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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

Quasipoisson modelling of specific sites. In B+, the simplest quasipoisson models Q2e and Q2d (Table 2) are fitted to all solid cancers and specific sites. In each case, a preferred version is chosen to minimise ML when each model is refitted at the scale optimised for the other member of the pair. The preference is indicated by e or d in the panel title, and its RR and 90% CI are shown in bold while the unselected model is displayed in the background
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Fig10: Quasipoisson modelling of specific sites. In B+, the simplest quasipoisson models Q2e and Q2d (Table 2) are fitted to all solid cancers and specific sites. In each case, a preferred version is chosen to minimise ML when each model is refitted at the scale optimised for the other member of the pair. The preference is indicated by e or d in the panel title, and its RR and 90% CI are shown in bold while the unselected model is displayed in the background

Mentions: Specific sites were analyzed by quasipoisson models with the Pearson estimate of scale . Additional file 1: Table S7 gives details for Q2 in B+ at 21 sites, using scale estimates from Q2e and Q2d with identical values of min.sp. The ML score of Q2d at Q2d is compared with that of Q2e refitted at Q2d, and vice-versa. The same covariate was preferred whichever optimised scale was used. The Q2 response curves and preferred covariates are shown in Fig. 10. Q2e curves are smoothed for display.Fig. 10


Low dose radiation risks for women surviving the a-bombs in Japan: generalized additive model
Quasipoisson modelling of specific sites. In B+, the simplest quasipoisson models Q2e and Q2d (Table 2) are fitted to all solid cancers and specific sites. In each case, a preferred version is chosen to minimise ML when each model is refitted at the scale optimised for the other member of the pair. The preference is indicated by e or d in the panel title, and its RR and 90% CI are shown in bold while the unselected model is displayed in the background
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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

Fig10: Quasipoisson modelling of specific sites. In B+, the simplest quasipoisson models Q2e and Q2d (Table 2) are fitted to all solid cancers and specific sites. In each case, a preferred version is chosen to minimise ML when each model is refitted at the scale optimised for the other member of the pair. The preference is indicated by e or d in the panel title, and its RR and 90% CI are shown in bold while the unselected model is displayed in the background
Mentions: Specific sites were analyzed by quasipoisson models with the Pearson estimate of scale . Additional file 1: Table S7 gives details for Q2 in B+ at 21 sites, using scale estimates from Q2e and Q2d with identical values of min.sp. The ML score of Q2d at Q2d is compared with that of Q2e refitted at Q2d, and vice-versa. The same covariate was preferred whichever optimised scale was used. The Q2 response curves and preferred covariates are shown in Fig. 10. Q2e curves are smoothed for display.Fig. 10

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