Jerome S. Puskin

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.

EPA's perspective on risks from residential radon exposure

Indoor radon has been judged to be the most serious environmental carcinogen which the EPA must address for the general public. The optimal strategy for dealing with this problem depends on the magnitude of the risk, how the risk is distributed within the population, as well as the effectiveness and costs of mitigation measures. Based on current exposure and risk estimates, radon exposure in single-family houses may be a causal factor in roughly 20,000 lung cancer fatalities per year. Most of these projected fatalities are attributable to exposures in houses with average or moderately elevated radon levels (below 10 pCi/L). Hence to appreciably reduce radon-induced lung cancers, remediation efforts must include houses not highly elevated in radon. From either an individual risk or a cost-benefit standpoint, reduction of a few pCi/L per home appears to be justified. The optimal strategy for dealing with the indoor radon problem depends on the magnitude of the risk per unit exposure, the distribution of exposures in houses, and the effectiveness and costs of mitigation. EPAs current views with respect to these factors and the associated uncertainties are discussed.

PERSPECTIVE ON THE USE OF LNT FOR RADIATION PROTECTION AND RISK ASSESSMENT BY THE U.S. ENVIRONMENTAL PROTECTION AGENCY

The U.S. Environmental Protection Agency (EPA) bases its risk assessments, regulatory limits, and nonregulatory guidelines for population exposures to low level ionizing radiation on the linear no-threshold (LNT) hypothesis, which assumes that the risk of cancer due to a low dose exposure is proportional to dose, with no threshold. The use of LNT for radiation protection purposes has been repeatedly endorsed by authoritative scientific advisory bodies, including the National Academy of Sciences’ BEIR Committees, whose recommendations form a primary basis of EPAs risk assessment methodology. Although recent radiobiological findings indicate novel damage and repair processes at low doses, LNT is supported by data from both epidemiology and radiobiology. Given the current state of the science, the consensus positions of key scientific and governmental bodies, as well as the conservatism and calculational convenience of the LNT assumption, it is unlikely that EPA will modify this approach in the near future.

Radon Exposure Assessment and Dosimetry Applied to Epidemiology and Risk Estimation

Abstract Puskin, J. S. and James, A. C. Radon Exposure Assessment and Dosimetry Applied to Epidemiology and Risk Estimation. Radiat. Res. 166, 193–208 (2006). Epidemiological studies of underground miners provide the primary basis for radon risk estimates for indoor exposures as well as mine exposures. A major source of uncertainty in these risk estimates is the uncertainty in radon progeny exposure estimates for the miners. Often the exposure information is very incomplete, and exposure estimation must rely on interpolations, extrapolations and reconstruction of mining conditions decades before, which might differ markedly from those in more recent times. Many of the measurements that were carried out—commonly for health protection purposes—are not likely to be representative of actual exposures. Early monitoring was often of radon gas rather than of the progeny, so that quantifying exposure requires an estimate of the equilibrium fraction under the conditions existing at the time of the reported measurement. In addition to the uncertainty in radon progeny exposure, doses from γ radiation, inhaled radioactive dust, and thoron progeny have historically been neglected. These may induce a systematic bias in risk estimates and add to the overall uncertainty in risk estimates derived from the miner studies. Unlike other radiogenic cancer risk estimates, numerical risk estimates derived for radon from epidemiology are usually expressed as a risk per unit exposure rather than as a risk per unit dose to a target tissue. Nevertheless, dosimetric considerations are important when trying to compare risks under different exposure conditions, e.g. in mines and homes. A recent comparative assessment of exposure conditions indicates that, for equal radon progeny exposures, the dose in homes is about the same as in mines. Thus, neglecting other possible differences, such as the presence in mines of other potential airborne carcinogens, the risk per unit progeny exposure should be about the same for indoor exposures as observed in miners. Results of case–control studies of lung cancer incidence in homes monitored for radon are reasonably consistent with what would be projected from miner studies. Measurements of exposure in these indoor case–control studies rely on different types of detectors than those used in mines, and the estimates of exposure are again a major source of uncertainty in these studies.

Low Dose Radiation Epidemiology: What Can It Tell Us?

A small workshop entitled ‘‘Low Dose Radiation Epidemiology—What Can it Tell Us?’’ was held at the North Bethesda Marriott Hotel, December 10–11, 2008. The workshop was organized and funded by the Department of Energy’s Low Dose Radiation Research Program, and the Organizing Committee consisted of a member each from DOE, EPA and NCI, plus one member from an academic institution. Participants were chosen for their acknowledged expertise and included 29 epidemiologists, four dosimetrists, and five radiation biologists. The impetus for holding the workshop was the following: There is some suggestion from research in cellular and animal systems that the biological response may differ after highand low-dose/dose-rate radiation exposure. There is no consensus, however, as to whether these differences would result in higher or lower risks of cancer or other diseases than would be predicted from the linear extrapolation defined by current epidemiological data. The workshop participants discussed the value of current human epidemiological data at lower doses and the possibilities for improving and expanding lowdose data obtained from epidemiological studies. On the first day, the selected existing epidemiological studies of low-dose/low-dose-rate exposed populations were reviewed.

Lack of Correlation between Stem-Cell Proliferation and Radiation- or Smoking-Associated Cancer Risk

Background A recent paper by Tomasetti and Vogelstein (Science 2015 347 78–81) suggested that the variation in natural cancer risk was largely explained by the total number of stem-cell divisions, and that most cancers arose by chance. They proposed an extra-risk score as way of distinguishing the effects of the stochastic, replicative component of cancer risk from other causative factors, specifically those due to the external environment and inherited mutations. Objectives We tested the hypothesis raised by Tomasetti and Vogelstein by assessing the degree of correlation of stem cell divisions and their extra-risk score with radiation- and tobacco-associated cancer risk. Methods We fitted a variety of linear and log-linear models to data on stem cell divisions per year and cumulative stem cell divisions over lifetime and natural cancer risk, some taken from the paper of Tomasetti and Vogelstein, augmented using current US lifetime cancer risk data, and also radiation- and tobacco-associated cancer risk. Results The data assembled by Tomasetti and Vogelstein, as augmented here, are inconsistent with the power-of-age relationship commonly observed for cancer incidence and the predictions of a multistage carcinogenesis model, if one makes the strong assumption of homogeneity of numbers of driver mutations across cancer sites. Analysis of the extra-risk score and various other measures (number of stem cell divisions per year, cumulative number of stem cell divisions over life) considered by Tomasetti and Vogelstein suggests that these are poorly predictive of currently available estimates of radiation- or smoking-associated cancer risk–for only one out of 37 measures or logarithmic transformations thereof is there a statistically significant correlation (p<0.05) with radiation- or smoking-associated risk. Conclusions The data used by Tomasetti and Vogelstein are in conflict with predictions of a multistage model of carcinogenesis, under the assumption of homogeneity of numbers of driver mutations across most cancer sites. Their hypothesis that if the extra-risk score for a tissue type is high then one would expect that environmental factors would play a relatively more important role in that cancer’s risk is in conflict with the lack of correlation between the extra-risk score and other stem-cell proliferation indices and radiation- or smoking-related cancer risk.

LETTER TO THE EDITOR: REPLY TO COHEN’S RESPONSE TO EPA POSITION ON CANCER RISK FROM LOW LEVEL RADIATION

The scientific basis for LNT has been repeatedly reviewed and supported by expert panels (BEIR, UNSCEAR, NCRP, ICRP, etc.). It rests on two main findings: (1) the epidemiological evidence on the Japanese atomic bomb survivors that there is an excess risk from low-LET radiation down to doses of about 0.1 Gy, with no dramatic deviation from linearity over the dose range from about 0.1 to 2 Gy; (2) a wide consensus that even a single track of ionizing radiation can produce clustered damage in DNA that may lead to a somatic mutation, which provides a plausible mechanism for a linear, no-threshold dose response for cancer induction at low doses. The panels have also concluded that, although anomalies may be found in some systems, the experimental data on carcinogenesis in animals are generally consistent with LNT so long as a DDREF adjustment is made in extrapolating from acute doses of greater than about 0.5–1 Gy to lower doses or to low dose rates. My paper referred to several observed biological processes, which could conceivably modulate the dose response significantly at (low-LET) doses below 0.1 Gy (Puskin 2009), and Cohen (2010) cites others. However, so far, there has been little evidence that these processes act to preclude cancer induction by low dose ionizing radiation or even to reduce it significantly. Were this the case, a reduction in risk would be expected if the dose is delivered in multiple fractions or at low dose rates, but so far the epidemiological data on cohorts receiving multiple diagnostic exposures or chronic occupational or environmental exposures does not bear out this prediction (Puskin 2009). Cohen refers to the microarray work by Yin et al. (2003), which showed a different pattern of activated genes at 0.1 Gy than at 2 Gy. But, as noted above, there is no strong indication of nonlinearity in the dose response for human carcinogenesis over this range, suggesting that the microarray results do not correlate well with proclivity for radiogenic cancer induction. Moreover, we already have evidence for risk at 0.1 Gy; the question is what happens at still lower doses, and here the microarray experiments are not at all informative. Likewise it has not been shown that the reports on immune system effects cited by Cohen have any bearing on risks from low dose chronic exposures. My focus was on low-LET radiation because there is considerably less controversy over the linearity of the dose response for high-LET radiation—aside perhaps for the special case of bone cancer induction by bone-seeking alpha-emitters such as 226Ra. Nevertheless, Cohen’s comments on bone cancer induced by internally deposited radium and on lung cancer due to radon exposure in homes should not stand unchallenged. While it is true that the dose response for bone cancer induction in radium dial painters appears to be sublinear, and that no osteosarcomas have been observed among subjects receiving less than 10 Gy, this does not prove that there is a (practical) threshold, nor, in any case, does such a finding appear to be generalizable to other types of cancer. In particular, a positive association between indoor radon levels and lung cancer have been observed in case-control studies where the dose rate to presumptive target cells was about 2 orders of magnitude lower than in the bone cancer studies. The apparent increase in latency with decreasing dose rate mentioned by Cohen is likely to be a statistical artifact relating to the high probability of tumor formation at very high dose rates employed (Guess & Hoel 1977, Peto 1978). Rowland has concluded, moreover, that a “practical threshold” relating to an increased latency with decreasing dose rate was inconsistent with the dial painter data (Rowland 1994, p. 83). Cohen continues to maintain that his observed negative correlation between lung cancer rates and average radon levels in U.S. counties implies that environmental radon poses little or no risk. A reexamination of that data has shown the negative correlation was likely due to confounding by smoking (Puskin 2003). There is also wide agreement that the residential case-control studies are a more reliable indicator than Cohen’s ecological approach and that those studies demonstrate a risk from relatively low concentrations of indoor radon (Heath et al. 2004, WHO 2009).

Adjustments to the Baseline Lung Cancer Mortality for Radon-Induced Lung Cancers in the BEIR VI Risk Models

where r0 is the baseline lung cancer mortality rate at age a in the population, b is the excess relative risk coefficient, which may be dependent on age and other parameters, z, such as smoking status, and w* is an effective exposure [e.g., in the BEIR VI Committee’s preferred models, w* is a sum of exposures weighted by a function of time since exposure and by a function of either exposure rate or exposure duration, and b is the product of a constant times age-specific and smoking-category correction coefficients (1)]. Suppressing the dependence on age and other variables for simplicity, the ‘‘excess risk’’ attributable to radon is then

Biological effectiveness of photons and electrons as a function of energy

*Division of Cancer Epidemiology and Genetics, National Canc Institute, Bethesda, MD 20892‐7238; †Texas AM ‡S International, Menlo Park, CA 94025‐3493; §Medical Research Cou cil, Harwell OX11 0RD, United Kingdom; **Center for Risk a Economic Analysis of Terrorism Events, University of Southe California, Los Angeles, CA 90089‐2902; ††Oak Ridge Center f Risk Analysis, Oak Ridge, TN 37830‐7739; ‡‡U.S. Environmen Protection Agency, Washington, DC 20460‐0001; §§Department Epidemiology, School of Public Health, University of North Carolin Chapel Hill, NC 27599‐7435; ***Clarksburg, MD 20871-436 †††Department of Biological Sciences, Wayne State Universi Detroit, MI 48202‐3917; ‡‡‡Department of Radiology, Medici School, Complutense University, Madrid, Spain. The authors declare no conflicts of interest. For correspondence contact: Steven L. Simon, Division of Canc Epidemiology and Genetics, National Cancer Institute, Bethesda, M 20892‐7238, or email at ssimon@mail.nih.gov. (Manuscript accepted 22 October 2012) 0017-9078/15/0 Copyright