancreatic cancer. Here, we combined a DNA methylation inhibitor (5-aza-2'-deoxycytidine; 5-aza-dC) and ionizing radiation (IR) to improve anti-cancer effects by inhibiting growth and proliferation and promoting apoptosis of pancreatic cancer cells in vitro and in vivo. Importantly, the combinatorial effect of 5-aza-dC with IR on sphere-forming pancreatic cancer cells was preferentially targeted toward CSCs through the downregulation of regulatory factors of self-renewal and CSC surface markers. We next performed the RNA sequencing to understand the underlying cellular mechanisms of the combined treatment with IR and 5-aza-dC in pancreatic cancer cells. Global transcriptome profiling indicated that the expression of the Oct4-centered transcriptional network of genes was significantly downregulated in cells with combination treatment. Our data suggested that combination treatment with DNA methylation inhibitor and IR may be a novel therapeutic strategy for pancreatic cancer. Overall, these findings support the use of epigenetic therapy in combination with radiotherapy to improve therapeutic efficacy by targeting and eradicating pancreatic CSCs.

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Post-Chornobyl Thyroid Cancers in Ukraine. Report 2: Risk Analysis

Cited by 50 publications

References 31 publications

Methods for Estimation of Radiation Risk in Epidemiological Studies Accounting for Classical and Berkson Errors in Doses

Methods for Estimation of Radiation Risk in Epidemiological Studies Accounting for Classical and Berkson Errors in Doses

Long‐term Adverse Health Consequences from Exposure to Products Generated from Major Disaster Sites

Epigenetic Effects of Ionizing Radiation

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