Health Effects of Exposure to Low Levels of Ionizing Radiation BEIR V (1990) / Chapter Skim
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4 Risk of Cancer--All Sites
4 Risk of Cancer--All Sites
Pages 161-241
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From page 161... ...
4 Risks of Cancer All Sites INTRODUCTION This report seeks to present the best description that can be provided at this time of the risk of cancer resulting from a specified dose of ionizing radiation. However, this description is bound to be inexact since the etiology of radiation-induced cancer is complex and incompletely understood.
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From page 162... ...
Nevertheless, the limitations of the data bases on which the Committee's risk estimates are based have conditioned the kinds of estimates that can be developed. Heretofore, cancer risk estimates for low-LET radiations have been made by BEIR committees on the basis of constant additive risk and constant relative risk models (NRC80)
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From page 163... ...
In this respect, the report differs from that of the United Nations Scientific Committee on the Effects of Radiation (IJN88) , which presented two lifetime risk estimates from fatal cancer at each of 10 individual organ sites, one estimate based on a simple additive risk model and the other based on a simple multiplicative risk model.
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From page 164... ...
for A-bomb survivors is discussed, survivors exposures are stratified into ten groups and organ doses calculated by multiplying the neutron and gamma kermas for each stratum by cityspecific and age-specific body transmission factors. As the estimate of the neutron component under DS86 is quite small and not very different between the two cities, there is virtually no prospect for estimating the RBE for neutrons from the available data.
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From page 165... ...
Mortality among A-bomb survivors due to leukemia, cancer of the respiratory tract, cancer of the digestive tract, breast cancer, and as a group, all "other" cancers was analyzed in detail for the lifetime risk projections described below. In making this selection, the committee fitted models for ten sites or groups of sites, with the number of cancer deaths ranging from 2034 to 34.
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From page 166... ...
In general, the excess risk function, gads will depend upon a number of parameters, for example, sex, attained age, age-at-exposure, and time-since-exposure. One can also write the age-specific risk as an additive risk model :(d)
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From page 167... ...
The Committee's Preferred Risk Models The committee's models for each site are discussed in the respective sections on site specific cancers in Chapter 5. Only a brief summary and the equations for dose response are presented here.
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From page 168... ...
. The Monte Carlo analysis of the statistical uncertainty in the risk estimates for leukemia, described below in the section on uncertainty in point estimates, provides a better measure of the precision.
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From page 169... ...
These issues are discussed in some detail in Annex 4E and the section on breast cancer, in Chapter 5. The model for breast cancer age specific mortality (female only)
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From page 170... ...
When attempted, the models were quite unstable, resulting in risk estimates for which there was little confidence. The general group of "other cancers" was reasonably fit by a simple model with only a negative linear effect by age-at-exposure at ages greater than 10.
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From page 171... ...
The fitted risk models described above were applied to a stationary population having United States death rates for 1979-81 (NCHS85) and lifetime risks calculated for the following patterns of exposure.
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From page 173... ...
173 o ', x 1 o o o ~ , ~ ~ r~ ~ ~ ~0 _ oo o _ o S ° ~ Cq ~_ ~ ~,, - ~ ~ ~ ~.
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From page 174... ...
In the other reports, the differences in age-specific rates between exposed and unexposed populations were multiplied by the survival probabilities for an exposed population and summed. Because an exposed population will have smaller survival probabilities, the method used here produces lower excess risk estimates, which more correctly reflect the difference in the lifetime risk of cancer mortality.
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From page 175... ...
90% confidence interval for these risk estimates are listed in Annex 4D, Table 4D-4. to this Committee's use of a linear dose response model for cancers other than leukemia rather than a linear quadratic one with an implicit DREF of nearly 2.5, as was the case in the BEIR III Committee's report.
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From page 176... ...
It is the opinion of this committee that the assumption of a constant additive excess risk is no longer tenable in the face of the data now available and that the risk estimates from this model provided in the BEIR III report are therefore too low. The estimates presented In this report are also higher than those based on a simple additive risk model in the latest UNSCEAR report (UN88)
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From page 177... ...
RISKS OF CANCER-ALL SITES o' a, E IL 6tS l-OOS 66t 1-OSb 6hb 1-00t 66£1 -OS£ 1 u)
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From page 178... ...
. Results of 1,000 Monte Carlo simulations and lifetable analyses of the excess mortality from leukemia following an acute total body dose of 0.1 Sv.
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From page 179... ...
2gO 280 270 260 250 240 230 220 210 200 190 180 170 100 150 o 130 120 110 100 70 60 50 40 20 10 o 140 F~mn lam w ~ ~ ~ w ~ ~ ~ w .. ____wwww~ 0 ~ w ~ ~ 0 ~ 0 ~ 0 ~ 0 ~ 0 0 ~ ~ ~ 0 w ~ ~ 0 _ _ _ _ w w w w EXCESS LEUKEMIA DEATHS per 104 PERSON Sv 179 ~ ~ ~ W ~ ~ ~ .
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From page 180... ...
These histograms give a good idea of the statistical uncertainty in the Committee's risk models. Able 4-2 summarizes the resulting 90% confidence limits due to statistical uncertainty on the lifetime risk estimates for each of three exposure patterns.
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From page 181... ...
1989. Breast cancer mortality following irradiation in a cohort of Canadian Tuberculosis Patients.
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From page 182... ...
1988. The effect of changes in dosimet~y on cancer mortality risk estimates in atomic bomb survivors.
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From page 183... ...
Number of Cancer Deaths (Sh87) leukemia 202 colon 232 ovary 82 esophagus 176 multiple myeloma 36 bladder 133 stomach 2007 female breast 155 lung 638 Incidence data are also being gathered and studied, the most prominent being data on breast cancer (~87~.
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From page 184... ...
However, there does not seem to be evidence of infectious disease; instead the lower mortality rates in the moderately exposed individuals result from lower rates of death from a variety of causes (Damp. It does not appear, at this point, that these differences in mortality contribute in any substantial way to cancer mortality risk estimates based upon data from this cohort.
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From page 185... ...
Only cancer mortality, and not cancer incidence data are available for the cohort. Study of Women Treated for Cancer of the Cervix Cohon Source and Exposure The cohort consists of approximately 150,000 women treated for cancer of the uterine cervix who were either registered in one of 19 populationbased cancer registries or treated at one of 20 clinics in a number of countries.
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From page 186... ...
The choice of a case-control analysis in order to make such dose estimates computationally feasible, however, means that absolute risk estimates can be made only by imputation. The most serious limitation of this study arises from the fact that the subjects had all developed cancer of the cervix, with its many associated risk factors, particularly those relating to socio-economic status.
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From page 187... ...
187 Strengths and Limitations This cohort has reported the largest number of breast cancer deaths observed to date in a single cohort, and the exposure is highly fractionated, and in a North American population. However, these subjects all had tuberculosis, and although comparisons are made internally within the cohort, extrapolations to the general population may require caution.
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From page 188... ...
Follow-up The vital status of 97% of the cohort through 1980 has been determined from hospital records, death certificates, and mailed questionnaires (Hr88~. A total of 74 breast cancer cases have been observed in this cohort, with a total accumulation of 30,932 women-years at risk Advantages and Limitations The exposure in this study was highly fractionated, and the population is a U.S.
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From page 189... ...
1987. Comparison of risk coefficients for site-speeifie cancer mortality based on the DS86 and T65DR shielded kerma and organ doses.
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From page 190... ...
Before outlining these differences, it is necessary to identify the various ways dose estimates for the A-bomb survivors have been specified, as this can be a source of confusion when comparing results obtained with the new and older dosimetries. In RERF reports, particularly those on the Life Span Study, individual survivors are categorized in terms of the incident radiation, i.e., the kerma, at the location where a survivor was exposed.
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From page 191... ...
How much smaller depends on the location of a particular organ within the body and the orientation of the survivor in the radiation field. In this report, as in the BEIR III report, risk estimates are based on organ doses, not the kerma at a survivor's location.
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From page 192... ...
N .~ . T65D DS86 Organ Dose Equivalent : : : i T65D Bone Marrow DS86 FIGURE 4B-1 Comparison of T65D and DS86 dose estimates for gamma rays and neutrons in Hiroshima.
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From page 193... ...
... e .~ N T65D DS86 Organ Dose Equivalent Bone Marrow DS86 T65D FIGURE 4B-2 Comparison of T65D and DS86 dose estimates for gamma rays and neutrons in Nagasaki.
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From page 194... ...
Organ doses were calculated by RERF for each survivor but were not used directly. Instead, average age-specific and city-specific body transmission factors are being used to estimate organ doses.
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From page 195... ...
Moreover, the A-bomb radiation had a substantial vertical component which leads to a rather atypical exposure geometry. Effective application of the Committee's risk estimates to other exposure situations are dependent therefore on a careful consideration of the dose distribution within the body and the resultant organ doses, as illustrated In Able 4B-1 for the A-bomb survivors.
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From page 196... ...
1987. The Effect of Change in Dosimetry on Cancer Mortality Risk Estimates in the Atomic Bomb Survivors.
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From page 197... ...
Some of the simpler relative risk models available in AMFIT can be fit using GLIM or PREG, and these three programs produce identical estimates in such cases. The committee chose to use AMFIT in the development of risk projection models because of its ease of use and the broad range of models available in the program.
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From page 198... ...
1987. Life Span Study Report 11, Part 1, Comparison of risk coefficients for site specific cancer mortality based on the DW86 and T65 Dr shielded kerma and organ doses.
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From page 199... ...
Able 4D-1 describes the results of varying the RBE in relative risk models for nonleukemia cancers and leukemia. Although the slope of the dose-response curve decreased with increasing RBE, the fit of the model (as judged by the column "Deviance")
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From page 200... ...
Hence it was decided to restrict all further analyses to the subgroup under 4 Gy. Model Selection While the BEIR III report used both additive and relative risk models, this committee prefers relative risk models.
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From page 201... ...
In BEIR III, however, the excess risk functions for the additive and relative risk models were either constant or approximately constant and as such, there needed to be a definite distinction between additive risk and relative risk. It is clear from the present analyses that such simple additive or relative risk models do not provide an adequate description of the data.
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From page 203... ...
Confidence limits do not vary as much with age at exposure for nonleukemia mortality (Table 4D-4~. Nevertheless, the risks for nonleukemia are relatively high and imprecise for early ages at exposure, so that considerably more experience will be needed before there are sufficient data to estimate more precisely the lifetime risks for those exposed at early ages.
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From page 204... ...
204 EFFECTS OF EXPOSURE TO LOW LEVELS OFlONIZING RADIATION TABLE 4D-S Alternative Models Leukemia Model (X2 (x3 131 ~2 33 ~4 ~5 O See Equation (4.3) in Chapter 4 for the preferred leukemia model 2.087 2.206 - 1.921 - 1.791 - 0.442 - 2.030 1.809 1.975 - 2.531 - 1.728 - 0.688 1.890 2.062 - 2.345 - 1.772 - 0.592 - ~.
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From page 205... ...
4 1 f E-10 I(E < 20) = {0 if E-20 TABLE 4D-6 Alternative Models Lifetime Cancer Mortality Risk per 10,000 Person Sv Acute Dose Equivalent (106 person rem)
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From page 206... ...
1987. The effect of changes in dosimet~y on cancer mortality risk estimates in the atomic bomb survivors.
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From page 207... ...
Tables 4E-1 and 4E-2 summarize the follow-up and exposure information for the mortality and incidence cohorts used in these analyses. Background Rate Models For the LSS, and CAN-TB cohorts there were enough deaths in the zero dose group to allow the use of internal estimates of the base line rate for breast cancer mortality.
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From page 208... ...
c Mean doses are weighted by person years. Cohort Effects Under Relative Risk and Additive Risks lthe excess relative risk for the incidence of breast cancer in the LSS was estimated to be about 50% greater than that in the two U.S.
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From page 209... ...
TABLE 4E-3 BEIR V Breast Cancer Models Log Rate Parameter Estimates for the Background Models Incidence LSS Effect Estimate S.E. Estimate Constant 0.97 0.18 2.46 Log(age/50)
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From page 210... ...
20 =~ 1 6 Q in I 12 tr: LU 8 6 LL 4 G m 25 35 45 55 ATTAINED AGE (y) Age in 1945 15 years old 40 years old / Canada Japan 65 75 FIGURE 4E-2 Breast cancer mortality in the Japanese RERF Life Span and Canadian TB Studies by attained age for 15- and 40-year-old cohorts in 1945.
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From page 211... ...
The Committee's final choice was to estimate the level of risk per Gy using the pooled LSS and non-Nova Scotia CAN-TB data, but to use data on all women in both cohorts in describing temporal factors affecting the dose response. This choice was based upon an assumption that relative risks for breast cancer mortality and incidence should be roughly similar across
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From page 212... ...
Based upon these results and the fact that relative risks are less subject to bias as a result of incomplete (non-dose related) ascertainment, the Committee decided to use time-dependent relative risk models for their lifetime risk estimates for both breast cancer incidence and mortality.
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From page 213... ...
Thus, in the committee's preferred model, the age-at-exposure effect on the excess relative risk is modelled as a step function with steps at ages 20 and 40. In the case of breast cancer mortality, the highest estimated relative risks were seen among women aged 10 to 14 at exposure.
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From page 214... ...
, and because of the suggestion of an elevated risk in the incidence data, it was decided to pool the 0-9 and 10-14 age-at-exposure categories in the final model. The excess relative risk of breast cancer mortality for women over age 40 at exposure was lower than that seen for women who were between 20 and 40 years of age when exposed GO < 0.1~; in fact, the point estimate of the relative risk for this group was slightly, but not significantly, less than one.
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From page 215... ...
A log quadratic function of log t~me-since-exposure fit the data slightly better than a log-linear spline with a single inflection point knot. The Committee has chosen to use a log-quadratic model for the variation in the excess relative risk with time in its preferred risk model for breast cancer mortality.
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From page 216... ...
It should be noted that although a 5-year minimum latency was used in the development of the preferred model, no excess breast cancer risk was observed within ten years of exposure. Therefore, in the calculations of lifetime risk for various patterns of exposure presented in Chapter 4, a 10-year minimum latency was assumed in life table calculations.
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From page 217... ...
1989. Breast cancer mortality following irradiation in a cohort of Canadian tuberculosis patients.
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From page 218... ...
These include uncertainties inherent in dose estimates, in the selection of an appropriate risk model, and in the applicability of risk estimates measured in one populaton to other exposed groups. Population Ejects A Japanese population is the most important source of data for this report, and for some types of cancer the only source.
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From page 219... ...
Because sex does not appear in the final models for leukemia and "other" cancers, a residual uncertainty of 10% is assessed in the risk estimates for these cancers. Time-Related Elects It is difficult enough to determine the cancer risk over a lifetime; if one asks what is the risk at a particular time following exposure, the number of cases available for analysis becomes so small as to frustrate attempts at direct estimation of risks.
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From page 220... ...
Are the effects of repeated doses, separated in time, the same as if the entire dose had been delivered at once? Are the effects of a given total dose received at very low dose rates the same as those from the same dose at high dose rates?
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From page 221... ...
where D represents the organ dose equivalent in sievert and the X's are covariates such as age at exposure, etc., and the It's are their respective coefficients. If we denote the logarithm of the excess relative risk by ln(~)
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From page 222... ...
The magnitude of the uncertainty in the new DS86 dose estimates for A-bomb survivors is still being evaluated. Preliminary assessments indicate that bias in the risk estimates resulting from random errors in the dose estimates is about 10% when organ doses are limited to 4 Sv, as is the case here (Piety.
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From page 223... ...
Unlike the Monte Carlo generated estimates of uncertainties in lifetime risk given in Chapter 4 and Annex 4D, the uncertainties in Table 4F-1 are shown explicitly as functions of age at exposure, latency and sex when these factors are significant. This level of detail is not practical with
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From page 224... ...
In general, where data are relatively sparse, as is true for leukemia, the uncertainties are large, varying from nearly 2 to 8 for different ages and latencies. Uncertainties are usually not large for respiratory or digestive cancers or for breast cancer except for a short latency of 10 years.
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From page 225... ...
RISK;S OF CANCER ALL SITES TABLE 4F-1 Estimates of the Excess Relative Cancer Risk from O.1-Sv Acute Dose and Their Geometric Standard Deviations (GSD) due to Sampling Variation 225 Male Female Cancer Age at Time After Type Exposure Exposure GSD Risk GSD Risk 15 1.90 0.418 Breast 5 25 1.60 0.427 cancer 1 57 0.230 mortality 45 - 1.89 0.105 15 15 1.90 0.418 25 - 1.60 0.427 35 1.57 0.230 45 - - 1.89 0.105 25 15 - 1.77 0.056 25 1.54 0.057 35 - 1.60 0.031 45 1.99 0.014 35 15 1.90 ()
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From page 226... ...
The data for breast cancer incidence in Able 4F-1 shows that the excess relative risk for breast cancer in a woman aged 20 through 39, 25 years after exposure, is 0.06 per 0.1 Gy (10 reds)
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From page 227... ...
Diagnostic Examination of the Committee's Risk Models Throughout its development of analytical models of cancer risk as a function of dose and other variables, the committee used a number of diagnostic tests to examine the degree of correspondence between a given model and the data on which it is based (Be80, McKay. As noted in Chapter 4, decrements of deviance were used as a measure of the improvement in model "fit" gained by adding additional terms.
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From page 228... ...
. There is another form of residual that is quite useful to Poisson regression models of "sparse" data.
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From page 229... ...
If data are not too sparse, pokey has pointed out that Egi2 is still a useful aggregate statistic of goodness-of-fit (Fr83, Vegas. Tests of the Committee's Preferred Models When stratified by dose, age and time, the LSS data for leukemia, digestive, respiratory and the group "other cancers" are very sparse.
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From page 230... ...
230 EFFECTS OF EXPOSURE TO LOW LEVELS OF IONIZING RADIATION 2000~ By , 1 000 UJ LL 2000 1 500 By , 1000 llJ fir 11 500 o Leukemia 500 _ ~ '' I I I I I I I I I ~ I I IIF~n~ l ~ ~ ~ A~ ~0 ~ ~0 ~ ~ ~ ~so~°~,o~: FREEMAN-TUKEY RESIDUAL, gj Digestive (iystem _ ~ 1,,`.\,1~: J:~ -2.5 -2.0 -1.5 -1.0 -G.5 0.0 0.5 1.0 1.5 2.0 2 5 FREEMAN-TUKEY RESIDUAL, 9; FIGURE 4F-1 Distribution of Freeman-lUkey residuals under the committee's models for leukemia, cancers of the respiratory and digestive systems, and the group "other cancers" (stippled) compared to a normal distribution with the same mean, variance, and sample size.
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From page 231... ...
RISKS OF CANCER-ALL SITES 2000 1 500 7 1 000 500 2000 1 500 z 1 O0O G 500 o - Respiratory System n _-EM By; I\= 2`,`; ] h 2 LiF ° ~ ~ ~ ~ TO ~ L'-j;~''~[-,'1 ~ ~ ~l''l~ ~ ~ 453O ~ ooze ~0~ ~ ~0 ~ 00 ~ ~0~ ~ ~0 ~ 00~ ~0 lo' ,~' in' ~ lo' lo' lo' ,0' ,0' ,0' O O' O' O' a' a' a' a' lo' A' A' FREEMAN-TUKEY RESIDUAL, 9; Other Cancers ` 4, `1,, 0.0 0.5 ~ ., ,, ~,1 1.0 1.5 2.0 2.5 -2.5 -2.0 -1.5 -1.0 231 FREEMAN-TUKEY RESIDUAL, 9;
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From page 232... ...
232 EFFECTS OF EXPOSURE TO LOW LEVELS OF IONIZING RADIATION TABLE 4F-2 Summary of Residual Analysis for BEIR V Models Tumors d(Min)
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From page 233... ...
233 Lit V)
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From page 234... ...
= 0.865. Note also that these are rather less than are the cognate precisions of the LQ-L model of leukemia incidence described in Table V-8 of the BEIR III Report (Nancy: p~ /~ = 1 .065; 32/ ~ =1.518.
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From page 235... ...
235 Cal oo Can _' U: o o m o C~ ._ V)
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From page 236... ...
of a regression model and the precision of the parameter estimates that are adequate for models that are linear in the parameter vectors (e.g., the Poisson regression models of the BEIR III data) are only approximately valid for models that are non-linear in the parameters (e.g., the Poisson regression models of the BEIR V data)
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From page 237... ...
, 1 c i c n (Be80, Co82) of the respective parameter vectors, A, of the BEIR III L - L and LQ - L models of the BEIR III leukemia incidence data.
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From page 238... ...
1983. The analysis of rates using Poisson regression models.
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From page 239... ...
ANNEX 4G: THE BEIR IV COMMITTEE'S MODEL AND RISK ESTIMATES FOR LUNG CANCER DUE TO RADON PROGENY The BEIR IV Committee's risk model is based on analyses of the lung cancer mortality experience of four cohorts of underground miners. These analyses indicated a decline in the excess relative risk with both attained age and time since exposure.
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From page 240... ...
Three measures of risk are listed: Re/Ro, the ratio of lifetime risk relative to that of an unexposed person of the same sex and smoking status; Re, the lifetime risk of lung cancer; and the average years of life lost compared to the longevity of a nonsmoker of the same sex. The BEIR IV Committee pointed out a number of uncertainties in these risk estimates.
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From page 241... ...
References NRC88 National Research Council, Committee on the Biological Effects of Ionizing Radiations. Health Risks of Radon and Other Internally Deposited AlphaEmitters (BEIR IV)
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