The linear no-threshold (LNT) model of low dose ionizing radiation's (LDIR) role in radiogenic cancer incidence has long served as a pseudo-scientific belief arising from evidence that has never been proven, but has been contested. One source of current evidence that favors the LNT model is the Radiation Effects Research Foundation’s (RERF) Life Span Study (LSS) cohort of Japanese atomic bomb survivors. The RERF has managed the input data, model development, and data analyses for the LSS cohort for 45 years, publishing research papers and reports updating the RERF’s progress. In recent years, the RERF has attempted to identify other cancer risk factors that may have played a role in the cancer incidence of cohort survivors, and this effort has drawn attention to the fact that many earlier years of papers and reports from the RERF have never considered these risk factors, making such publications of questionable merit. This investigation examines two recent papers from the RERF that denominate how the RERF now analyzes specific cancer incidence for cohort members, how it treats lifestyle and other risk factors for various cancers that have arisen in the cohort, and how it continues to find and assert that bomb-blast LDIR remains a distinguishable source of radiogenic cancer in the cohort. The investigation observes that the cohort input data and modeling have extensive deficiencies and defects, many having been identified by RERF authors themselves, that substantially compromise the findings of these two papers, and offers concluding evidence that the LDIR radiogenic cancer model is highly implausible if not impossible. From such evidence, a final conclusion must arise that supports a threshold model for the dose–response relationship between LDIR exposure and radiogenic cancer.

The linear no-threshold (LNT) model for low-dose, radiogenic cancer has been a fixture of radiation protection and regulatory requirements for decades, but its validity has long been contested. This article finds, yet again, more questionable data and analyses purporting to support the model, this within the "gold-standard" data set for estimating radiation effects in humans. Herein is addressed a number of significant uncertainties in the Radiation Effects Research Foundation's Life Span Study (LSS) cohort of atomic bomb survivors, especially in its latest update of 2017, showing that the study's support of the LNT model is not evidence based. We find that its latest 2 analyses of solid cancer incidence ignore biology and do not support the LNT model. Additionally, we identify data inconsistencies and missing causalities in the LSS data and analyses that place reliance on uncertain, imputed data and apparently flawed modeling, further invalidating the LNT model. These observations lead to a most credible conclusion, one supporting a threshold model for the dose-response relationship between low-dose radiation exposure and radiogenic cancer in humans. Based upon these findings and those cited from others, it becomes apparent that the LNT model cannot be scientifically valid.

We are writing with regard to the paper authored by Walczak et al. entitled "Occupational exposure to radon for underground tourist routes in Poland: Doses to lung and the risk of developing lung cancer" [1].The authors of this paper evaluated the radon concentrations in 31 Polish underground tourist routes and calculated the equivalent dose to the lung.They also calculated the effective dose and the relative risk of lung cancer for the employees.The authors have reported that the relative risk of developing lung cancer for the people working in underground tourist routes was higher than for the general population.They have also reported that after 40 years of work, exposure to radon would be the cause of lung cancer in 42.3% of the cohort of all employees of the surveyed tourist routes.The authors used the Biological Effects of Ionizing Radiation (BEIR) VI Report [2] model for calculating the relative risk of developing lung cancer.This paper has some major shortcomings.The first shortcoming comes from the assumed model which does not have supporting evidence.The BEIR VI report stated that based on the analysis of available residential radon studies, it could not determine the shape of dose-response

TO THE EDITOR: In their Invited Perspective, Duncan et al. ([1][1]) continue a defense of the linear no-threshold (LNT) model for low-dose radiation (LDR) but do not respond to Siegel et al. ([2][2]) regarding important issues within the Biologic Effects of Ionizing Radiation (BEIR) VII report. This

TO THE EDITOR: Contrary to Siegel et al.'s commentary ([1][1]), we find little reason to believe that "dose optimization to minimize radiation risk for children … is misguided and detrimental." Although Siegel et al. acknowledge that ionizing radiation causes DNA double-strand breaks (DSBs)

This paper examines the birthing process of the linear no-threshold model with respect to genetic effects and carcinogenesis. This model was conceived >70 years ago but still remains a foundational element within much of the scientific thought regarding exposure to low-dose ionizing radiation. This model is used today to provide risk estimates for cancer resulting from any exposure to ionizing radiation down to zero dose, risk estimates that are only theoretical and, as yet, have never been conclusively demonstrated by empirical evidence. We are literally bathed every second of every day in low-dose radiation exposure due to natural background radiation, exposures that vary annually from a few mGy to 260 mGy, depending upon where one lives on the planet. Irrespective of the level of background exposure to a given population, no associated health effects have been documented to date anywhere in the world. In fact, people in the United States are living longer today than ever before, likely due to always improving levels of medical care, including even more radiation exposure from diagnostic medical radiation (eg, x-ray and computed tomography imaging examinations) which are well within the background dose range across the globe. Yet, the persistent use of the linear no-threshold model for risk assessment by regulators and advisory bodies continues to drive an unfounded fear of any low-dose radiation exposure, as well as excessive expenditures on putative but unneeded and wasteful safety measures.

Siegel, Jeffry A. PhD*; Sacks, Bill PhD, MD†; Pennington, Charles W. MS, MBA‡; Welsh, James S. MS, MD, FACRO§ Author Information

A debate exists within the medical community on whether the linear no-threshold model of ionizing radiation exposure accurately predicts the subsequent incidence of radiogenic cancer. In this article, we evaluate evidence refuting the linear no-threshold model and corollary efforts to reduce radiation exposure from CT and nuclear medicine imaging in accord with the as-low-as-reasonably-achievable principle, particularly for children. Further, we review studies demonstrating that children are not, in fact, more radiosensitive than adults in the radiologic imaging dose range, rendering dose reduction for children unjustifiable and counterproductive. Efforts to minimize nonexistent risks are futile and a major source of persistent radiophobia. Radiophobia is detrimental to patients and parents, induces stress, and leads to suboptimal image quality and avoidance of imaging, thus increasing misdiagnoses and consequent harm while offering no compensating benefits.

Radiologic imaging is claimed to carry an iatrogenic risk of cancer, based on an uninformed commitment to the 70-y-old linear no threshold hypothesis (LNTH). Credible evidence of imaging-related low-dose (<100 mGy) carcinogenic risk is nonexistent; it is a hypothetical risk derived from the demonstrably false LNTH. On the contrary, low-dose radiation does not cause, but more likely helps prevent, cancer. The LNTH and its offspring, ALARA (as low as reasonably achievable), are fatally flawed, focusing only on molecular damage while ignoring protective, organismal biologic responses. Although some grant the absence of low-dose harm, they nevertheless advocate the "prudence" of dose optimization (i.e., using ALARA doses); but this is a radiophobia-centered, not scientific, approach. Medical imaging studies achieve a diagnostic purpose and should be governed by the highest science-based principles and policies. The LNTH is an invalidated hypothesis, and its use, in the form of ALARA dosing, is responsible for misguided concerns promoting radiophobia, leading to actual risks far greater than the hypothetical carcinogenic risk purportedly avoided. Further, the myriad benefits of imaging are ignored. The present work calls for ending the radiophobia caused by those asserting the need for dose optimization in imaging: the low-dose radiation of medical imaging has no documented pathway to harm, whereas the LNTH and ALARA most assuredly do.

A debate within radiation protection science has been building over many years regarding whether low-dose, ionizing radiation (LDIR, in the range of 0 200 mGy) is known to be a carcinogen (1). That debate now approaches a fever pitch, and the time is ripe to assess what is known and how it is known to determine where truth must lie. A philosophy developed over centuries that applies to such an investigation, termed the philosophy of knowledge, or the philosophy of science (or scientific knowledge) as a subset (see, for example, the discussion by Wenning (2)), is useful in this debate. Within this philosophy, an ontology (and, specifically, a science ontology) may be simply defined as what we know in some particular niche or entity of science-space. But "knowing" in science requires strong foundations, and knowledge has been refined over the centuries to mean a 'justified, true belief.' Such a belief may be knowledge only under three conditions: it is certain; we believe it is true; and we have empirical justification to believe it. Stated differently, scientific knowledge arises when: we accept an objective reality; postulated rules govern that reality; and those rules may be demonstrated by empirical evidence. The empirical evidence supporting that belief or rule is called the epistemology how we know the belief or rule is true and epistemology for science must make use of reason constrained by verification through experimentation and observation. Putative facts deriving from misinformation and/or opinion can never be scientific knowledge.

Scientific achievement has a muddled, disordered topography, with landscapes that include both great pinnacles of success and deep crevices of failure. We focus on one failure that remains uncorrected: the linear no-threshold (LNT) model of radiation-induced cancer, on which governments and advisory bodies have based regulatory policy for 70 years. High-dose radiation can cause cancer, but no such correlation has ever unequivocally been shown at low doses in the range of x-ray and computed tomography (CT) examinations or in the vicinity of nuclear power plants.The proven consequence of high doses of radiation has simply been assumed to apply even at doses near zero, and no threshold has been given below which it is harmless. Consequently, all doses have been predicted to cause cancer. But as many studies prove,11. J. A. Siegel, J. S. Welsh, Technol. Cancer Res. Treat. (2015), https://doi.org/10.1177/1533034615578011.,22. A. Aurengo et al., Dose-Effect Relationships and Estimation of the Carcinogenic Effects of Low Doses of Ionizing Radiation, French Academy of Sciences and National Academy of Medicine (2005). the body responds differently to radiation at high and low doses: At low doses, the body eliminates the damage through various protective mechanisms that have evolved in humans from eons of living in a world bathed in low dose-rate but sometimes high-dose natural radiation.Based on the Japanese government’s unwarranted fear that any radiation exposure would increase cancer cases, residents were forcibly evacuated from around the Fukushima nuclear plant, a decision that according to the government’s own figures resulted in more than 1600 deaths. The Japanese Cabinet recently decided to lift evacuation orders; whether residents will actually return is uncertain due to the radiophobia instilled in them over the past four years. Reliance on the LNT model has resulted in even larger health and economic impacts at Chernobyl. All such devastating consequences of using the LNT model to form policy and standards have prompted three recent petitions to the US Nuclear Regulatory Commission to reject the flawed model, whose origin can be traced to the work of Hermann Muller and colleagues.Nobelist Muller, a founding proponent of the LNT model, investigated x-ray effects on fruit-fly gene mutations. He claimed in his 1946 Nobel lecture that the mutation rate was a linear function of dose down to zero, independent of dose rate, with no threshold below which there is no effect. Muller based his claim on his testing at doses that are actually high—at least 4000 mGy. For comparison, US natural radiation exposure averages 3 mGy annually, and a typical CT scan is 10 mGy. Thus Muller’s extrapolation of harm down to zero dose was untrue.In 1948–49, research by Muller’s colleague Curt Stern33. W. P. Spencer, C. Stern, Genetics 33, 43 (1948); E. Caspari, C. Stern, Genetics 33, 75 (1948); D. E. Uphoff, C. Stern, Science 109, 609 (1949). https://doi.org/10.1126/science.109.2842.609 found that at doses below 500 mGy, flies often had mutation rates similar to or even lower than unirradiated flies, and these mutation rate differences decreased if the dose rate was reduced. Those findings clearly suggest protective responses and a no-harm threshold somewhere below 500 mGy. Some of the results were inconsistent, but rather than continue testing, the researchers arbitrarily decided that there was no threshold and that dose rate was irrelevant; they thus reinforced Muller’s false claim.Fortunately, those researchers left a trail of published data that does confirm a threshold, contrary to their claim. Apparently, neither they nor any others noticed that result until we recently discovered it.44. J. A. Siegel et al., Am. J. Clin. Oncol. (in press), https://doi.org/10.1097/COC.0000000000000244.Muller’s and Stern’s approaches survive in the LNT model of today, which says that low-dose radiation increases cancer risk. However, while linearity—the “L” in LNT—was demonstrated only at high doses, the absence of a threshold has never been demonstrated. The only scientific conclusion from the data from 1949 through today is that the linear threshold (LT) model, not the LNT, is correct, and it has a low-dose threshold below which radiation is harmless. Even data from atomic-bomb survivors, the gold standard of dose-response data, do not support the LNT model; adaptive protections mitigate radiation-induced damage at low doses and low dose rates. No epidemiological studies have ever demonstrated a causal relationship between low-dose radiation exposure and carcinogenesis.Many people, though they admit the absence of evidence, nevertheless believe that “precautions” derived from the LNT model save lives. But misguided application of the LNT model to regulation and policy have caused death and psychological damage from unnecessary mass evacuations and have created adverse health consequences from patients’ fear-driven rejection of potentially life-saving x rays and CTs. Additionally, hundreds of billions of dollars are wasted on unnecessary precautionary measures due to unwarranted fear of low-dose radiation.Scientists have failed in the science of radiation protection. The accurate LT model must become the basis of radiation regulation. Science must finally arrive at summary judgment that the LNT model is fallacious and thereby alleviate suffering and abate needless, paralyzing public fear. The LT model’s threshold with no low-dose radiation harm can free people from the grip of groundless phobias. No harm, no fear!REFERENCESSection:ChooseTop of pageREFERENCES <

The Geocap Study described by Sermage-Faure et al. (2012) suggested to them “a possible excess risk of AL [childhood acute leukemia] in the close vicinity of French NPPs [nuclear power plants] in 2002–2007”. The abstract contains general results of two analyses: the nationwide Geocap case-control study showing the odds ratio of cancer incidence OR = 1.9 (1.0–3.3, 95% confidence interval [CI]) and a concomitant study with standardized incidence ratio (SIR) = 1.9 (1.0–3.2, 95% CI). However, we provide evidence that this hypothetical risk increase is likely a statistical fluctuation. In addition, the data are subject to confounding factors that were not addressed. The putative increase in leukemia risk therefore cannot be justifiably attributed to very small radiation doses associated with the operation of the NPPs. First, the authors have not one datum in Table 2 (Sermage-Faure et al. 2012) that shows a statistically significant increase in cancer risk, whether for children under 5 or under 15 years of age, in either the interval 1990–2001 or 2002–2007. Only by data dredging and subdividing the numbers into smaller time intervals and other discriminatory indices in Table 4 (Sermage-Faure et al. 2012), can they produce a few showing statistical significance. But then, the numbers of children included in each time interval are small. Second, the results in the abstract are based on only 14 cancer cases near 19 NPPs. Fourteen cases are too few for a clinically significant result. Fourteen cases near 19 NPPs are on average 0.7 cases per NPP. Third, neither any confounding factor nor individual history of the children (especially their migrations) was taken into consideration. These omissions and the mentioned small-sample-size-related statistical problems invalidate the claimed association of cancer risk with NPP proximity. Additional weak points of the analysis were diligently mentioned by the authors (Sermage-Faure et al. 2012). First, no correlation was found between cancer cases and radioactive releases from NPPs. Second, similar French investigations several years earlier failed to find an increase in risk (White-Koning et al. 2004; Evrard et al. 2006; Laurier et al. 2008). And the evaluation over a wider time period (1990–2007) did not show a statistically significant risk increase. Third, total accumulated doses over the time period 2002–2007 were in the range of microsieverts – several orders of magnitude lower than the variations in natural background radiation. Fourth, lower doses were received by children living up to 5 km from the NPP, where the risk was estimated to be higher, while no risk increase was found among children who received the highest doses. These four weaknesses alone should have been sufficient to invalidate any claimed association between NPP operation and cancer, without the three points raised in this Letter. One can add also that despite the authors’ reluctance to unambiguously relate the leukemia incidence to the NPP emissions, they nevertheless suggest that leukemia is a consequence of radiation exposure from NPP operation. We point out in the present Letter why this suggestion is not justified. Attribution of an excess risk of cancers to nearby NPPs is a well known practice, even though many independent studies, such as COMARE (2011), CANUPIS (Spycher et al. 2011) or RADICON (2013), have demonstrated no correlation between radiation exposures around NPPs and cancer incidence. Observed increases can be attributed to population mixing, as pointed out in the most recent extensive review of childhood leukemia around NPPs (Janiak 2014). The population mixing hypothesis considered involves “the influx of outside workers to rural regions where nuclear installations are being set up and where local people are not immune to pathogens brought along with the incomers” (Janiak 2014). The Geocap Study (Sermage-Faure et al. 2012) is one of many studies on cancer risk around NPPs. The presented conclusions implicitly blame NPP-related, low-dose-radiation exposures for increased cancer risk. The “call for investigation for potential risk factors related to the vicinity of NPP” (Sermage-Faure et al. 2012) should be seriously questioned because such studies will lack statistical power for demonstrating any change (increase or decrease) in risk. In addition, such studies can promote potentially-harmful radiophobia (Jaworowski 2010; Scott 2011; Orient 2014), thereby making it difficult to communicate accurate information to the public on the health effects of radiation exposure, especially in the event of an actual radiological emergency (Allison 2009; Sanders 2010). The previous version of this Letter was submitted to the International Journal of Cancer. In his reply, the Editor stated that our remarks would not interest the journal’s readers.

The most emotionally gripping topic of the debate over expansion of commercial nuclear power in the USA centres on the threat of radiological harm to the public from a commercial nuclear power plant accident. The perseverance of the radiation fear issue is reviewed herein, followed by summarisation of the expanded knowledge of reactor safety over the last 30 years. Analyses of maximum population radiation doses from a worst-case, credible accident at a current US reactor and from a terrorist attack on a nuclear spent fuel storage or transportation system are developed, with 50-year population doses of 1.3 million person-cSv and 5500 person-cSv, respectively, as maximum risks, if these events are modeled on the same bases as the accident outcomes at the Chernobyl Nuclear Power Plant unit 4. The study demonstrates such outcomes are significantly below what actually results from many non-nuclear industries in the USA that have existed for decades and whose radiological characteristics have not been, and likely will never be, regulated. Such information can be used for informing public and political stakeholders in the USA having safety concerns about commercial nuclear power to reduce fear and improve knowledge.

The debate over a large expansion of commercial nuclear energy for electricity production in the U.S., termed a “nuclear renaissance,” has most recently focused on the issues of spent nuclear fuel transportation and the closing of the once-through nuclear fuel cycle through the licensing, construction, and operation of the national spent nuclear fuel repository at Yucca Mountain, Nevada. While such a commercial nuclear energy expansion is postulated to have environmental, climate, resource utilization, and economic benefits, the fundamental issue for typical U.S. citizens about nuclear energy concerns the potential for exposure to ionizing radiation. Two generations of U.S. citizens have experienced public and media “education” that has heightened their primal fears of ionizing radiation from commercial nuclear energy. In such an environment, comparing the risks of radiation doses from commercial nuclear energy fuel cycle closure and further nuclear energy expansion with ionizing radiation population doses experienced year after year, decade after decade from non-nuclear (conventional) industries seems worthwhile for use in achieving stakeholder education and concurrence. The U.S. National Academy of Sciences (NAS) has recently performed its own landmark risk assessment of spent fuel transport in the U.S., demonstrating the guiding principles and methods for use in comparative risk assessments involving radiation dose considerations. Using the NAS assessment approach, this paper broadens its application to the full consideration of the risk of nuclear fuel cycle closure and renewal of the commercial nuclear energy alternative in the U.S., to evaluate the ionizing radiation dose risks of such expansion compared to those routinely accepted for non-nuclear industries by policy makers and the public. The 50-year collective dose risk from the total commercial nuclear fuel cycle, even if the U.S. triples its installed nuclear capacity, transports spent fuel to Yucca Mountain, and operates the Yucca Mountain repository as planned, is shown to be in the range of 3.1-million person-cSv; for five selected non-nuclear industries, the corresponding 50-year collective dose risk exceeds 1 billion person-cSv, a more than 300 times greater risk. A key step towards renewing the commercial nuclear energy alternative, then, is to use this knowledge for education of various stakeholder parties.

The American public knows little about radiation exposures from either the commercial nuclear fuel cycle or non-nuclear (conventional) industries. Yet, many oppose commercial nuclear energy because of fear of ionizing radiation. Exposing America to education about normal radiation received from non-nuclear industries may help mitigate public concern over commercial nuclear generation, improving acceptance of this source of electricity for an energy-challenged 21st century. Using data and models developed from a variety of reliable sources, this work offers the first comparative assessments of historic and projected population ionizing radiation doses in the U.S. from both the commercial nuclear electricity industry and several non-nuclear industries. In these assessments, it is shown that just a few non-nuclear industries have produced annual radiation doses to millions of Americans for decades that exceed what has been or likely ever will be produced by either the current or expanded use of commercial nuclear electricity. Such information may also be useful in setting acceptance criteria for beyond-design-basis events hypothesized to occur in the nuclear fuel cycle, as well as for public education. From these comparative assessments, it is concluded that current or expanded use of nuclear energy in the U.S. offers no significant threat of population doses from ionizing radiation that even approach the normal radiation doses historically experienced by the public resulting from many other industries.