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This study revised the thyroid doses for 2582 Ukrainian in utero cohort members exposed to Chornobyl fallout (the Ukrainian in utero cohort) based on revision of: (i) 131I thyroid activity measured in the Ukrainian population, (ii) thyroid dosimetry system for entire Ukraine, and (iii) 131I ground deposition densities in Ukraine. Other major improvements included: (i) assessment of uncertainties in the thyroid doses considering shared and unshared error, and (ii) accounting for intake of short-lived radioisotopes of tellurium and iodine (132Te+132I and 133I). Intake of 131I was the major pathway for thyroid exposure, its median contribution to the thyroid dose was 97.4%. The mean prenatal and postnatal thyroid dose from 131I was 87 mGy (median = 17 mGy), higher than previous deterministic dose of 72 mGy (median = 12 mGy). For 39 individuals (1.5%) the dose exceeded 1.0 Gy, while the highest dose among the cohort members was 2.7 Gy. The geometric standard deviation (GSD) of 1000 individual stochastic doses varied from 1.9 to 5.2 with a mean of 3.1 and a median of 3.2. The lowest uncertainty (mean GSD = 2.3, median GSD = 2.2) was found for the subjects whose mothers were measured for 131I thyroid activity, while for individuals, whose mothers were not measured, the mean and median GSDs were 3.4. Uncertainties in thyroid doses were driven by shared errors associated with the parameters of the ecological model.

A large excess risk of thyroid cancer was observed among Belarusian/Russian/Baltic Chornobyl cleanup workers. A more recent study of Ukraine cleanup workers found more modest excess risks of thyroid cancer. Dose errors in this data are substantial, associated with model uncertainties and questionnaire response. Regression calibration is often used for dose-error adjustment, but may not adequately account for the full error distribution. We aimed to examine the impact of exposure-assessment uncertainties on thyroid cancer among Ukrainian cleanup workers using Monte Carlo maximum likelihood, and compare with results derived using regression calibration. Analyses assessed the sensitivity of results to various components of internal and external dose. Regression calibration yielded an excess odds ratio per Gy (EOR/Gy) of 0.437 (95% CI - 0.042, 1.577, p = 0.100), compared with the EOR/Gy using Monte Carlo maximum likelihood of 0.517 (95% CI - 0.039, 2.035, p = 0.093). Trend risk estimates for follicular morphology tumors exhibited much more extreme effects of full-likelihood adjustment, the EOR/Gy using regression calibration of 3.224 (95% CI - 0.082, 30.615, p = 0.068) becoming ~ 50% larger, 4.708 (95% CI - 0.075, 85.143, p = 0.066) when using Monte Carlo maximum likelihood. Results were sensitive to omission of external components of dose. In summary, use of Monte Carlo maximum likelihood adjustment for dose error led to increases in trend risks, particularly for follicular morphology thyroid cancers, where risks increased by ~ 50%, and were borderline significant. The unexpected finding for follicular tumors needs to be replicated in other exposed groups.