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Low dose radiation risks for women surviving the a-bombs in Japan: generalized additive model

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ABSTRACT

Background: Analyses of cancer mortality and incidence in Japanese A-bomb survivors have been used to estimate radiation risks, which are generally higher for women. Relative Risk (RR) is usually modelled as a linear function of dose. Extrapolation from data including high doses predicts small risks at low doses. Generalized Additive Models (GAMs) are flexible methods for modelling non-linear behaviour.

Methods: GAMs are applied to cancer incidence in female low dose subcohorts, using anonymous public data for the 1958 – 1998 Life Span Study, to test for linearity, explore interactions, adjust for the skewed dose distribution, examine significance below 100 mGy, and estimate risks at 10 mGy.

Results: For all solid cancer incidence, RR estimated from 0 – 100 mGy and 0 – 20 mGy subcohorts is significantly raised. The response tapers above 150 mGy. At low doses, RR increases with age-at-exposure and decreases with time-since-exposure, the preferred covariate. Using the empirical cumulative distribution of dose improves model fit, and capacity to detect non-linear responses. RR is elevated over wide ranges of covariate values. Results are stable under simulation, or when removing exceptional data cells, or adjusting neutron RBE. Estimates of Excess RR at 10 mGy using the cumulative dose distribution are 10 – 45 times higher than extrapolations from a linear model fitted to the full cohort. Below 100 mGy, quasipoisson models find significant effects for all solid, squamous, uterus, corpus, and thyroid cancers, and for respiratory cancers when age-at-exposure > 35 yrs. Results for the thyroid are compatible with studies of children treated for tinea capitis, and Chernobyl survivors. Results for the uterus are compatible with studies of UK nuclear workers and the Techa River cohort.

Conclusion: Non-linear models find large, significant cancer risks for Japanese women exposed to low dose radiation from the atomic bombings. The risks should be reflected in protection standards.

Electronic supplementary material: The online version of this article (doi:10.1186/s12940-016-0191-3) contains supplementary material, which is available to authorized users.

No MeSH data available.


Related in: MedlinePlus

0 – 4 Gy interactions with age at 1 Gy. For all solid cancers in the full female dataset including NIC, as in [1], RR at 1000 mGy is plotted against age for the Poisson models P5ae and P5ad (Table 2), with agex fixed at 10, 35 and 60. Likewise RR at 1000 mGy is plotted against age for the Poisson models P5se and P5sd, with since fixed at 15, 35, and 50
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Fig11: 0 – 4 Gy interactions with age at 1 Gy. For all solid cancers in the full female dataset including NIC, as in [1], RR at 1000 mGy is plotted against age for the Poisson models P5ae and P5ad (Table 2), with agex fixed at 10, 35 and 60. Likewise RR at 1000 mGy is plotted against age for the Poisson models P5se and P5sd, with since fixed at 15, 35, and 50

Mentions: At 1 Gy, the interaction of ecdos or dose with logage and agex from fitting P5a over J+ is consistent with [1], whose Fig. 4 is comparable with Fig. 11 here. If agex or since is fixed, RR /1 Gy decreases with age. Preston’s Fig. 6 (using smoothed category estimates) is comparable with the curve for 1000 mGy in Fig. 12 panel (P5ad at age 70). At age 70, RR /1 Gy initially decreases with agex but rises when agex > 40. Using P5sd, with better fit, at age 70 RR /1 Gy peaks at since 35. Similar curves arise at age 50, but with higher values of RR.Fig. 11


Low dose radiation risks for women surviving the a-bombs in Japan: generalized additive model
0 – 4 Gy interactions with age at 1 Gy. For all solid cancers in the full female dataset including NIC, as in [1], RR at 1000 mGy is plotted against age for the Poisson models P5ae and P5ad (Table 2), with agex fixed at 10, 35 and 60. Likewise RR at 1000 mGy is plotted against age for the Poisson models P5se and P5sd, with since fixed at 15, 35, and 50
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC5121957&req=5

Fig11: 0 – 4 Gy interactions with age at 1 Gy. For all solid cancers in the full female dataset including NIC, as in [1], RR at 1000 mGy is plotted against age for the Poisson models P5ae and P5ad (Table 2), with agex fixed at 10, 35 and 60. Likewise RR at 1000 mGy is plotted against age for the Poisson models P5se and P5sd, with since fixed at 15, 35, and 50
Mentions: At 1 Gy, the interaction of ecdos or dose with logage and agex from fitting P5a over J+ is consistent with [1], whose Fig. 4 is comparable with Fig. 11 here. If agex or since is fixed, RR /1 Gy decreases with age. Preston’s Fig. 6 (using smoothed category estimates) is comparable with the curve for 1000 mGy in Fig. 12 panel (P5ad at age 70). At age 70, RR /1 Gy initially decreases with agex but rises when agex > 40. Using P5sd, with better fit, at age 70 RR /1 Gy peaks at since 35. Similar curves arise at age 50, but with higher values of RR.Fig. 11

View Article: PubMed Central - PubMed

ABSTRACT

Background: Analyses of cancer mortality and incidence in Japanese A-bomb survivors have been used to estimate radiation risks, which are generally higher for women. Relative Risk (RR) is usually modelled as a linear function of dose. Extrapolation from data including high doses predicts small risks at low doses. Generalized Additive Models (GAMs) are flexible methods for modelling non-linear behaviour.

Methods: GAMs are applied to cancer incidence in female low dose subcohorts, using anonymous public data for the 1958 – 1998 Life Span Study, to test for linearity, explore interactions, adjust for the skewed dose distribution, examine significance below 100 mGy, and estimate risks at 10 mGy.

Results: For all solid cancer incidence, RR estimated from 0 – 100 mGy and 0 – 20 mGy subcohorts is significantly raised. The response tapers above 150 mGy. At low doses, RR increases with age-at-exposure and decreases with time-since-exposure, the preferred covariate. Using the empirical cumulative distribution of dose improves model fit, and capacity to detect non-linear responses. RR is elevated over wide ranges of covariate values. Results are stable under simulation, or when removing exceptional data cells, or adjusting neutron RBE. Estimates of Excess RR at 10 mGy using the cumulative dose distribution are 10 – 45 times higher than extrapolations from a linear model fitted to the full cohort. Below 100 mGy, quasipoisson models find significant effects for all solid, squamous, uterus, corpus, and thyroid cancers, and for respiratory cancers when age-at-exposure > 35 yrs. Results for the thyroid are compatible with studies of children treated for tinea capitis, and Chernobyl survivors. Results for the uterus are compatible with studies of UK nuclear workers and the Techa River cohort.

Conclusion: Non-linear models find large, significant cancer risks for Japanese women exposed to low dose radiation from the atomic bombings. The risks should be reflected in protection standards.

Electronic supplementary material: The online version of this article (doi:10.1186/s12940-016-0191-3) contains supplementary material, which is available to authorized users.

No MeSH data available.


Related in: MedlinePlus