Dale L. Preston Hirosoft International Eureka, CA Cancer Risks Following Low Dose Radiation Exposures: Lessons from Epi Studies The Accidents at Fukushima Dai-Ichi Exploring the impacts of Radiation on the Ocean November 13, 2012

2 Topics Describing long-term radiation effects on disease risks Follow-up studies of radiation health effects –Atomic bomb survivors (Life Span Study) –Techa river residents Results –Leukemia –Solid cancers Conclusions

Radiation Effects on Disease Risks Affected cases indistinguishable from other cases Magnitude of effect depends on dose –Dose rate may be important –Effects (if any) of low to moderate doses appear to be “small” Effects can appear and persist long after exposure Effects can depend on sex, age, and other factors Detection and characterization requires: –Large exposed populations (especially when doses are low) –High quality long-term follow-up –Good dose estimates –Careful analyses using sophisticated statistical methods, 3

Disease Risks and Rates Risk –Probability of disease occurrence during a specified period (e.g. lifetime after exposure, within 10 years of exposure, …) Rate –Ratio of the number of new cases in a time period to the total time at risk in the time period (person-years) –Risks can be computed from rates –Characterization of rates is central to modern description of radiation effects. 4

Disease rates and radiation effects Baseline rate B 0 –Describe population rates in the absence of radiation exposure –Depends on age, sex (s), and other factors Describing rates in an exposed population –Relative risk model: B 0 [ 1 + ERR(d)] The excess relative risk (ERR) describes the magnitude of the radiation effect relative to the baseline rate. –Rate difference model: B 0 + EAR(d) The excess absolute rate (EAR) describes the difference between the rate in the exposed and an unexposed population. 5

Describing Radiation Effects on Rates Issues Shape of dose response –Linear (LNT) –Non-linear (quadratic, J-shaped, high dose attenuation, …) –Threshold Dose rate effects Effect modification –Time since exposure, age at exposure, attained age, sex, ethnicity, … Interactions with other risk factors –Additive –Multiplicative –Other 6

Atomic Bomb Survivor Studies Initial studies ( ) focused on genetic effects in children of survivors –No evidence of heritable genetic effects Anecdotal reports of radiation-associated leukemia from late 1940’s –Leukemia registry established in early 1950’s Life Span Study (LSS) cohort established for long-tern follow-up of survivors –All-cause mortality and leukemia incidence follow-up since 1950 –Solid cancer incidence follow-up since 1958 Clinical follow-up of a subset of the LSS since

Life Span Study 120,321 people with 93,741 exposed –58% women –40% exposed as children Individual organ dose estimates for 93% of exposed –Mean weighted colon dose ~170 mGy within 3 km –Maximum mGy –25% of exposed mGy –15% 100+ mGy Virtually complete follow-up –Since 1950 for mortality and leukemia incidence solid cancers; 371 leukemias –Since 1958 for solid cancer incidence 17,448 cases (3,994 unexposed) 8

Linear ERR per 100mGy 0 – 2 Gy 0.05 No evidence of non-linearity (LQ model on 0 – 2 Gy) P > % (850/7,851) of cases among those with 5 mGy or more associated with radiation exposure 48% above 1 Gy - 307/645 LSS Solid Cancer Incidence Dose Response 9 Using RERF public dataset lssinc07.csv ( Proximal zero dose baseline (adjusted for distal and NIC)

LSS Solid Cancer Incidence Dose Response 0 – 0.5 Gy Linear ERR per 100 mGy 0 – 2 Gy – 100 mGy 0.05 LSS often described as a high dose study, but has as more information on risk at relatively low doses (<100 mGy) than many low dose studies Test for trend 0 – 100 mGy P = Using RERF public dataset lssinc07.csv ( Proximal zero dose baseline (adjusted for distal and NIC)

LSS Solid Cancer Incidence Temporal Patterns 11 ERR EAR Significant effect modification by attained age and age at exposure and sex (ERR only)

LSS Leukemia Risks Analyses based on 312 cases –CLL (12 cases) and adult T-cell leukemia (47 cases) were excluded Significant non-linear dose response ERR at 1 Gy 2.3 (age 60 age at exposure 25) ERR at 100 mGy 0.09 No significant sex-difference in the ERR 12

LSS Leukemia Temporal Patterns ERR decreases with both attained age with no sex difference EAR decreases with attained age and time since exposure with lower risks for women than men 13

Mayak Plutonium Production Association 14 Mayak Secret facility located in a closed territory in the Southern Urals Began operation in 1948 Produced Pu used in first Soviet nuclear weapon

Mayak Production Association 15 Complex occupational exposures –External gamma –Inhaled plutonium for radiochemical and plutonium production worker ~40% monitored for Pu exposure –Highest doses in period Multiple Environmental exposures

Mayak-related Environmental Releases Discharges into Techa River PBq Cs137, Sr90, Sr89, …. (98% ) Khyshtym accident PBq Rare earths, Sr90 Y90 Karachai resusupension PBq Cs137, Sr90 Gaseous aerosols PBq I131 16

Techa River Cohort 29,730 residents of 41 riverside villages born before 1950 –58% women –39% exposed as children Individualized organ dose estimates –35 mGy mean stomach dose (8.5 mGy per year ) –414 mGy mean marrow dose (72 mGy per year ) (90% from Sr) Follow-up –Since 1950 for morality; 1953 for leukemia incidence; 1956 for solid cancer incidence –~20% lost to follow-up due to migration –2,303 solid cancer deaths; 99 leukemia cases (27 CLL) 17

Techa River Solid Cancer Mortality Weak suggestion that ERR increases with increasing age 2% (50/2303) of solid cancer deaths associated with exposure Significant dose-response following low dose rate exposures ERR broadly similar to that seen in the LSS Little power to characterize effect modification or to look at cause- specific solid cancer mortality 18 ERR at 100 mGy 0.06 (95% CI to 0.13) No significant non-linearity, but power to detect non-linearity is low Comparable to LSS estimate No significant sex difference in ERR

Techa River Leukemia Risks Significant dose response with ERR per 100 mGy of 0.23 No significant non-linearity No significant attained age, sex, or ethnicity effects 19 Weak suggestion that doses received 2 to 10 years before diagnosis have higher ERR (0.5) than doses received more than 10 years earlier (0.17) –Similar pattern seen in Mayak workers –Pattern consistent with LSS temporal variation 47% (34 of 72) of cases associated with radiation exposure

Conclusions Epidemiological studies of radiation exposed populations are challenging and expensive, but have provide important information on the risks at low doses and low dose rates The exposures of Techa River residents are similar in nature to those received by people in areas contaminated by the Fukushima accident Studies of the Techa River cohort find clear evidence of low dose rate radiation effects on cancer risks Techa River risks are comparable to LSS risk and provide no evidence of a reduction in effect at low doses 20

Fukushima Challenges A well-designed long-term epidemiological study should be developed –Power to detect effects may be limited but failure to find effects would be a reassuring message Studies should include an assessment of the long term psychological effects –These have not been investigated in a systematic manner in other major radiation exposed cohorts –Could help in developing better ways to work with public in the even of future radiation accidents 21

Sources LSS Solid cancer incidence Preston et al Radiat Res :1-64 LSS Leukemia incidence Hsu et al Radiat Res in press Preston et al Radiat Res (Suppl 2):68-97 Techa Solid cancer Schonfeld et al Radiat Res in press Krestinina et al Radiat Res : Krestinina et al Int J Epidemiol : Techa Leukemia Krestinina et al Leukemia (tent.) Krestinina et al Radiat Environ Biophys :

Acknowledgments I am grateful for long term support of my efforts in the Atomic bomb survivor and Southern Urals studies provided by the National Cancer Institute, the Department of Energy, and the Radiation Effects Research Foundation I have benefitted greatly from my collaborations with: Elaine Ron (NCI), Don Pierce (RERF), Ludmila Krestinina and Marina Degteva (URCRM – Techa River), Sara Schonfeld (NCI, IARC) and many more 23