Issues in Interpreting Epidemiologic Studies of Populations Exposed to Low-Dose, High-Energy Photon Radiation

A Historical Survey of Key Epidemiological Studies of Ionizing Radiation Exposure

In this article we review the history of key epidemiological studies of populations exposed to ionizing radiation. We highlight historical and recent findings regarding radiation-associated risks for incidence and mortality of cancer and non-cancer outcomes with emphasis on study design and methods of exposure assessment and dose estimation along with brief consideration of sources of bias for a few of the more important studies. We examine the findings from the epidemiological studies of the Japanese atomic bomb survivors, persons exposed to radiation for diagnostic or therapeutic purposes, those exposed to environmental sources including Chornobyl and other reactor accidents, and occupationally exposed cohorts. We also summarize results of pooled studies. These summaries are necessarily brief, but we provide references to more detailed information. We discuss possible future directions of study, to include assessment of susceptible populations, and possible new populations, data sources, study designs and methods of analysis.

A generalisation of the method of regression calibration and comparison with Bayesian and frequentist model averaging methods

For many cancer sites low-dose risks are not known and must be extrapolated from those observed in groups exposed at much higher levels of dose. Measurement error can substantially alter the dose-response shape and hence the extrapolated risk. Even in studies with direct measurement of low-dose exposures measurement error could be substantial in relation to the size of the dose estimates and thereby distort population risk estimates. Recently, there has been considerable attention paid to methods of dealing with shared errors, which are common in many datasets, and particularly important in occupational and environmental settings. In this paper we test Bayesian model averaging (BMA) and frequentist model averaging (FMA) methods, the first of these similar to the so-called Bayesian two-dimensional Monte Carlo (2DMC) method, and both fairly recently proposed, against a very newly proposed modification of the regression calibration method, the extended regression calibration (ERC) method, which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. The quasi-2DMC with BMA method performs well when a linear model is assumed, but very poorly when a linear-quadratic model is assumed, with coverage probabilities both for the linear and quadratic dose coefficients that are under 5% when the magnitude of shared Berkson error is large (50%). For the linear model the bias is generally under 10%. However, using a linear-quadratic model it produces substantially biased (by a factor of 10) estimates of both the linear and quadratic coefficients, with the linear coefficient overestimated and the quadratic coefficient underestimated. FMA performs as well as quasi-2DMC with BMA when a linear model is assumed, and generally much better with a linear-quadratic model, although the coverage probability for the quadratic coefficient is uniformly too high. However both linear and quadratic coefficients have pronounced upward bias, particularly when Berkson error is large. By comparison ERC yields coverage probabilities that are too low when shared and unshared Berkson errors are both large (50%), although otherwise it performs well, and coverage is generally better than the quasi-2DMC with BMA or FMA methods, particularly for the linear-quadratic model. The bias of the predicted relative risk at a variety of doses is generally smallest for ERC, and largest for the quasi-2DMC with BMA and FMA methods (apart from unadjusted regression), with standard regression calibration and Monte Carlo maximum likelihood exhibiting bias in predicted relative risk generally somewhat intermediate between ERC and the other two methods. In general ERC performs best in the scenarios presented, and should be the method of choice in situations where there may be substantial shared error, or suspected curvature in the dose response.

A generalisation of the method of regression calibration and comparison with Bayesian and frequentist model averaging methods

For many cancer sites low-dose risks are not known and must be extrapolated from those observed in groups exposed at much higher levels of dose. Measurement error can substantially alter the dose-response shape and hence the extrapolated risk. Recently, there has been considerable attention paid to methods of dealing with shared errors, which are particularly important in occupational and environmental settings. In this paper we test Bayesian model averaging (BMA) and frequentist model averaging (FMA) methods, the first of these similar to the so-called Bayesian two-dimensional Monte Carlo (2DMC) method, and both fairly recently proposed, against a very newly proposed modification of the regression calibration method, the extended regression calibration (ERC) method. The quasi-2DMC+BMA method performs well when a linear model is assumed, but poorly when a linear-quadratic model is assumed. FMA performs as well as quasi-2DMC+BMA when a linear model is assumed, and generally much better with a linear-quadratic model, although the coverage probability for the quadratic coefficient is uniformly too high. ERC yields coverage probabilities that are too low when shared and unshared Berkson errors are both large (50%), although otherwise it performs well, and coverage is generally better than the quasi-2DMC+BMA or FMA methods, particularly for the linear-quadratic model. The bias of predicted relative risk at a variety of doses is generally smallest for ERC, and largest for quasi-2DMC+BMA and FMA, with standard regression calibration and Monte Carlo maximum likelihood exhibiting bias in predicted relative risk generally somewhat intermediate between ERC and the other two methods. In general ERC performs best in the scenarios presented, and should be the method of choice in situations where there may be substantial shared error, or suspected curvature in the dose response.

Radiation-Related Thyroid Cancer

Radiation is an environmental factor that elevates the risk of developing thyroid cancer. Actual and possible scenarios of exposures to external and internal radiation are multiple and diverse. This article reviews radiation doses to the thyroid and corresponding cancer risks due to planned, existing, and emergency exposure situations, and medical, public, and occupational categories of exposures. Any exposure scenario may deliver a range of doses to the thyroid, and the risk for cancer is addressed along with modifying factors. The consequences of the Chornobyl and Fukushima nuclear power plant accidents are described, summarizing the information on thyroid cancer epidemiology, treatment, and prognosis, clinicopathological characteristics, and genetic alterations. The Chornobyl thyroid cancers have evolved in time: becoming less aggressive and driver shifting from fusions to point mutations. A comparison of thyroid cancers from the 2 areas reveals numerous differences that cumulatively suggest the low probability of the radiogenic nature of thyroid cancers in Fukushima. In view of continuing usage of different sources of radiation in various settings, the possible ways of reducing thyroid cancer risk from exposures are considered. For external exposures, reasonable measures are generally in line with the As Low As Reasonably Achievable principle, while for internal irradiation from radioactive iodine, thyroid blocking with stable iodine may be recommended in addition to other measures in case of anticipated exposures from a nuclear reactor accident. Finally, the perspectives of studies of radiation effects on the thyroid are discussed from the epidemiological, basic science, and clinical points of view.

A generalisation of the method of regression calibration and comparison with the Bayesian 2-dimensional Monte Carlo method

For many cancer sites it is necessary to assess risks from low-dose exposures via extrapolation from groups exposed at moderate and high levels of dose. Measurement error can substantially alter the shape of this relationship and hence the derived population risk estimates. Even in studies with direct measurement of low-dose exposures measurement error could be substantial in relation to the size of the dose estimates and thereby distort population risk estimates. Recently, much attention has been devoted to the issue of shared errors, common in many datasets, and particularly important in occupational settings. In this paper we test a Bayesian model averaging method, the so-called Bayesian two-dimensional Monte Carlo (2DMC) method, that has been fairly recently proposed against a very newly proposed modification of the regression calibration method, which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. We also compared both methods against standard regression calibration and Monte Carlo maximum likelihood. The Bayesian 2DMC method performs poorly, with coverage probabilities both for the linear and quadratic dose coefficients that are under 5%, particularly when the magnitudes of classical and Berkson error are both moderate to large (20%-50%). The method also produces substantially biased (by a factor of 10) estimates of both the linear and quadratic coefficients, with the linear coefficient overestimated and the quadratic coefficient underestimated. By comparison the extended regression calibration method yields coverage probabilities that are too low when shared and unshared Berkson errors are both large (50%), although otherwise it performs well, and coverage is generally better than the Bayesian 2DMC and all other methods. The bias of the predicted relative risk at a variety of doses is generally smallest for extended regression calibration, and largest for the Bayesian 2DMC method (apart from unadjusted regression), with standard regression calibration and Monte Carlo maximum likelihood exhibiting bias in predicted relative risk generally somewhat intermediate between the other two methods.

A generalisation of the method of regression calibration

There is direct evidence of risks at moderate and high levels of radiation dose for highly radiogenic cancers such as leukaemia and thyroid cancer. For many cancer sites, however, it is necessary to assess risks via extrapolation from groups exposed at moderate and high levels of dose, about which there are substantial uncertainties. Crucial to the resolution of this area of uncertainty is the modelling of the dose-response relationship and the importance of both systematic and random dosimetric errors for analyses in the various exposed groups. It is well recognised that measurement error can alter substantially the shape of this relationship and hence the derived population risk estimates. Particular attention has been devoted to the issue of shared errors, common in many datasets, and particularly important in occupational settings. We propose a modification of the regression calibration method which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. This method can be used in settings where there is a mixture of Berkson and classical error. In fits to synthetic datasets in which there is substantial upward curvature in the true dose response, and varying (and sometimes substantial) amounts of classical and Berkson error, we show that the coverage probabilities of all methods for the linear coefficient [Formula: see text] are near the desired level, irrespective of the magnitudes of assumed Berkson and classical error, whether shared or unshared. However, the coverage probabilities for the quadratic coefficient [Formula: see text] are generally too low for the unadjusted and regression calibration methods, particularly for larger magnitudes of the Berkson error, whether this is shared or unshared. In contrast Monte Carlo maximum likelihood yields coverage probabilities for [Formula: see text] that are uniformly too high. The extended regression calibration method yields coverage probabilities that are too low when shared and unshared Berkson errors are both large, although otherwise it performs well, and coverage is generally better than these other three methods. A notable feature is that for all methods apart from extended regression calibration the estimates of the quadratic coefficient [Formula: see text] are substantially upwardly biased.

A generalisation of the method of regression calibration

There is direct evidence of risks at moderate and high levels of radiation dose for highly radiogenic cancers such as leukaemia and thyroid cancer. For many cancer sites, however, it is necessary to assess risks via extrapolation from groups exposed at moderate and high levels of dose, about which there are substantial uncertainties. Crucial to the resolution of this area of uncertainty is the modelling of the dose-response relationship and the importance of both systematic and random dosimetric errors for analyses in the various exposed groups. It is well recognised that measurement error can alter substantially the shape of this relationship and hence the derived population risk estimates. Particular attention has been devoted to the issue of shared errors, common in many datasets, and particularly important in occupational settings. We propose a modification of the regression calibration method which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. This method can be used in settings where there is a mixture of Berkson and classical error. In fits to synthetic datasets in which there is substantial upward curvature in the true dose response, and varying (and sometimes substantial) amounts of classical and Berkson error, we show that the coverage probabilities of all methods for the linear coefficient \(\alpha\) are near the desired level, irrespective of the magnitudes of assumed Berkson and classical error, whether shared or unshared. However, the coverage probabilities for the quadratic coefficient \(\beta\) are generally too low for the unadjusted and regression calibration methods, particularly for larger magnitudes of the Berkson error, whether this is shared or unshared. In contrast Monte Carlo maximum likelihood yields coverage probabilities for \(\beta\) that are uniformly too high. The extended regression calibration method yields coverage probabilities that are too low when shared and unshared Berkson errors are both large, although otherwise it performs well, and coverage is generally better than these other three methods. A notable feature is that for all methods apart from extended regression calibration the estimates of the quadratic coefficient \(\beta\) are substantially upwardly biased.

Circulatory disease mortality among male medical radiation workers in South Korea, 1996-2019

OBJECTIVE

The aim of this study was to investigate the relationship between occupational radiation exposure and circulatory disease (CD) mortality among medical radiation workers.

METHODS

The study included 53 860 male diagnostic medical radiation workers enrolled in the National Dosimetry Registry (NDR) between 1996 and 2011 in South Korea. NDR data were linked with mortality data obtained from the national registry at the end of 2019. Observed CD mortality rates in this population were compared to those in the general population using the standardized mortality ratio (SMR). The relative risk (RR) for occupational history was estimated by use of internal comparisons, and the excess relative risk (ERR) was used to quantify the radiation dose-response relationship.

RESULTS

A total of 320 deaths due to CD were identified among 53 860 male medical radiation workers. The SMR of CD was significantly lower among male workers than the general population. A linear dose-response model provided an estimated ERR per 100 mGy for CD [0.85, 95% confidence interval (CI) -0.11-1.82], ischemic heart disease (1.18, 95% CI -0.69-3.05), and cerebrovascular disease (0.23, 95% CI -0.48-0.94) with a 10-years lag, showing no statistical evidence of a radiation dose-response relationship. Additional adjustments for non-radiation factors did not affect the findings on occupational radiation risk for CD mortality. Sensitivity analyses excluding workers employed <1 year or who had exposure to a cumulative badge dose of ≥1 mSv showed similar results.

CONCLUSIONS

Occupational radiation doses were non-significantly positively associated with CD mortality among male diagnostic medical radiation workers. However, cautious interpretation is needed due to the limitations of short follow-up.

Mortality among medical radiation workers in the United States, 1965-2016

BACKGROUND

Estimates of radiation risks following prolonged exposures at low doses and low-dose rates are uncertain. Medical radiation workers are a major component of the Million Person Study (MPS) of low-dose health effects. Annual personal dose equivalents, H_P(10), for individual workers are available to facilitate dose-response analyses for lung cancer, leukemia, ischemic heart disease (IHD) and other causes of death.

MATERIALS AND METHODS

The Landauer, Inc. dosimetry database identified 109,019 medical and associated radiation workers first monitored 1965-1994. Vital status and cause of death were determined through 2016. Mean absorbed doses to red bone marrow (RBM), lung, heart, and other organs were estimated by adjusting the recorded H_P(10) for each worker by scaling factors, accounting for exposure geometry, the energy of the incident photon radiation, sex of the worker and whether an apron was worn. There were 4 exposure scenarios: general radiology characterized by low-energy x-ray exposure with no lead apron use, interventional radiologists/cardiologists who wore aprons, nuclear medicine personnel and radiation oncologists exposed to high-energy photon radiation, and other workers. Standardized mortality ratio (SMR) analyses were performed. Cox proportional hazards models were used to estimate organ-specific radiation risks.

RESULTS

Overall, 11,433 deaths occurred (SMR 0.60; 95%CI 0.59,0.61), 126 from leukemia other than chronic lymphocytic leukemia (CLL), 850 from lung cancer, and 1654 from IHD. The mean duration of monitoring was 23.7 y. The excess relative rate (ERR) per 100 mGy was estimated as 0.10 (95% CI -0.34, 0.54) for leukemia other than CLL, 0.15 (0.02, 0.27) for lung cancer, and -0.10 (-0.27, 0.06) for IHD. The ERR for lung cancer was 0.16 (0.01, 0.32) among the 55,218 male workers and 0.09 (-0.19, 0.36) among the 53,801 female workers; a difference that was not statistically significant (p-value = 0.23).

CONCLUSIONS

Medical radiation workers were at increased risk for lung cancer that was higher among men than women, although this difference was not statistically significant. In contrast, the study of Japanese atomic bomb survivors exposed briefly to radiation in 1945 found females to be nearly 3 times the radiation risk of lung cancer compared with males on a relative scale. For medical workers, there were no statistically significant radiation associations with leukemia excluding CLL, IHD or other specific causes of death. Combining these data with other cohorts within the MPS, such as nuclear power plant workers and nuclear submariners, will enable more precise estimates of radiation risks at relatively low cumulative doses.

Cancer risks among studies of medical diagnostic radiation exposure in early life without quantitative estimates of dose

BACKGROUND

There is accumulating evidence of excess risk of cancer in various populations exposed at acute doses below several tens of mSv or doses received over a protracted period. There is also evidence that relative risks are generally higher after radiation exposures in utero or in childhood.

METHODS AND FINDINGS

We reviewed and summarised evidence from 89 studies of cancer following medical diagnostic exposure in utero or in childhood, in which no direct estimates of radiation dose are available. In all of the populations studied exposure was to sparsely ionizing radiation (X-rays). Several of the early studies of in utero exposure exhibit modest but statistically significant excess risks of several types of childhood cancer. There is a highly significant (p < 0.0005) negative trend of odds ratio with calendar period of study, so that more recent studies tend to exhibit reduced excess risk. There is no significant inter-study heterogeneity (p > 0.3). In relation to postnatal exposure there are significant excess risks of leukaemia, brain and solid cancers, with indications of variations in risk by cancer type (p = 0.07) and type of exposure (p = 0.02), with fluoroscopy and computed tomography scans associated with the highest excess risk. However, there is highly significant inter-study heterogeneity (p < 0.01) for all cancer endpoints and all but one type of exposure, although no significant risk trend with calendar period of study.

CONCLUSIONS

Overall, this large body of data relating to medical diagnostic radiation exposure in utero provides support for an associated excess risk of childhood cancer. However, the pronounced heterogeneity in studies of postnatal diagnostic exposure, the implied uncertainty as to the meaning of summary measures, and the distinct possibilities of bias, substantially reduce the strength of the evidence from the associations we observe between radiation imaging in childhood and the subsequent risk of cancer being causally related to radiation exposure.

Causes of cardiovascular and noncardiovascular death in the ISCHEMIA trial

BACKGROUND

The International Study of Comparative Health Effectiveness with Medical and Invasive Approaches trial demonstrated no overall difference in the composite primary endpoint and the secondary endpoints of cardiovascular (CV) death/myocardial infarction or all-cause mortality between an initial invasive or conservative strategy among participants with chronic coronary disease and moderate or severe myocardial ischemia. Detailed cause-specific death analyses have not been reported.

METHODS

We compared overall and cause-specific death rates by treatment group using Cox models with adjustment for pre-specified baseline covariates. Cause of death was adjudicated by an independent Clinical Events Committee as CV, non-CV, and undetermined. We evaluated the association of risk factors and treatment strategy with cause of death.

RESULTS

Four-year cumulative incidence rates for CV death were similar between invasive and conservative strategies (2.6% vs 3.0%; hazard ratio [HR] 0.98; 95% CI [0.70-1.38]), but non-CV death rates were higher in the invasive strategy (3.3% vs 2.1%; HR 1.45 [1.00-2.09]). Overall, 13% of deaths were attributed to undetermined causes (38/289). Fewer undetermined deaths (0.6% vs 1.3%; HR 0.48 [0.24-0.95]) and more malignancy deaths (2.0% vs 0.8%; HR 2.11 [1.23-3.60]) occurred in the invasive strategy than in the conservative strategy.

CONCLUSIONS

In International Study of Comparative Health Effectiveness with Medical and Invasive Approaches, all-cause and CV death rates were similar between treatment strategies. The observation of fewer undetermined deaths and more malignancy deaths in the invasive strategy remains unexplained. These findings should be interpreted with caution in the context of prior studies and the overall trial results.

Age effects on radiation response: summary of a recent symposium and future perspectives

One of the principal uncertainties when estimating population risk of late effects from epidemiological data is that few radiation-exposed cohorts have been followed up to extinction. Therefore, the relative risk model has often been used to estimate radiation-associated risk and to extrapolate risk to the end of life. Epidemiological studies provide evidence that children are generally at higher risk of cancer induction than adults for a given radiation dose. However, the strength of evidence varies by cancer site and questions remain about site-specific age at exposure patterns. For solid cancers, there is a large body of evidence that excess relative risk (ERR) diminishes with increasing age at exposure. This pattern of risk is observed in the Life Span Study (LSS) as well as in other radiation-exposed populations for overall solid cancer incidence and mortality and for most site-specific solid cancers. However, there are some disparities by endpoint in the degree of variation of ERR with exposure age, with some sites (e.g., colon, lung) in the LSS incidence data showing no variation, or even increasing ERR with increasing age at exposure. The pattern of variation of excess absolute risk (EAR) with age at exposure is often similar, with EAR for solid cancers or solid cancer mortality decreasing with increasing age at exposure in the LSS. We shall review the human data from the Japanese LSS cohort, and a variety of other epidemiological data sets, including a review of types of medical diagnostic exposures, also some radiobiological animal data, all bearing on the issue of variations of radiation late-effects risk with age at exposure and with attained age. The paper includes a summary of several oral presentations given in a Symposium on "Age effects on radiation response" as part of the 67th Annual Meeting of the Radiation Research Society, held virtually on 3-6 October 2021.

Comparison of All Solid Cancer Mortality and Incidence Dose-Response in the Life Span Study of Atomic Bomb Survivors, 1958-2009

Recent analysis of all solid cancer incidence (1958-2009) in the Life Span Study (LSS) revealed evidence of upward curvature in the radiation dose response among males but not females. Upward curvature in sex-averaged excess relative risk (ERR) for all solid cancer mortality (1950-2003) was also observed in the 0-2 Gy dose range. As reasons for non-linearity in the LSS are not completely understood, we conducted dose-response analyses for all solid cancer mortality and incidence applying similar methods [1958-2009 follow-up, DS02R1 doses, including subjects not-in-city (NIC) at the time of the bombing] and statistical models. Incident cancers were ascertained from Hiroshima and Nagasaki cancer registries, while cause of death was ascertained from death certificates throughout Japan. The study included 105,444 LSS subjects who were alive and not known to have cancer before January 1, 1958 (80,205 with dose estimates and 25,239 NIC subjects). Between 1958 and 2009, there were 3.1 million person-years (PY) and 22,538 solid cancers for incidence analysis and 3.8 million PY and 15,419 solid cancer deaths for mortality analysis. We fitted sex-specific ERR models adjusted for smoking to both types of data. Over the entire range of doses, solid cancer mortality dose-response exhibited a borderline significant upward curvature among males (P = 0.062) and significant upward curvature among females (P = 0.010); for solid cancer incidence, as before, we found a significant upward curvature among males (P = 0.001) but not among females (P = 0.624). The sex difference in magnitude of dose-response curvature was statistically significant for cancer incidence (P = 0.017) but not for cancer mortality (P = 0.781). The results of analyses in the 0-2 Gy range and restricted lower dose ranges generally supported inferences made about the sex-specific dose-response shape over the entire range of doses for each outcome. Patterns of sex-specific curvature by calendar period (1958-1987 vs. 1988-2009) and age at exposure (0-19 vs. 20-83) varied between mortality and incidence data, particularly among females, although for each outcome there was an indication of curvature among 0-19-year-old male survivors in both calendar periods and among 0-19-year-old female survivors in the recent period. Collectively, our findings indicate that the upward curvature in all solid cancer dose response in the LSS is neither specific to males nor to incidence data; its evidence appears to depend on the composition of sites comprising all solid cancer group and age at exposure or time. Further follow up and site-specific analyses of cancer mortality and incidence will be important to confirm the emerging trend in dose-response curvature among young survivors and unveil the contributing factors and sites.

Review of the risk of cancer following low and moderate doses of sparsely ionising radiation received in early life in groups with individually estimated doses

BACKGROUND

The detrimental health effects associated with the receipt of moderate (0.1-1 Gy) and high (>1 Gy) acute doses of sparsely ionising radiation are well established from human epidemiological studies. There is accumulating direct evidence of excess risk of cancer in a number of populations exposed at lower acute doses or doses received over a protracted period. There is evidence that relative risks are generally higher after radiation exposures in utero or in childhood.

METHODS AND FINDINGS

We reviewed and summarised evidence from 60 studies of cancer or benign neoplasms following low- or moderate-level exposure in utero or in childhood from medical and environmental sources. In most of the populations studied the exposure was predominantly to sparsely ionising radiation, such as X-rays and gamma-rays. There were significant (p < 0.001) excess risks for all cancers, and particularly large excess relative risks were observed for brain/CNS tumours, thyroid cancer (including nodules) and leukaemia.

CONCLUSIONS

Overall, the totality of this large body of data relating to in utero and childhood exposure provides support for the existence of excess cancer and benign neoplasm risk associated with radiation doses < 0.1 Gy, and for certain groups exposed to natural background radiation, to fallout and medical X-rays in utero, at about 0.02 Gy.

Impact of Reverse Causation on Estimates of Cancer Risk Associated With Radiation Exposure From Computerized Tomography: A Simulation Study Modeled on Brain Cancer

Use of computed tomography (CT) scanning has increased substantially since its introduction in the 1990s. Several authors have reported increased risk of leukemia and brain tumors associated with radiation exposure from CT scans. However, reverse causation is a concern, particularly for brain cancer; in other words, the CT scan may have been taken because of preexisting cancer and therefore not have been a cause. We assessed the possibility of reverse causation via a simulation study focused on brain tumors, using a simplified version of the data structure for recent CT studies. Five-year-lagged and unlagged analyses implied an observed excess risk per scan up to 70% lower than the true excess risk per scan, particularly when more than 10% of persons with latent cancer had increased numbers of scans or the extra scanning rate after development of latent cancer was greater than 2 scans/year; less extreme values of these parameters imply little risk attenuation. Without a lag and when more than 20% of persons with latent cancer had increased scans-an arguably implausible scenario-the excess risk per scan was increased over the true excess risk per scan by up to 35%-40%. This study suggests that with a realistic lag, reverse causation results in downwardly biased risk, a result of induced classical measurement error, and is therefore unlikely to produce a spurious positive association between cancer and radiation dose from CT scans.

Cancer risk following low doses of ionising radiation - Current epidemiological evidence and implications for radiological protection

Recent studies suggest that every year worldwide about a million patients might be exposed to doses of the order of 100 mGy of low-LET radiation, due to recurrent application of radioimaging procedures. This paper presents a synthesis of recent epidemiological evidence on radiation-related cancer risks from low-LET radiation doses of this magnitude. Evidence from pooled analyses and meta-analyses also involving epidemiological studies that, individually, do not find statistically significant radiation-related cancer risks is reviewed, and evidence from additional and more recent epidemiological studies of radiation exposures indicating excess cancer risks is also summarized. Cohorts discussed in the present paper include Japanese atomic bomb survivors, nuclear workers, patients exposed for medical purposes, and populations exposed environmentally to natural background radiation or radioactive contamination. Taken together, the overall evidence summarized here is based on studies including several million individuals, many of them followed-up for more than half a century. In summary, substantial evidence was found from epidemiological studies of exposed groups of humans that ionizing radiation causes cancer at acute and protracted doses above 100 mGy, and growing evidence for doses below 100 mGy. The significant radiation-related solid cancer risks observed at doses of several 100 mGy of protracted exposures (observed, for example, among nuclear workers) demonstrate that doses accumulated over many years at low dose rates do cause stochastic health effects. On this basis, it can be concluded that doses of the order of 100 mGy from recurrent application of medical imaging procedures involving ionizing radiation are of concern, from the viewpoint of radiological protection.

Mortality from Leukemia, Cancer and Heart Disease among U.S. Nuclear Power Plant Workers, 1957-2011

BACKGROUND

The aim of the Million Person Study (MPS) of Low Dose Health Effects is to examine the level of radiation risk for chronic exposures received gradually over time and not acutely as was the case for the Japanese atomic bomb survivors. Nuclear power plant (NPP) workers comprise nearly 15 percent of the MPS. Leukemia, selected cancers, Parkinson's disease, ischemic heart disease (IHD) and other causes of death are evaluated.

METHODS AND MATERIAL

The U.S. Nuclear Regulatory Commission's Radiation Exposure Information and Reporting System (REIRS) and the Landauer, Inc. dosimetry databases identified 135,193 NPP workers first monitored 1957-1984. Annual personal dose equivalents [Hp(10)] were available for each worker. Radiation records from all places of employment were sought. Vital status was determined through 2011. Mean absorbed doses to red bone marrow (RBM), esophagus, lung, colon, brain and heart were estimated by adjusting the recorded Hp(10) for each worker by scaling factors, accounting for exposure geometry and energy of the incident gamma radiation. Standardized mortality ratios (SMR) were calculated. Radiation risks were estimated using Cox proportional hazards models.

RESULTS

Nearly 50% of workers were employed for more than 20 years. The mean duration of follow-up was 30.2 y. Overall, 29,076 total deaths occurred, 296 from leukemia other than chronic lymphocytic leukemia (CLL), 3,382 from lung cancer, 140 from Parkinson's disease and 5,410 from IHD. The mean dose to RBM was 37.9 mGy (maximum 1.0 Gy; percent >100 mGy was 9.2%), 43.2 mGy to lung, 43.7 mGy to colon, 33.2 mGy to brain, and 43.9 mGy to heart. The SMRs (95% CI) were 1.06 (0.94;1.19) for leukemia other than CLL, 1.10 (1.07;1.14) for lung cancer, 0.90 (0.76;1.06) for Parkinson's disease, and 0.80 (0.78; 0.82) for IHD. The excess relative risk (ERR) per 100 mGy for leukemia other than CLL was 0.15 (90% CI 0.001; 0.31). For all solid cancers the ERR per 100 mGy (95% CI) was 0.01 (-0.03; 0.05), for lung cancer -0.04 (-0.11; 0.02), for Parkinson's disease 0.24 (-0.02; 0.50), and for IHD -0.01 (-0.06; 0.04).

CONCLUSION

Prolonged exposure to radiation increased the risk of leukemia other than CLL among NPP workers. There was little evidence for a radiation-association for all solid cancers, lung cancer or ischemic heart disease. Increased precision will be forthcoming as the different cohorts within the MPS are combined, such as industrial radiographers and medical radiation workers who were assembled and evaluated in like manner.

Epidemiological studies of CT scans and cancer risk: the state of the science

20 years ago, 3 manuscripts describing doses and potential cancer risks from CT scans in children raised awareness of a growing public health problem. We reviewed the epidemiological studies that were initiated in response to these concerns that assessed cancer risks from CT scans using medical record linkage. We evaluated the study methodology and findings and provide recommendations for optimal study design for new efforts. We identified 17 eligible studies; 13 with published risk estimates, and 4 in progress. There was wide variability in the study methodology, however, which made comparison of findings challenging. Key differences included whether the study focused on childhood or adulthood exposure, radiosensitive outcomes (e.g. leukemia, brain tumors) or all cancers, the exposure metrics (e.g. organ doses, effective dose or number of CTs) and control for biases (e.g. latency and exclusion periods and confounding by indication). We were able to compare results for the subset of studies that evaluated leukemia or brain tumors. There were eight studies of leukemia risk in relation to red bone marrow (RBM) dose, effective dose or number of CTs; seven reported a positive dose-response, which was statistically significant (p < 0.05) in four studies. Six of the seven studies of brain tumors also found a positive dose-response and in five, this was statistically significant. Mean RBM dose ranged from 6 to 12 mGy and mean brain dose from 18 to 43 mGy. In a meta-analysis of the studies of childhood exposure the summary ERR/100 mGy was 1.78 (95%CI: 0.01-3.53) for leukemia/myelodisplastic syndrome (n = 5 studies) and 0.80 (95%CI: 0.48-1.12) for brain tumors (n = 4 studies) (p-heterogeneity >0.4). Confounding by cancer pre-disposing conditions was unlikely in these five studies of leukemia. The summary risk estimate for brain tumors could be over estimated, however, due to reverse causation. In conclusion, there is growing evidence from epidemiological data that CT scans can cause cancer. The absolute risks to individual patients are, however, likely to be small. Ongoing large multicenter cohorts and future pooling efforts will provide more precise risk quantification.

Quantitative Bias Analysis of the Association between Occupational Radiation Exposure and Ischemic Heart Disease Mortality in UK Nuclear Workers

The scientific question of whether protracted low-dose or low-dose-rate exposure to external radiation is causally related to the risk of circulatory disease continues to be an important issue for radiation protection. Previous analyses of a matched case-control dataset nested in a large cohort of UK nuclear fuel cycle workers indicated that there was little evidence that observed associations between external radiation dose and ischemic heart disease (IHD) mortality risk [OR = 1.35 (95% CI: 0.99-184) for 15-year-lagged exposure] could alternatively be explained by confounding from pre-employment tobacco smoking, BMI or blood pressure, or from socioeconomic status or occupational exposure to excessive noise or shiftwork. To improve causal inference about the observed external radiation dose and IHD mortality association, we estimated the potential magnitude and direction of non-random errors, incorporated sensitivity analyses and simulated bias effects under plausible scenarios. We conducted quantitative bias analyses of plausible scenarios based on 1,000 Monte Carlo samples to explore the impact of exposure measurement error, missing information on tobacco smoking, and unmeasured confounding, and assessed whether observed associations were reliant on the inclusion of specific matched pairs using bootstrapping with 10% of matched pairs randomly excluded in 1,000 samples. We further explored the plausibility that having been monitored for internal exposure, which was an important confounding factor in the case-control analysis for which models were adjusted, was indeed a confounding factor or whether it might have been the result of some form of selection bias. Consistent with the broader epidemiological evidence-base, these analyses provide further evidence that the dose-response association between cumulative external radiation exposure and IHD mortality is non-linear in that it has a linear shape plateauing at an excess risk of 43% (95% CI: 7-92%) on reaching 390 mSv. Analyses of plausible scenarios of patterns of missing data for tobacco smoking at start of employment indicated that this resulted in relatively little bias towards the null in the original analysis. An unmeasured confounder would have had to have been highly correlated (rp > 0.60) with cumulative external radiation dose to importantly bias observed associations. The confounding effect of "having been monitored for internal dose" was unlikely to have been a true confounder in a biological sense, but instead may have been some unknown factor related to differences over time and between sites in selection criteria for internal monitoring, possibly resulting in collider bias. Plausible patterns of exposure measurement error negatively biased associations regardless of the modeled scenario, but did not importantly change the shape of the observed dose-response associations. These analyses provide additional support for the hypothesis that the observed association between external radiation exposure and IHD mortality may be causal.

Low- and moderate-dose non-cancer effects of ionizing radiation in directly exposed individuals, especially circulatory and ocular diseases: a review of the epidemiology

PURPOSE

There are well-known correlations between high and moderate doses (>0.5 Gy) of ionizing radiation exposure and circulatory system damage, also between radiation and posterior subcapsular cataract. At lower dose correlations with circulatory disease are emerging in the Japanese atomic bomb survivors and in some occupationally exposed groups, and are still to some extent controversial. Heterogeneity in excess relative risks per unit dose in epidemiological studies at low (<0.1 Gy) and at low-moderate (>0.1 Gy, <0.5 Gy) doses may result from confounding and other types of bias, and effect modification by established risk factors. There is also accumulating evidence of excess cataract risks at lower dose and low dose rate in various cohorts. Other ocular endpoints, specifically glaucoma and macular degeneration have been little studied. In this paper, we review recent epidemiological findings, and also discuss some of the underlying radiobiology of these conditions. We briefly review some other types of mainly neurological nonmalignant disease in relation to radiation exposure.

CONCLUSIONS

We document statistically significant excess risk of the major types of circulatory disease, specifically ischemic heart disease and stroke, in moderate- or low-dose exposed groups, with some not altogether consistent evidence suggesting dose-response non-linearity, particularly for stroke. However, the patterns of risk reported are not straightforward. We also document evidence of excess risks at lower doses/dose-rates of posterior subcapsular and cortical cataract in the Chernobyl liquidators, US Radiologic Technologists and Russian Mayak nuclear workers, with fundamentally linear dose-response. Nuclear cataracts are less radiogenic. For other ocular endpoints, specifically glaucoma and macular degeneration there is very little evidence of effects at low doses; radiation-associated glaucoma has been documented only for doses >5 Gy, and so has the characteristics of a tissue reaction. There is some evidence of neurological detriment following low-moderate dose (∼0.1-0.2 Gy) radiation exposure in utero or in early childhood.

A review of studies of childhood cancer and natural background radiation

PURPOSE

The projected existence and magnitude of carcinogenic effects of ionizing radiation at low doses and low-dose rates is perhaps the most important issue in radiation protection today. Studies of childhood cancer and natural background radiation have the potential to throw direct light on this question, into a dose range below a few tens of mSv. This paper describes the studies that have been undertaken and their context, discusses some problems that arise and summarizes the present position.

CONCLUSIONS

Many such studies have been undertaken, but most were too small to have a realistic chance of detecting the small effects expected from such low doses, based on risk projections from higher exposures. Case-control or cohort studies are to be preferred methodologically to ecological studies but can be prone to problems of registration/participation bias. Interview-based studies of the requisite size would be prohibitively expensive and would undoubtedly also run into problems of participation bias. Register-based studies can be very large and are free of participation bias. However, they need to estimate the radiation exposure of study subjects using models rather than individual measurements in the homes of those concerned. At present, no firm conclusions can be drawn from the studies that have been published to date. Further data and perhaps pooled studies offer a way forward.

Risk of Bias Assessments and Evidence Syntheses for Observational Epidemiologic Studies of Environmental and Occupational Exposures: Strengths and Limitations

BACKGROUND

Increasingly, risk of bias tools are used to evaluate epidemiologic studies as part of evidence synthesis (evidence integration), often involving meta-analyses. Some of these tools consider hypothetical randomized controlled trials (RCTs) as gold standards.

METHODS

We review the strengths and limitations of risk of bias assessments, in particular, for reviews of observational studies of environmental exposures, and we also comment more generally on methods of evidence synthesis.

RESULTS

Although RCTs may provide a useful starting point to think about bias, they do not provide a gold standard for environmental studies. Observational studies should not be considered inherently biased vs. a hypothetical RCT. Rather than a checklist approach when evaluating individual studies using risk of bias tools, we call for identifying and quantifying possible biases, their direction, and their impacts on parameter estimates. As is recognized in many guidelines, evidence synthesis requires a broader approach than simply evaluating risk of bias in individual studies followed by synthesis of studies judged unbiased, or with studies given more weight if judged less biased. It should include the use of classical considerations for judging causality in human studies, as well as triangulation and integration of animal and mechanistic data.

CONCLUSIONS

Bias assessments are important in evidence synthesis, but we argue they can and should be improved to address the concerns we raise here. Simplistic, mechanical approaches to risk of bias assessments, which may particularly occur when these tools are used by nonexperts, can result in erroneous conclusions and sometimes may be used to dismiss important evidence. Evidence synthesis requires a broad approach that goes beyond assessing bias in individual human studies and then including a narrow range of human studies judged to be unbiased in evidence synthesis. https://doi.org/10.1289/EHP6980.

Epidemiological Studies of Low-Dose Ionizing Radiation and Cancer: Summary Bias Assessment and Meta-Analysis

BACKGROUND

Ionizing radiation is an established carcinogen, but risks from low-dose exposures are controversial. Since the Biological Effects of Ionizing Radiation VII review of the epidemiological data in 2006, many subsequent publications have reported excess cancer risks from low-dose exposures. Our aim was to systematically review these studies to assess the magnitude of the risk and whether the positive findings could be explained by biases.

METHODS

Eligible studies had mean cumulative doses of less than 100 mGy, individualized dose estimates, risk estimates, and confidence intervals (CI) for the dose-response and were published in 2006-2017. We summarized the evidence for bias (dose error, confounding, outcome ascertainment) and its likely direction for each study. We tested whether the median excess relative risk (ERR) per unit dose equals zero and assessed the impact of excluding positive studies with potential bias away from the null. We performed a meta-analysis to quantify the ERR and assess consistency across studies for all solid cancers and leukemia.

RESULTS

Of the 26 eligible studies, 8 concerned environmental, 4 medical, and 14 occupational exposure. For solid cancers, 16 of 22 studies reported positive ERRs per unit dose, and we rejected the hypothesis that the median ERR equals zero (P = .03). After exclusion of 4 positive studies with potential positive bias, 12 of 18 studies reported positive ERRs per unit dose (P  = .12). For leukemia, 17 of 20 studies were positive, and we rejected the hypothesis that the median ERR per unit dose equals zero (P  = .001), also after exclusion of 5 positive studies with potential positive bias (P  = .02). For adulthood exposure, the meta-ERR at 100 mGy was 0.029 (95% CI = 0.011 to 0.047) for solid cancers and 0.16 (95% CI = 0.07 to 0.25) for leukemia. For childhood exposure, the meta-ERR at 100 mGy for leukemia was 2.84 (95% CI = 0.37 to 5.32); there were only two eligible studies of all solid cancers.

CONCLUSIONS

Our systematic assessments in this monograph showed that these new epidemiological studies are characterized by several limitations, but only a few positive studies were potentially biased away from the null. After exclusion of these studies, the majority of studies still reported positive risk estimates. We therefore conclude that these new epidemiological studies directly support excess cancer risks from low-dose ionizing radiation. Furthermore, the magnitude of the cancer risks from these low-dose radiation exposures was statistically compatible with the radiation dose-related cancer risks of the atomic bomb survivors.

Strengths and Weaknesses of Dosimetry Used in Studies of Low-Dose Radiation Exposure and Cancer

BACKGROUND

A monograph systematically evaluating recent evidence on the dose-response relationship between low-dose ionizing radiation exposure and cancer risk required a critical appraisal of dosimetry methods in 26 potentially informative studies.

METHODS

The relevant literature included studies published in 2006-2017. Studies comprised case-control and cohort designs examining populations predominantly exposed to sparsely ionizing radiation, mostly from external sources, resulting in average doses of no more than 100 mGy. At least two dosimetrists reviewed each study and appraised the strengths and weaknesses of the dosimetry systems used, including assessment of sources and effects of dose estimation error. An overarching concern was whether dose error might cause the spurious appearance of a dose-response where none was present.

RESULTS

The review included 8 environmental, 4 medical, and 14 occupational studies that varied in properties relative to evaluation criteria. Treatment of dose estimation error also varied among studies, although few conducted a comprehensive evaluation. Six studies appeared to have known or suspected biases in dose estimates. The potential for these biases to cause a spurious dose-response association was constrained to three case-control studies that relied extensively on information gathered in interviews conducted after case ascertainment.

CONCLUSIONS

The potential for spurious dose-response associations from dose information appeared limited to case-control studies vulnerable to recall errors that may be differential by case status. Otherwise, risk estimates appeared reasonably free of a substantial bias from dose estimation error. Future studies would benefit from a comprehensive evaluation of dose estimation errors, including methods accounting for their potential effects on dose-response associations.

Outcome Assessment in Epidemiological Studies of Low-Dose Radiation Exposure and Cancer Risks: Sources, Level of Ascertainment, and Misclassification

BACKGROUND

Outcome assessment problems and errors that could lead to biased risk estimates in low-dose radiation epidemiological studies of cancer risks have not been systematically evaluated.

METHODS

Incidence or mortality risks for all cancers or all solid cancers combined and for leukemia were examined in 26 studies published in 2006-2017 involving low-dose (mean dose ≤100 mGy) radiation from environmental, medical, or occupational sources. We evaluated the impact of loss to follow-up, under- or overascertainment, outcome misclassification, and changing classifications occurring similarly or differentially across radiation dose levels.

RESULTS

Loss to follow-up was not reported in 62% of studies, but when reported it was generally small. Only one study critically evaluated the completeness of the sources of vital status. Underascertainment of cancers ("false negatives") was a potential shortcoming for cohorts that could not be linked with high-quality population-based registries, particularly during early years of exposure in five studies, in two lacking complete residential history, and in one with substantial emigration. False positives may have occurred as a result of cancer ascertainment from self- or next-of-kin report in three studies or from enhanced medical surveillance of exposed patients that could lead to detection bias (eg, reporting precancer lesions as physician-diagnosed cancer) in one study. Most pediatric but few adult leukemia studies used expert hematopathology review or current classifications. Only a few studies recoded solid cancers to the latest International Classification of Diseases or International Classification of Diseases for Oncology codes. These outcome assessment shortcomings were generally nondifferential in relation to radiation exposure level except possibly in four studies.

CONCLUSION

The majority of studies lacked information to enable comprehensive evaluation of all major sources of outcome assessment errors, although reported data suggested that the outcome assessment limitations generally had little effect on risk or biased estimates towards the null except possibly in four studies.

Evaluation of Confounding and Selection Bias in Epidemiological Studies of Populations Exposed to Low-Dose, High-Energy Photon Radiation

BACKGROUND

Low-dose, penetrating photon radiation exposure is ubiquitous, yet our understanding of cancer risk at low doses and dose rates derives mainly from high-dose studies. Although a large number of low-dose cancer studies have been recently published, concern exists about the potential for confounding to distort findings. The aim of this study was to describe and assess the likely impact of confounding and selection bias within the context of a systematic review.

METHODS

We summarized confounding control methods for 26 studies published from 2006 to 2017 by exposure setting (environmental, medical, or occupational) and identified confounders of potential concern. We used information from these and related studies to assess evidence for confounding and selection bias. For factors in which direct or indirect evidence of confounding was lacking for certain studies, we used a theoretical adjustment to determine whether uncontrolled confounding was likely to have affected the results.

RESULTS

For medical studies of childhood cancers, confounding by indication (CBI) was the main concern. Lifestyle-related factors were of primary concern for environmental and medical studies of adult cancers and for occupational studies. For occupational studies, other workplace exposures and healthy worker survivor bias were additionally of interest. For most of these factors, however, review of the direct and indirect evidence suggested that confounding was minimal. One study showed evidence of selection bias, and three occupational studies did not adjust for lifestyle or healthy worker survivor bias correlates. Theoretical adjustment for three factors (smoking and asbestos in occupational studies and CBI in childhood cancer studies) demonstrated that these were unlikely to explain positive study findings due to the rarity of exposure (eg, CBI) or the relatively weak association with the outcome (eg, smoking or asbestos and all cancers).

CONCLUSION

Confounding and selection bias are unlikely to explain the findings from most low-dose radiation epidemiology studies.

Epidemiological Studies of Low-Dose Ionizing Radiation and Cancer: Rationale and Framework for the Monograph and Overview of Eligible Studies

Whether low-dose ionizing radiation can cause cancer is a critical and long-debated question in radiation protection. Since the Biological Effects of Ionizing Radiation report by the National Academies in 2006, new publications from large, well-powered epidemiological studies of low doses have reported positive dose-response relationships. It has been suggested, however, that biases could explain these findings. We conducted a systematic review of epidemiological studies with mean doses less than 100 mGy published 2006-2017. We required individualized doses and dose-response estimates with confidence intervals. We identified 26 eligible studies (eight environmental, four medical, and 14 occupational), including 91 000 solid cancers and 13 000 leukemias. Mean doses ranged from 0.1 to 82 mGy. The excess relative risk at 100 mGy was positive for 16 of 22 solid cancer studies and 17 of 20 leukemia studies. The aim of this monograph was to systematically review the potential biases in these studies (including dose uncertainty, confounding, and outcome misclassification) and to assess whether the subset of minimally biased studies provides evidence for cancer risks from low-dose radiation. Here, we describe the framework for the systematic bias review and provide an overview of the eligible studies.