Health Risks from Exposure to Low Levels of Ionizing Radiation BEIR VII Phase 2 (2006) / Chapter Skim
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12 Estimating Cancer Risk
12 Estimating Cancer Risk
Pages 267-312
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From page 267... ...
radiation, risk models are based primarily from data on Japanese atomic bomb survivors. However, the vast litera- DATA EVALUATED FOR BEIR VII MODELS ture on both medically exposed persons and nuclear workers As in earlier BEIR reports addressing health effects from exposed at relatively low doses has been reviewed to evalu exposure to low-LET radiation, the committee's models for ate whether findings from these studies are compatible with risk estimation are based primarily on the Life Span Study A-bomb survivor-based models.
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found little evidence of heterogeneity POINTS among excess relative risk (ERR) 1 models developed for To express the health impact of whole-body exposures to several specific cancer sites.
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. Both excess relative risk models and excess and attained age, but make use only of data for the site of absolute risk (EAR)
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40 Age at exposure 10 Age at exposure 10 Age at exposure 20 Sv) PY-Sv 30 Age at exposure 20 (1 Age at exposure 30+ Age at exposure 30+ Risk 10,000 per 20 Relative deaths Excess 10 Excess 0 30 40 50 60 70 80 90 Attained age Attained age FIGURE 12-1B Age-time patterns in the radiation-associated risks for all solid cancer mortality.
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The committee's preferred crease with exposure age in the ERR or EAR after exposure models for estimating solid cancer risks are similar to the age 30, and there was even a suggestion of an increase at RERF model, except that the ERR and EAR depend on age older ages. Further discussion of the rationale for choosing at exposure only for exposure ages under 30 years and are the Equation (12-2)
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This approach is similar Although the committee provides risk estimates for both to that used by UNSCEAR (2000b) except that the commitcancer incidence and mortality, models for site-specific cancers were based on cancer incidence data.
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The committee's preferred model for estimating thyroid cancer incidence is based on a pooled analysis of data from seven thyroid cancer incidence studies conducted by Ron Models for Female Breast Cancer and colleagues (1995a)
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0.88 Sv1 (0.16, 15) In Chapter 10, both data on solid cancer risks in the LSS cohort and experimental data pertinent to this issue are evaluNOTE: Estimated parameters with 95% CIsd based on likelihood ratio ated by the committee.
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workers found that leukemia risks 35 years following ex- For breast and thyroid cancer, the committee's models ternal radiation exposure were more than an order of magni- are based on combined analyses that include Caucasian subtude higher than risks for later periods (Shilnikova and oth- jects. For other solid cancer sites including leukemia, the ers 2003)
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However, it may be desirable to increase Relative Effectiveness of X-Rays and -Rays risk estimates in this report by a factor of 2 or 3 for the purpose of estimating risks from low-dose X-ray exposure. Risk estimates in this report have been developed primarily from data on A-bomb survivors and are thus directly Relative Effectiveness of Internal Exposure relevant to exposure from high-energy photons.
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. Lifetime risk estimates using relative risk transport attained age (a)
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For QUANTITATIVE EVALUATION OF UNCERTAINTY IN TABLE 12-4 Baseline Lifetime Risk Estimates of Cancer LIFETIME RISKS Incidence and Mortality Because of the various sources of uncertainty it is important to regard specific estimates of LAR with a healthy skep- Incidence Mortality ticism, placing more faith in a range of possible values. Al Cancer site Males Females Males Females though a confidence interval is the usual statistical device for doing so, the approach here also accounts for uncertain- Solid cancera 45,500 36,900 22,100 (11)
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, prostate, and uterus, lowed by colon and lung cancer. These three categories are estimates based on relative and absolute risk differ by a fac- also the most important contributors to cancer mortality.
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Although the transport than those obtained using the sum-of-sites approach, a dif- model has not been considered a major source of uncertainty ference that comes about in part because of the weighting in leukemia risk estimates (UNSCEAR 2000b; NIH 2003) , scheme used to combine estimates based on relative and ab- Table 12-7 shows that LAR estimates based on relative risk solute risk transport (particularly the greater weight given to transport are higher than those based on absolute risk transabsolute risk transport for lung cancer)
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These weights were reversed for lung cancer. Models for breast and thyroid cancer were based on data that included Caucasian subjects.
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cers based on both relative and absolute risk transport models without expressing a preference. Again to facilitate compari son, the UNSCEAR estimates in parentheses combine these Comparison of BEIR VII Risk Estimates with Those from estimates using the same approach adopted by the BEIR VII Other Sources committee and reducing them by a DDREF of 1.5.
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indicates that lung cancer evaluated site-specific mortality data through 1997 and can- and the residual category of other solid cancers are the stroncer incidence data through 1998. ICRP estimates were in- gest contributors to this difference.
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This standard error is tive risk used to calculate the assigned share, and it would be conveyed in Table 12-10 as the coefficient of variation, possible to extend this to lifetime risk estimates. which is the standard error of LAR as a percentage of the TABLE 12-10 Estimated Lifetime Attributable Risks of Solid Cancer Incidencea for a Population of Mixed Ages Exposed to 0.1 Gy (Corresponding to Table 12-5A)
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The lifetime risk estimates shown in Tables 12-5, Risk or Excess Absolute Risk 12-6, and 12-7 are also accompanied by subjective confidence intervals that include uncertainty from sampling The committee has based its risk estimates for all solid variation. cancers and for cancers of specific sites on models of the Uncertainty in parameter estimates may also come about form shown in Equation (12-2)
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Furpresent lifetime risk estimates for solid cancer mortality in thermore, studies frequently include only a limited range of the LSS cohort. Estimates based on ERR and EAR models exposure ages and thus provide little information on the were similar for those exposed at ages of 30 or more, but for modifying effect of this variable.
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The estimates from medical studies Thyroid Cancer can be considered an average over the exposure and attained ages of the study cohorts; in all cases, exposure occurred in The committee's model for thyroid cancer risks was based adulthood. The LSS estimates are for exposure at age 30 or on analyses of data from five studies of persons exposed older at attained age 60, ages that seem likely to be reasonunder age 15 (Ron and others 1995a)
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aSites had to meet the following criteria: (1) the BEIR VII committee provides lifetime risk estimates, (2)
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evalulung, bone, nonmelanoma skin cancer, female breast, uterus, ated patterns in the ERR/Gy for leukemia with age at expoand ovary. sure, time since exposure, and attained age in the LSS co Little found that estimates of the ERR/Gy based on the hort, women treated for cervical cancer, and patients treated medical studies were generally lower than those based on for ankylosing spondylitis.
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, cancer risk estimates. In contrast to previous BEIR reports, the committee presents estimates based on the assumption data on both cancer mortality and cancer incidence (from the that the excess risk due to radiation is proportional to Hiroshima and Nagasaki tumor registries)
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models are not given, but the general approaches that have The committee provides estimates of lifetime risks of been used are described. The committee begins with menboth cancer incidence and mortality for leukemia, all solid tion of the BEIR IV model for estimating lung cancer risks cancers, and cancers of several specific sites (stomach, co from exposure to radon, which is important because it was lon, liver, lung, female breast, prostate, uterus, ovary, blad the first major radiation risk assessment based on modeling der, and all other solid cancers)
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Although a major objective in developused was the excess lifetime risk, which excludes radiation- ing these weighting factors was to estimate the detrimental induced deaths in persons who would have died from the effects of radiation exposures that deliver nonuniform doses same cause at a later time in the absence of radiation expo- to various organs of the body, they can also be used to obtain sure. The BEIR V report provides estimates for excess mor- lifetime risks for site-specific cancers.
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The leukemia model was that developed , , and were set equal to those for all solid cancers unless by Preston and colleagues (1994) and based on A-bomb sur- there was evidence of significant departure from these valvivor leukemia incidence data for the period 19501987.
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Estimates based on both relative and absolute trans onset of such disease developed cancer as a result of these portation models were presented. With the absolute risk doses." The mandate included a provision for periodic upmodel, the absolute magnitude of the radiation risk is dating of the tables.
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. Nonmelanoma skin cancer risks were estimated tistically stable estimates at the extremes of the exposure from a special A-bomb survivor data set used by Ron and ages and attained ages.
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The material that follows describes analyses that dose, d, to the colon was used for the combined category of were conducted to evaluate several possible models for solid all solid cancers or all solid cancers excluding thyroid and cancer risks, including models that allow for dependence on nonmelanoma skin cancer. This choice was made to achieve age at exposure alone, on attained age alone, on time since comparability with analyses by RERF investigators.
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, then estimation of the effect of age at exposure General Considerations in Describing Dependencies of should be based on modeling the ERR. However, if the facSolid Cancer Risks on Exposure Age and Attained Age tors responsible for secular trends in baseline risks have no A decline in the solid cancer ERR with increasing expo- effect on radiation risks (an additive relationship)
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Cancer Site Males Females Total Males Females Total Analyses of Incidence Data on All Solid Cancers Excluding Stomach 1,899 1,703 3,602 1,555 1,312 2,867 Thyroid and Nonmelanoma Skin Cancer and of Mortality Colon 547 618 1,165 206 272 478 Data on All Solid Cancers Liver 676 470 1,146 722 514 1,236 Lung 770 574 1,344 716 548 1,264 The analyses of cancer incidence data described in this Breast 7 847 854 3 272 275 section were based on the category of all solid cancers ex- Prostate 281 0 281 104 0 104 cluding thyroid cancer and nonmelanoma skin cancer. These Ovary 0 190 190 0 136 136 exclusions were made primarily because both thyroid cancer Uterus 0 875 875 0 518 518 Bladder 227 125 352 83 67 150 and nonmelanoma skin cancer exhibit exceptionally strong Other solid 1,416 1,553 2,969 1,036 1,175 2,211 age dependencies that do not seem to be typical of cancers of Total 5,823 6,955 12,778 4,425 4,814 9,239 other sites (Thompson and others 1994)
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The function h includes parameters to thyroid cancer and nonmelanoma skin cancer and on mortalbe estimated. Most commonly, h is of the form ity from all solid cancers.
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. bERR-S: stratified excess relative risk model; ERR-P: parametric excess relative risk model; EAR-P: parametric excess absolute risk model.
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BEIR VII EAR model." Further exploration of the cancer incidence data revealed As another approach to evaluating alternative models, that the elevation of both ERR and EAR for the oldest exposeparate ERRs per sievert and EARs per 104 PY-Sv were sure age category was strongest for stomach and liver canestimated for each of five groups defined by age at exposure cers; for these cancers, js for the 60+ exposure age group TABLE 12B-3 Sex-Averaged Estimates of ERR/Sv and EAR per 104 PY-Sv by Age-at-Exposure Categories for All Solid Cancers Excluding Thyroid and Nonmelanoma Skina Age at Exposure Data Used <15 years 1530 years 3045 years 4560 years 60+ years Incidence datab Number of cases 2044 3465 4417 2526 326 ERR/Sv (95% CI)
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The two data, about 37% of the cancers in the solid cancer category EAR models show similar exposure age effects, but the rate that the committee analyzed were cancers of the stomach of increase with attained age is greater for the mortality data and liver; by contrast, SEER data for the United States (see than for the incidence data. Table 12-3)
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Results are shown for a model in which all four of the cancer incidence and mortality, models for site-specific cancers were based mainly on cancer incidence data. This was parameters M, F, , and were estimated and are also shown for a model in which the parameters quantifying the done primarily because site-specific cancer incidence data modifying effects of age of exposure and attained age and are based on diagnostic information that is more detailed and were set equal to the values obtained from analysis of the accurate than death certificate data and because, for several category all solid cancers excluding thyroid and nonsites, the number of incident cases is considerably larger than melanoma skin cancers; these values are referred to subsethe number of deaths.
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However, for these sites, there TABLE 12B-5B Results of Fitting Stratified ERR Models to Site-Specific Cancer Mortality Data Using the Model ERR(D, s, e, a)
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. viation from the all-solid-cancer estimate are considered in The analyses of site-specific cancer presented in the last developing site-specific estimates that draw both on data for few paragraphs address the use of common parameters to the specific individual site and on data for all solid cancers.
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With the exception of the category of all other solid site-specific data as evidenced from the parameter estimates cancers, the ERR models are based on common values of the shown in Table 12B-4. Nevertheless, the committee conparameters and that quantify the modifying effects of age ducted analyses of the solid cancer mortality data with paat exposure and attained age.
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, (12B-10) diagnostic information for non-type-specific leukemia mortality is thought to be much better than for most site-specific where e is age at exposure in years and t is time since exposolid cancers.
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. As an example, the estimated LAR based on relative risk transport so that the estimate of log (LAR)
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For most cancers, a value With the simplifying approximation that the "hats" can of .7 was taken for p. Exceptions were lung cancer, where be dropped from ^ A and ^ R in the middle term and the p = .3, and thyroid cancer, where only an ERR model devel- assumption that the uncertainties due to risk model estimaoped from data on Caucasian women was available.
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] = Tables 12D-1 and 12D-2 show lifetime risk estimates for cancer incidence and mortality resulting from a single dose var[logLARA(e, D;^ A)
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aThese estimates are obtained as combined estimates based on relative and absolute risk transport and have been adjusted by a DDREF of 1.5, except for leukemia, which is based on a linear-quadratic model. TABLE 12D-2 Lifetime Attributable Risk of Cancer Mortalitya Age at Exposure (years)
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312 BEIR VII TABLE 12D-3 Lifetime Attributable Risk of Solid Cancer Incidence and Mortalitya Incidence: Mortality: Exposure Scenario Exposure Scenario 1 mGy 10 mGy 1 mGy 10 mGy per Year per Year per Year per Year throughout from Ages throughout from Ages Cancer site Life 18 to 65 Life 18 to 65 Males Stomach 24 123 13 66 Colon 107 551 53 273 Liver 18 93 14 72 Lung 96 581 99 492 Prostate 32 164 6.3 32 Bladder 69 358 16 80 Other 194 801 85 395 Thyroid 14 28 All solid 554 2699 285 1410 Leukemia 67 360 47 290 All cancers 621 3059 332 1700 Females Stomach 32 163 19 94 Colon 72 368 34 174 Liver 8.7 44 8 40 Lung 229 1131 204 1002 Breast 223 795 53 193 Uterus 14 19 3.5 18 Ovary 29 140 18 91 Bladder 71 364 21 108 Other 213 861 98 449 Thyroid 75 139 All solid 968 4025 459 2169 Leukemia 51 270 38 220 All cancers 1019 4295 497 2389 NOTE: Number of cases or deaths per 100,000 persons exposed to 1 mGy per year throughout life or to 10 mGy per year from ages 18 to 64. aThese estimates are obtained as combined estimates based on relative and absolute risk transport and have been adjusted by a DDREF of 1.5, except for leukemia, which is based on a linear-quadratic model.
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