Jay H. Lubin

Cancer risks attributable to low doses of ionizing radiation: Assessing what we really know

High doses of ionizing radiation clearly produce deleterious consequences in humans, including, but not exclusively, cancer induction. At very low radiation doses the situation is much less clear, but the risks of low-dose radiation are of societal importance in relation to issues as varied as screening tests for cancer, the future of nuclear power, occupational radiation exposure, frequent-flyer risks, manned space exploration, and radiological terrorism. We review the difficulties involved in quantifying the risks of low-dose radiation and address two specific questions. First, what is the lowest dose of x- or γ-radiation for which good evidence exists of increased cancer risks in humans? The epidemiological data suggest that it is ≈10–50 mSv for an acute exposure and ≈50–100 mSv for a protracted exposure. Second, what is the most appropriate way to extrapolate such cancer risk estimates to still lower doses? Given that it is supported by experimentally grounded, quantifiable, biophysical arguments, a linear extrapolation of cancer risks from intermediate to very low doses currently appears to be the most appropriate methodology. This linearity assumption is not necessarily the most conservative approach, and it is likely that it will result in an underestimate of some radiation-induced cancer risks and an overestimate of others.

Thyroid Cancer after Exposure to External Radiation: A Pooled Analysis of Seven Studies

The thyroid gland of children is especially vulnerable to the carcinogenic action of ionizing radiation. To provide insights into various modifying influences on risk, seven major studies with organ doses to individual subjects were evaluated. Five cohort studies (atomic bomb survivors, children treated for tinea capitis, two studies of children irradiated for enlarged tonsils, and infants irradiated for an enlarged thymus gland) and two case-control studies (patients with cervical cancer and childhood cancer) were studied. The combined studies include almost 120,000 people (approximately 58,000 exposed to a wide range of doses and 61,000 nonexposed subjects), nearly 700 thyroid cancers and 3,000,000 person years of follow-up. For persons exposed to radiation before age 15 years, linearity best described the dose response, even down to 0.10 Gy. At the highest doses (> 10 Gy), associated with cancer therapy, there appeared to be a decrease or leveling of risk. For childhood exposures, the pooled excess relative risk per Gy (ERR/Gy) was 7.7 (95% CI = 2.1, 28.7) and the excess absolute risk per 10(4) PY Gy (EAR/10(4) PY Gy) was 4.4 (95% CI = 1.9, 10.1). The attributable risk percent (AR%) at 1 Gy was 88%. However, these summary estimates were affected strongly by age at exposure even within this limited age range. The ERR was greater (P = 0.07) for females than males, but the findings from the individual studies were not consistent. The EAR was higher among women, reflecting their higher rate of naturally occurring thyroid cancer. The distribution of ERR over time followed neither a simple multiplicative nor an additive pattern in relation to background occurrence. Only two cases were seen within 5 years of exposure. The ERR began to decline about 30 years after exposure but was still elevated at 40 years. Risk also decreased significantly with increasing age at exposure, with little risk apparent after age 20 years. Based on limited data, there was a suggestion that spreading dose over time (from a few days to > 1 year) may lower risk, possibly due to the opportunity for cellular repair mechanisms to operate. The thyroid gland in children has one of the highest risk coefficients of any organ and is the only tissue with convincing evidence for risk about 1.10 Gy.

Epidemiologic Evaluation of Measurement Data in the Presence of Detection Limits

Quantitative measurements of environmental factors greatly improve the quality of epidemiologic studies but can pose challenges because of the presence of upper or lower detection limits or interfering compounds, which do not allow for precise measured values. We consider the regression of an environmental measurement (dependent variable) on several covariates (independent variables). Various strategies are commonly employed to impute values for interval-measured data, including assignment of one-half the detection limit to nondetected values or of “fill-in” values randomly selected from an appropriate distribution. On the basis of a limited simulation study, we found that the former approach can be biased unless the percentage of measurements below detection limits is small (5–10%). The fill-in approach generally produces unbiased parameter estimates but may produce biased variance estimates and thereby distort inference when 30% or more of the data are below detection limits. Truncated data methods (e.g., Tobit regression) and multiple imputation offer two unbiased approaches for analyzing measurement data with detection limits. If interest resides solely on regression parameters, then Tobit regression can be used. If individualized values for measurements below detection limits are needed for additional analysis, such as relative risk regression or graphical display, then multiple imputation produces unbiased estimates and nominal confidence intervals unless the proportion of missing data is extreme. We illustrate various approaches using measurements of pesticide residues in carpet dust in control subjects from a case–control study of non-Hodgkin lymphoma.

Residential radon and risk of lung cancer : A combined analysis of 7 north american case-control studies

Background: Underground miners exposed to high levels of radon have an excess risk of lung cancer. Residential exposure to radon is at much lower levels, and the risk of lung cancer with residential exposure is less clear. We conducted a systematic analysis of pooled data from all North American residential radon studies. Methods: The pooling project included original data from 7 North American case–control studies, all of which used long-term α-track detectors to assess residential radon concentrations. A total of 3662 cases and 4966 controls were retained for the analysis. We used conditional likelihood regression to estimate the excess risk of lung cancer. Results: Odds ratios (ORs) for lung cancer increased with residential radon concentration. The estimated OR after exposure to radon at a concentration of 100 Bq/m3 in the exposure time window 5 to 30 years before the index date was 1.11 (95% confidence interval = 1.00–1.28). This estimate is compatible with the estimate of 1.12 (1.02–1.25) predicted by downward extrapolation of the miner data. There was no evidence of heterogeneity of radon effects across studies. There was no apparent heterogeneity in the association by sex, educational level, type of respondent (proxy or self), or cigarette smoking, although there was some evidence of a decreasing radon-associated lung cancer risk with age. Analyses restricted to subsets of the data with presumed more accurate radon dosimetry resulted in increased estimates of risk. Conclusions: These results provide direct evidence of an association between residential radon and lung cancer risk, a finding predicted using miner data and consistent with results from animal and in vitro studies.

Biased selection of controls for case-control analyses of cohort studies.

It is known that unbiased estimates of the relative risk in a cohort study may be obtained by a matched case-control analysis that compares each case with a random sample of controls obtained from those at risk at the time of case incidence. Through inadvertence , or for practical or scientific reasons, a biased referent group may be selected instead. Three kinds of biasing restrictions on controls are commonly imposed: (i) the requirement that controls remain completely disease-free for a fixed time interval, (ii) the exclusion of all cases incident during observation as controls, and (iii) the exclusion, from the referent group, of subjects who develop other diseases, which may be related to the exposure of interest. The bias in estimation of the relative risk associated with each of these restrictions is evaluated under the proportional-hazards model. For several examples of cancer mortality data, the bias from (iii) appears quite small, whereas the bias from (i) can be appreciable and is mostly attributable to the bias from case exclusion (ii). The effect of random variation in the time of onset of exposure is to reduce these biases.

Drinking Water Source and Chlorination Byproducts I. Risk of Bladder Cancer

We conducted a population-based case-control study of bladder cancer in Iowa in 1986–1989 to evaluate the risk posed by tapwater containing chlorination byproducts. We combined information about residential history, drinking water source, beverage intake, and other factors with historical data from water utilities and measured contaminant levels to create indices of past exposure to chlorination byproducts. The study comprised 1,123 cases and 1,983 controls who had data relating to at least 70% of their lifetime drinking water source. After we adjusted for potential confounders, we calculated odds ratios for duration of chlorinated surface water of 1.0 (referent), 1.0, 1.1, 1.2, and 1.5 for 0, 1–19, 20–39, 40–59, and ≥60 years of use. We also found associations with total and average lifetime byproduct intake, as represented by trihalomethane estimates. Positive findings were restricted to men and to ever-smokers. Among men, odds ratios were 1.0 (referent), 1.1, 1.3, 1.5, and 1.9, and among ever-smokers, 1.0, 1.1, 1.3, 1.8, and 2.2, after adjustment for intensity and timing of smoking. Among nonsmoking men and women, regardless of smoking habit, there was no association. Among men, smoking and exposure to chlorinated surface water mutually enhanced the risk of bladder cancer. The overall association of bladder cancer risk with duration of chlorinated surface water use that we found is consistent with the findings of other investigations, but the differences in risk between men and women, and between smokers and nonsmokers, have not been widely observed.

Obesity and cancer risk among white and black United States veterans

Background: Obesity has been linked to excess risk for many cancers, but the evidence remains tenuous for some types. Although the prevalence of obesity varies by race, few studies of obesity-related cancer risk have included non-white subjects. Methods: In a large cohort of male US veterans (3,668,486 whites; 832,214 blacks) hospitalized with a diagnosis of obesity between 1969 and 1996, we examined risk for all major cancer sites and subsites. Person-years accrued from the date of first obesity diagnosis until the occurrence of a first cancer, death, or the end of the observation period (September 30, 1996). We calculated age- and calendar-year adjusted relative risks (RR) and 95% confidence intervals (CI) for cancer among white and black veterans, comparing obese men to men hospitalized for other reasons, with obesity status as time-dependent. For selected cancers, we performed additional analyses stratified by specific medical conditions related to both obesity and risk of those cancers. To determine whether obesity-related cancer risks differed significantly between white and black men, we evaluated heterogeneity of risk for each cancer site. Results: Among white veterans, risk was significantly elevated for several cancers, including cancers of the lower esophagus, gastric cardia, small intestine, colon, rectum, gallbladder and ampulla of vater, male breast, prostate, bladder, thyroid, and connective tissue, and for malignant melanoma, multiple myeloma, chronic lymphocytic leukemia (CLL), and acute myeloid leukemia (AML). Excess risks initially observed for cancers of the liver and pancreas persisted among men without a history of diabetes or alcoholism. Among black veterans, risks were significantly elevated for cancers of the colon, extrahepatic bile ducts, prostate, thyroid, and for malignant melanoma, multiple myeloma, CLL and AML. Conclusions: Obese men are at increased risk for several major cancers as well as a number of uncommon malignancies, a pattern generally similar for white and black men. Due to the increasing prevalence of obesity and overweight worldwide, it is important to clarify the impact of excess body weight on cancer and to elucidate the mechanisms involved.

A Combined Analysis of North American Case-Control Studies of Residential Radon and Lung Cancer

Cohort studies have consistently shown underground miners exposed to high levels of radon to be at excess risk of lung cancer, and extrapolations based on those results indicate that residential radon may be responsible for nearly 10–15% of all lung cancer deaths per year in the United States. However, case-control studies of residential radon and lung cancer have provided ambiguous evidence of radon lung cancer risks. Regardless, alpha-particle emissions from the short-lived radioactive radon decay products can damage cellular DNA. The possibility that a demonstrated lung carcinogen may be present in large numbers of homes raises a serious public health concern. Thus, a systematic analysis of pooled data from all North American residential radon studies was undertaken to provide a more direct characterization of the public health risk posed by prolonged radon exposure. To evaluate the risk associated with prolonged residential radon exposure, a combined analysis of the primary data from seven large scale case-control studies of residential radon and lung cancer risk was conducted. The combined data set included a total of 4081 cases and 5281 controls, representing the largest aggregation of data on residential radon and lung cancer conducted to date. Residential radon concentrations were determined primarily by α-track detectors placed in the living areas of homes of the study subjects in order to obtain an integrated 1-yr average radon concentration in indoor air. Conditional likelihood regression was used to estimate the excess risk of lung cancer due to residential radon exposure, with adjustment for attained age, sex, study, smoking factors, residential mobility, and completeness of radon measurements. Although the main analyses were based on the combined data set as a whole, we also considered subsets of the data considered to have more accurate radon dosimetry. This included a subset of the data involving 3662 cases and 4966 controls with α-track radon measurements within the exposure time window (ETW) 5–30 yr prior to the index date considered previously by Krewski et al. (2005). Additional restrictions focused on subjects for which a greater proportion of the ETW was covered by measured rather than imputed radon concentrations, and on subjects who occupied at most two residences. The estimated odds ratio (OR) of lung cancer generally increased with radon concentration. The OR trend was consistent with linearity (p = .10), and the excess OR (EOR) was 0.10 per Bq/m3 with 95% confidence limits (−0.01, 0.26). For the subset of the data considered previously by Krewski et al. (2005), the EOR was 0.11 (0.00, 0.28). Further limiting subjects based on our criteria (residential stability and completeness of radon monitoring) expected to improve radon dosimetry led to increased estimates of the EOR. For example, for subjects who had resided in only one or two houses in the 5–30 ETW and who had α-track radon measurements for at least 20 yr of this 25-yr period, the EOR was 0.18 (0.02, 0.43) per 100 Bq/m3. Both estimates are compatible with the EOR of 0.12 (0.02, 0.25) per 100 Bq/m3 predicted by downward extrapolation of the miner data. Collectively, these results provide direct evidence of an association between residential radon and lung cancer risk, a finding predicted by extrapolation of results from occupational studies of radon-exposed underground miners. E. G. Létourneau and J. B. Schoenberg have retired; J. A. Stolwijk holds an emeritus position. We acknowledge the helpful input of the following individuals who served on the International Steering Committee for the North American combined analysis: Ken Chadwick (CEC Radiation Protection Program), Susan Conrath (U.S. Environmental Protection Agency), Sarah Darby (Oxford University), Evan Douple (U.S. National Academy of Sciences), Colin Muirhead (UK National Radiation Protection Board), and Susan Rose (U.S. Department of Energy). Salary support for Drs. Field, Lynch, and Steck was provided in part by grant numbers R01 ES05653 and P30 ES05605 from the National Institute of Environmental Health Sciences, NIH and grant number R01 CA85942 from the National Cancer Institute, NIH. This research was supported by grants from the Canadian Institutes of Health Research (formerly the Medical Research Council of Canada) and the Natural Sciences and Engineering Research Council of Canada to D. Krewski, who currently holds the NSERC/SSHRC/McLaughlin Chair in Population Health Risk Assessment at the University of Ottawa. Financial support for the meetings of the Analysis Team and the Steering Committee was also provided by Health Canada and the U.S. Department of Energy. We are grateful to Dr. Huixia Jiang for assistance with the combined analysis, and to Jackie Monaghan for technical assistance in preparing this report.

The Diesel Exhaust in Miners Study: A Nested Case–Control Study of Lung Cancer and Diesel Exhaust

Background Most studies of the association between diesel exhaust exposure and lung cancer suggest a modest, but consistent, increased risk. However, to our knowledge, no study to date has had quantitative data on historical diesel exposure coupled with adequate sample size to evaluate the exposure–response relationship between diesel exhaust and lung cancer. Our purpose was to evaluate the relationship between quantitative estimates of exposure to diesel exhaust and lung cancer mortality after adjustment for smoking and other potential confounders. Methods We conducted a nested case–control study in a cohort of 12 315 workers in eight non-metal mining facilities, which included 198 lung cancer deaths and 562 incidence density–sampled control subjects. For each case subject, we selected up to four control subjects, individually matched on mining facility, sex, race/ethnicity, and birth year (within 5 years), from all workers who were alive before the day the case subject died. We estimated diesel exhaust exposure, represented by respirable elemental carbon (REC), by job and year, for each subject, based on an extensive retrospective exposure assessment at each mining facility. We conducted both categorical and continuous regression analyses adjusted for cigarette smoking and other potential confounding variables (eg, history of employment in high-risk occupations for lung cancer and a history of respiratory disease) to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Analyses were both unlagged and lagged to exclude recent exposure such as that occurring in the 15 years directly before the date of death (case subjects)/reference date (control subjects). All statistical tests were two-sided. Results We observed statistically significant increasing trends in lung cancer risk with increasing cumulative REC and average REC intensity. Cumulative REC, lagged 15 years, yielded a statistically significant positive gradient in lung cancer risk overall (P trend = .001); among heavily exposed workers (ie, above the median of the top quartile [REC ≥ 1005 μg/m3-y]), risk was approximately three times greater (OR = 3.20, 95% CI = 1.33 to 7.69) than that among workers in the lowest quartile of exposure. Among never smokers, odd ratios were 1.0, 1.47 (95% CI = 0.29 to 7.50), and 7.30 (95% CI = 1.46 to 36.57) for workers with 15-year lagged cumulative REC tertiles of less than 8, 8 to less than 304, and 304 μg/m3-y or more, respectively. We also observed an interaction between smoking and 15-year lagged cumulative REC (P interaction = .086) such that the effect of each of these exposures was attenuated in the presence of high levels of the other. Conclusion Our findings provide further evidence that diesel exhaust exposure may cause lung cancer in humans and may represent a potential public health burden.

RE: “DOES NONDIFFERENTIAL MISCLASSIFICATION OF EXPOSURE ALWAYS BIAS A TRUE EFFECT TOWARD THE NULL VALUE?”

The authors present some examples to demonstrate that in certain nondifferential misclassification conditions with polychotomous exposure variables, estimates of odds ratios for categories at intermediate level of risk can be biased away from the null or can change direction. In addition, the authors present two examples to demonstrate that the slope of the dose-response trend for the true distributions can change direction, creating a false inverse trend, even if the misclassification is nondifferential.