Linear non-threshold dose relationship

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1 Linear non-threshold dose relationship Basis for understanding high doses The origins of understanding the effects of radiation began with ignorance, which led to what we today would classify as huge doses of radiation. These proved to have certain and dire consequences. We can say that in the regime of very large doses, the results of increasing the dose are increasing consequences. That is, for large doses, we can say with assurance that Consequences Dose. The doses elicit a response in all cases, and they appear quickly (often fatally). Health physicists characterize these situations as deterministic. Any subtlety is overwhelmed by the hugeness of the assault. This impelled those who could see the consequences to put into effect methods for decreasing the risk to individuals of these large doses, mostly through avoidance to the extent possible, and shielding to the extent possible. As we know, thick lead walls can shield against even radiation. Tolerance doses (doses to people who were exposed to radiation through their jobs or medical procedures) were set to be low enough that the acute effects were not observed as more information was gained. Basis for ignorance low doses Even after these measures had been taken, effects in people exposed to smaller amounts of radioactivity began to be observed. (163) For example, many cases of leukemia were observed among those who had tested medical uses of radioactivity.

2 Energy, Ch. 20 extension 9 Linear non-threshold dose relationship 2 For lower doses, the problem is much bigger. Is there a cutoff, below which there is no effect of radiation that is, is there a threshold? Does increasing the dose, say doubling it, cause the effect to be doubled? Clearly, neither of these can be ferreted out from the high dose regime. But the question is very important to try to answer. The effect of low doses is termed stochastic. This means that it is the result of random effects. At high doses, there is enough radiation so we can be certain that cells are hit multiple times by radiation, and certain that there must be damage. An individual particle may or may not hit a cell. If it does, does it cause ionization followed by immediate recombination (basically a return to the status quo ante)? Two methods of examining the effects of low doses were pursued historically top down, examining the effects of radiation on living things and trying to find out mechanisms of action (radiobiology), and bottom up, examining large populations and using statistics to tease out effects as they are worked out through their actions (epidemiology). (163) Examples of the former approach are exposing laboratory animals to radioactivity and seeing what happens, or studies of the effects of radiation on individual cells. Examples of the latter are the followup studies on the survivors of the nuclear bombing of Japan at the end of World War II. Both contribute to understanding. Top down The problem of discussing the effect of a radiation dose is similar to that of determining if some chemical compound, say saccharin, is carcinogenic. Investigators could feed doses of saccharin to rats and observe the resulting number of cancers. However, there would probably be some cancers even if no rat had ingested saccharin. The investigator would then have to find the difference in the numbers of cancers between two identical groups

3 Energy, Ch. 20 extension 9 Linear non-threshold dose relationship 3 one fed saccharin, one not. If we suppose that the risk of cancer is relatively low (for example, one in a million per year per rat), then for a sample size of 2,000 rats one would have to wait 1,000 years to see a difference of 1 in the number of cancers. Unfortunately for the test results, most rats will have died of other causes before the end of this time. The investigator could use 2 million rats, and then at the end of the year see a difference of 1 cancer. But, rats have cancer at some rate say, 1 in 10,000. Then there would be 100 natural cancers, and 101 in the group treated with saccharin, which is within the statistical error of 10 in this example. It is clear that the investigator has caused a boom in the rat-supply market. Not much else is clear. If the investigator could feed (and not feed) a reasonable number of rats a very large amount of saccharin, an effect would probably be quite noticeable. If the investigator knew how low doses of saccharin are related to high doses of saccharin, something will have been learned. What the investigator does for saccharin dose is to assume a linear dose theory for dose-response. By this is meant that a dose one-tenth as large as that given would produce one-tenth as many cancers, or a dose 10 times larger would cause 10 times as many cancers. (164) It was just such a procedure that led to the Food and Drug Administration s (FDA s) proposed ban on saccharin as a probable carcinogen. The linear-dose theory specifically rules out the presence of thresholds, below which there is no significant effect, because of cell repair or some other mechanism. There is some evidence for thresholds, (17,18,165) but there is no proof either way. About half the chemicals tested in this way can cause cancer (at some dose). (166) There are problems with using mice and rats. Toxicity and carcinogenicity vary among species, as well as by the method of administration of the chemical. (165) Cancer rates should be greater in humans than in mice, say, because humans have so many more cells and thus more places for things to go wrong. Old mice should have much lower rates of

4 Energy, Ch. 20 extension 9 Linear non-threshold dose relationship 4 cancer than old humans; this is not found, which suggests that mice are thirty thousand to a billion times more susceptible than humans. (165) Additionally, there are mouse cancers of organs that do not exist for human beings, (167) which complicates study interpretations. Furthermore, to get the largest effect possible, the researcher gives the animal as large a dose as it can tolerate without being poisoned. Some question the efficacy of animal models altogether. (168) The investigator who concentrates on the effects of nuclear doses, and who faces similar problems, adopts an approach identical to the approach discussed for exposure to chemicals. That is, the linear theory of dose-response is used to estimate the effect of low doses of radiation. Of course, there is the possibility that some dose would produce no response; in this case, there is said to be a threshold dose. In the absence of proof that there are thresholds, the conservative thing to do is to choose the linear dose relationship. Then any error made will result in an overestimate of the effect, an error on the side of caution. The linear dose theory is an expression of scientific ignorance. Bottom up The estimates of effects of nuclear doses are critically dependent on the experience of the survivors of the Hiroshima and Nagasaki bombings. For this reason the controversy during the past decade over the actual dose at Hiroshima is very important. (169) Two groups, one at Lawrence Livermore Lab and another at Oak Ridge National Lab, agreed that accepted figures for the neutron (high LET) dose was grossly overstated; for example, they calculated that the neutron radiation at 1.18 km from the center was previously overestimated by a factor of 6 to 10. (169,170) It was thought that the main dose arose from gamma rays. This recalculation was accepted, the Hiroshima and Nagasaki data were combined, with the result that the biological effectiveness of lower doses was

5 Energy, Ch. 20 extension 9 Linear non-threshold dose relationship 5 increased by a factor of 2-3. (169,171) However, another group centered at Livermore has suggested that the Hiroshima dose is larger than thought, due to fast neutrons. (172) The slope that best describes the data as currently understood is R bomb = 150 leukemias per million people per year per gray. Support for the recalibration also came from a group studying fast neutron exposure, who found that only about 2% of exposure to surviving Japanese was from fast neutrons. (173) The effect of some doses describing the number of early deaths from each particular type of cancer as a consequence of a dose of Sv (1 rem) delivered to 1 million people and the average loss of lifespan for each type of cancer is shown in Table (174) These effects presented in Table are consensus effects (see for comparison Table E in Extension 14.5, The 1990 CAAA, NO x, particulates, and the EPA). TABLE Health Effects of Radiation Maximum Chance of Early Death/mSv/ million People Average Shortening of Life (days/msv/ million people) leukemia lung stomach alimentary canal pancreas breast bone thyroid other Source: Adapted with permission from R. L. Gotchy, Estimation of life shortening resulting from radiogenic cancer per rem of absorbed dose, Health Physics 35, 563 (1978). Copyright 1978 by Pergamon Journals, Ltd.

6 Energy, Ch. 20 extension 9 Linear non-threshold dose relationship 6 Other examples of bottom-up studies are followups on uranium miners over many years (see Extension 20.2, Nuclear units and applications). This was part of the work that established the dangers of radon and its progeny. Also, during the late 1940s and early 1950s, European doctors injected some 900 patients with 224 Ra to treat tuberculosis and ankylosing spondylitis. Some patients later developed bone cancers. The patients chances of contracting cancer increased at about 2%/gray. (18,175) Garwin claims that world data are described by the relationship in a linear no-threshold model of R cancer = 0.04 deaths/sv. (176) A microscopic view As Cohen has pointed out, the basis of the linear no-threshold dose theory is very simple: (177) A single particle of radiation hitting a single deoxyribonucleic acid (DNA) molecule in a single cell nucleus of a human body can initiate a cancer. Again, that particle might not hit a cell at all, it might traverse an entire body and not affect the body any of its cells in any way, and not trigger an event leading to cancer. This is why the process is stochastic. Natural background radiation apparently produces five DNA-damaging events per cell per year (although there is an uncertainty of orders of magnitude in this statement). (178) In fact, it is actually thought that it is double strand DNA breaks that might give rise to the cancers, not single strand breaks, as DNA has remarkable self-healing properties. (178) Obviously, double strand breaks are less likely than single strand breaks. Linearity can be

7 Energy, Ch. 20 extension 9 Linear non-threshold dose relationship 7 maintained even if there are repair mechanisms. For example, the proportion of repairs could not vary. We have already seen a lot of evidence that the linear relationship is valid, in the chapter and above. A 1 to 2 Sv dose halves the number of cells capable of division. (11) Mutations in many media are approximately 10-5 to 10-4 per cell per sievert. (11) The frequency of chromosomal aberrations is 0.1 per cell per sievert overall, and there are 4 to 18 x 10-4 excess cancers per year per sievert (2 to 10 x 10-4 of which are fatal) from 2 to 10 years after irradiation. (10,11) A study of the children of workers at Sellafield, the United Kingdom s reprocessing facility showed that children of workers have a higher probability of getting leukemia or non-hodgkin s lymphoma than comparable children whose parents were not exposed to on-the-job ionizing radiation. The study followed almost 10,000 children for up to 25 years. Thirteen children of Sellafield workers contracted leukemia, and about half that number would have been expected to have leukemia in any case, so the risk is small (of course, the extra risk is comparatively large). The researchers found that [t]he risk increased significantly with father s total preconceptional external radiation dose. (179) The lifetime excess cancers are 14 to 100 x 10-3 per sievert, of which 7 to 50 x 10-3 per sievert are fatal. (10) Overall, 1% to 3% of all cancers in the general population is attributable to natural background. Even if the dose-response relationship is not linear overall, over a restricted range about any dose, it could well be linear (Crawford and Wilson restrict themselves to alwaysincreasing, or monotonic, functions). They posit that the pollutant elicits an incremental

8 Energy, Ch. 20 extension 9 Linear non-threshold dose relationship 8 (and possibly linear) response with even the lowest dose, irrespective of the biological details of the dose-response relationship, provided that it monotonically increases. Crawford and Wilson (Ref. 166) have suggested that low dose linearity is broadly generalizable and should apply to non-carcinogens as well. They point out that there are backgrounds to all exposures, and that even if thresholds did exist, they could be superseded by the background exposure. Their argument depends crucially on the assumption that the background and the dose elicit the same response act through the same mechanism. Whether this is correct is subject to experimental verification, but so far the results are not clear. Is the linear dose relationship correct? Radiation is very complicated, and it is very hard to see the effects at very low exposure, as was pointed out above. We have seen a lot of evidence in the chapter and extensions that show that there are difficulties with the linear no threshold relationship. And, as Cohen has succinctly pointed out, (177) the simple theory predicts the cancer risk to be proportional to the mass of the animal. However, experience indicates that the cancer risk of a given radiation field is roughly the same for a 30 g mouse as for a 70 kg man, and there is no evidence that elephants are more susceptible than either. Recently, a great deal of controversy has existed over the appropriateness of the linear dose relationship. For example, we mentioned above the bone and other types of cancers caused by treatment of tuberculosis and ankylosing spondylitis. A study that looked at 48 of these patients 25 years after this treatment (such a long interval should have caught all the cancers caused by the treatment dose) found that the linear dose theory did not describe the relationship particularly well. (175) We ve mentioned the Indians of Kerala,

9 Energy, Ch. 20 extension 9 Linear non-threshold dose relationship 9 whose children are exposed in the womb to far more radiation than in other places, with no indication of effects. No genetic disorders have been found among children of the irradiated survivors of Hiroshima and Nagasaki. (180) However, Russians living downwind from the old USSR Semipalatinsk nuclear facility show a connection between radioactive fallout and heightened DNA mutation rates. (181) A few investigators claimed that risk increases at low dose, (182) but most experts are arguing among themselves over whether there are or are not thresholds. (174) A strong majority of these experts is still of the opinion that the linear dose theory is the best method available for estimating risk from ionizing radiation. All the risks commonly quoted use this method. Thresholds are more likely for chemical mutagens, according to latest ideas. Ref. 182 is of particular interest because it is a study of the effects of radon in over half the counties in the U.S. Cohen has done a very careful job of analysis that seems to show clearly that lung cancer mortality decreases between about 0 and 150 Bq/m 3 before rising again. (177,182) That is, there seems to be a protective effect, possibly biological defense mechanisms that play a role if they are stimulated. This is apparently an example of hormesis, (183,184) when biological systems display a stimulatory response at low doses and an inhibitory response at higher doses. Hormesis is observed in many experiments. Figure E shows the sort of dose-response Cohen observed for radon exposure. Radiation hormesis is being newly restudied. (185) These are so many examples of chemical hormesis and so many plausible mechanisms that could lead to hormesis that the subject is worth pursuit. It is clear that DNA breaks do not self-repair at low doses, as had been believed, lending some support to the no-threshold dose-response relation and undercutting the efficacy of hormesis. (186) Because of that, Rothkamm and Löbrich

10 Energy, Ch. 20 extension 9 Linear non-threshold dose relationship 10 propose that this lack allows direct tests to ascertain whether there was exposure to low doses of ionizing radiation. (186) A repair mechanism for DNA has been found that involves a protein researchers have called MDC1 (mediator of DNA damage checkpoint protein 1). In response to exposure to ionizing radiation, MDC1 is hyperphosphorylated in an ATM-dependent manner, and rapidly relocalizes to nuclear foci that also contain the MRE11 complex, phosphorylated histone H2AX and 53BP1. (187) This means that it can collect repair proteins at the sites of DNA breaks, helping the DNA to heal itself. (187,188) In the absence of MDC1, the cells cannot protect themselves from damage. Fig. E The dose-response curve for exposure to radon, compared to a hypothetical linear response. The minimum falls at about 150 Bq/m 3.

11 Energy, Ch. 20 extension 9 Linear non-threshold dose relationship 11 Later BEIR reports have suggested that there is evidence for linear-quadratic behavior for bone cancers following radium injection, while the preponderance of the evidence supports the linear dose theory. (17,18) The National Research Council has had problems on committees due to arguments between people trying to determine whether there are or are not thresholds, whether the dose-response relationship is linear, sublinear, or supralinear. (189) Doses could be linear in different ways in different regimes. (166) Sielken has pointed out that even when the critical assumptions are met, there is no scientific justification for the common policy (default) of assuming that the slope of the straight line from the risk at the background dose to the risk at a high dose is a good estimate or surrogate for the lowdose slope. (190) So, what does one do? Heitzmann and Wilson tell us that [s]ince it is economically and physically infeasible to identify and avoid exposure to all harmful agents, we must settle for protecting against the most harmful and the least beneficial.... As a society, we must accept and live with the idea that a necessary part of health risk assessment involves weighing benefits against costs. (166) Hoel has proposed that low-dose linearity is speculative and it is a reasonable assumption for public health purposes in those instances where there is no scientific evidence to the contrary. (191) Similarly, Brenner et al. say: 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.... Given our current state of knowledge, the most reasonable assumption is that the cancer risks from low doses of x- or γ-rays decrease linearly with decreasing dose.... This linear assumption is not necessarily the most conservative

12 Energy, Ch. 20 extension 9 Linear non-threshold dose relationship 12 approach,... and it is likely that it will result in an underestimate of some radiation risks and an overestimate of others. (192) We may use the average slope, given no better knowledge, which may overstate the response for some doses and understate it for others. This is an urgent problem, because we spend enormous amounts of money remediating things that may have negligible effects while neglecting more urgent problems. Wilson says it well: (193) Society spends thousands of times more to avert deaths from radiation exposure than from more common, and more reliably determined, causes of death for which LNT certainly applies. Another area that has not been thoroughly investigated is the existence of drugs that would protect against radiation or give some help after exposure. The drugs amifostine and tempol scavenge free radicals and if they are present at the time of exposure, they could afford some protection. (194) The compound 5-androstenediol seems to work protecting priomates, and may help humans. One especially promising drug is being tested for use by the Army. (195) The protection and the mechanisms through which protection occurs are still largely mysterious. (194) Absolute versus relative risk The absolute-risk model assumes that the radiation-induced cancer rate is an extra additive risk independent of the rate of incidence of the particular type of cancer; the relative risk model assumes that the risk is some multiple of the existent rate for that type of cancer. The latter model gives higher numbers than the former, because the cancer rate increases with age. Unfortunately, there is no way to decide the correct risk model which model is appropriate may depend on the cancer type. (47) However, the relative risk model satisfies

13 Energy, Ch. 20 extension 9 Linear non-threshold dose relationship 13 the criterion of conservatism and therefore should have been used in the Rasmussen report. A problem with the Rasmussen report is the use of an absolute-risk model. (47,196) Again, the procedure is to try to adopt a conservative model of cancer risk in light of the lack of information on risk and the latency period for cancers (as much as four decades). This is not the most conservative approach.

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