Radiological Risk from Low Dose and Low Dose-Rate Exposures: An - - PowerPoint PPT Presentation

MELODI Conference

Munich, November 2015

Roy Shore, Linda Walsh, Werner Rühm, Tamara Azizova

Radiological Risk from Low Dose and Low Dose-Rate Exposures: An Epidemiologic Perspective

hrshore@gmail.com (Abridged version)

Disclaimer

This represents preliminary concepts and data, and not necessarily the position of the ICRP Task Group-91 on Dose and Dose-Rate Effectiveness Factors.

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Is there a need for a DDREF? If so, …  How large is the DDREF?  Should the DDREF be separated into a:

• LDEF (low-dose effectiveness factor) – upward curvature in

the dose-response function, rather than linear, for a single brief exposure

• DREF (dose rate effectiveness factor) – less effect per unit

dose for low dose rates or numerous small exposures,

• r …

 Are the values of the LDEF and DREF the same?

DDREF: Dose and Dose-Rate Effectiveness Factor (DDREF) Questions for Low-LET radiations

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Recent Views regarding DDREF

 From radiobiological studies DDREF estimates often have ranged from 2 to >5.  ICRP (2007) and UNSCEAR (2006) indicated compatibility with a DDREF of 2  BEIR VII (USA, 2006) derived an estimate of DDREF of 1.5 (with a potential range of 1.1-2.3)  SSK (Germany, 2014) – report concluded that no DDREF is necessary (i.e., DDREF of 1).

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Low-Dose Effectiveness Factor (LDEF): A-bomb Life Span Study

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(Ozasa, Radiat Res, 2012;177:229-)

Life Span Study (LSS) Solid Cancer Mortality Risk: Linear & Linear-Quadratic Dose Response

Weighted Absorbed Colon Dose (Gy) Excess Relative Risk (ERR)

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• The quadratic term was statistically significant over the dose range 0-2 Gy,

with estimated curvature (β/α) = 0.8

• Significant dose response on 0-200 mGy

(Preston D et al: Radiat Res 168:1-64, 2007)

 “No significant evidence” of non-linearity (p=0.09) in the dose response

 Estimated curvature (β/α) = 0.3 (90% CI 0.01, 0.9)  Significant dose response on 0-150 mGy

50 100 150 1 2 3

% Excess Relative Risk Weighted Absorbed Colon Dose (Gy) (LSS Incidence, 1958-1998)

Fitted linear dose response at age 70 following exposure at age 30 Smoothed non-parametric dose response

ERR/Gy= 47% (90%CI: 40-54%) Dose-threshold: 40 mGy (90% CI: <0, 85 mGy)

LSS dose response: Solid-cancer incidence

0.0 0.5 1.0 1.5 2.0 2.5 3.0 0.0 0.5 1.0 1.5 DS02 weighted colon dose (Gy) Excess relative risk

• 0.02

0.0 0.5 1.0 1.5 2.0 2.5 3.0 0.0 0.5 1.5 1.0 Excess relative risk

Linear ERR@ 1Gy: 0.47 (95% CI 0.38, 0.56) Bayesian Semi-parametric: 0.45 (95% CI 0.36, 0.56) Linear

DS02 weighted absorbed colon dose (Gy)

LSS solid cancer incidence (1958-98)

(data from Preston, Radiat Res, 2007)

(Furukawa K, Risk Analy, In press, 2015)

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LSS solid cancer incidence (1958-98)

0.0 0.5 1.0 1.5 2.0 2.5 3.0 0.0 0.5 1.0 1.5 DS02 weighted colon dose (Gy) 0.0 0.5 1.0 1.5 2.0 2.5 3.0

0.00 0.05 0.10 0.15 0.20

• 0.02

0.00 0.02 0.04 0.06 0.08 0.10 0.12 Excess relative risk

Linear Bayesian Semi-parametric

0-200 mGy

Excess relative risk 50 100 150 200

• 0.02

0.00 0.02 0.04 0.06 0.08 0.10 0.12 DS02 weighted absorbed colon dose (mGy)

(Furukawa K, Risk Analy, In press, 2015)

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DREF: Some Issues in Addressing Risk after Low-Dose or Low Dose-Rate (LDLDR) Exposures

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Low-Dose Studies: Intrinsic Implications

 As the Radiation Signal-to-Background (“signal:noise”) ratio of cancers decreases at lower doses, radiation effects become increasingly uncertain

• Therefore, both statistical power and statistical precision

(per unit dose) decrease greatly at low doses, i.e., uncertainty increases appreciably.

 Bias from unmeasured confounding variables (e.g., other disease risk factors) has the potential to be relatively greater in a low-dose study

• Because the magnitude of bias (either to exaggerate or

mask the true degree of association) may approach or exceed the magnitude of the dose effect.

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(Brenner et al, PNAS 100:13762-, 2003)

Sample Size Needed to Study Various Doses with Adequate Statistical Power, Lifetime Risk

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 Potential biases due to dose-dependent differences, e.g.

• Lifestyle factors – e.g., smoking, alcohol consumption
• Healthy Worker Effects
• Unaccounted for radiation exposures – e.g., medical
• Dose-related differential adequacy of diagnosis and

completeness of cancer ascertainment

 Sources of uncertainty, e.g.,

• Dosimetric uncertainties
• Quality of the cancer morbidity or mortality data
• Uncertainties in modeling, risk transport to other populations,

etc

Issues to Consider in Analyzing and Interpreting LDLDR Studies

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Examining the Dose-Rate Effectiveness Factor (DREF) in Low-Dose or Low Dose-Rate (LDLDR) Studies

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 Conduct a meta-analysis. Why?

 Provide “weight of evidence”.  Much larger numbers of cancers and person-years needed at low doses to detect risks and achieve precise risk estimates.

 Inclusion criteria: Studies must have a dose-response risk estimate Gy-1 and have low doses and/or highly fractionated or protracted exposures  Compile comprehensive list of studies with dose-response analyses of LDLDR data – try to avoid redundancy among studies, use latest data, and minimize study selection biases (e.g., publication bias, “cherry picking”)  Meta-analysis to evaluate ratios of risk coefficients in the LDLDR studies to the matching LSS data – (cf. Jacob et al, Occup Environ Med, 2009)

Approach to Examine Low Dose and/or Low Dose Rate (LDLDR) Studies

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Radiation effects for various types of cancer may be modified differently by:  Tumor biology: relevant genes & genetic pathways; epigenetic, tissue and metabolic cofactors  Other environmental risk factors – e.g. impact of smoking, alcohol intake, infections.  Baseline rates which vary across populations and over time. A knowledge gap exists regarding organ specific risks, especially following acute or protracted exposures under a few hundred mSv.

Rationale to Examine DREF for Specific Cancer Types

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 Low Dose Effectiveness Factor – preliminary evidence of upward curvature for solid cancer in the A-bomb LSS  All solid cancer DREF: Most (9/11) of the LDLDR studies with >250 cancers had positive risk coefficients

• Meta-analyses are underway to compare LDLDR risk with LSS risk

 LDLDR summaries of specific tumour sites:

• Breast cancer DREF – substantial evidence for LDLDR risk
• Lung cancer DREF – weak evidence of LDLDR risk. But problem of

possible confounding by smoking

• Stomach cancer DREF – moderate evidence of LDLDR risk
• Colon cancer DREF – small numbers of studies and cancers. Little

evidence of risk

Summary of Preliminary Findings regarding Low Doses

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 Uncertainties in the risk of leukemia and solid cancers at low doses (<100, <50, <20 mSv) and low dose rates (but data are becoming stronger)  Are low-dose risk and DDREF factors similar for various tumor sites?  Are low-dose radiation risks modified by disease risk factors: lifestyle, infectious, reproductive, etc?  How large an impact do biological and genetic susceptibility factors have on the radiation induction of cancer or cardiovascular disease, especially at low doses?

Epidemiologic Gaps in Knowledge

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 Epidemiologic data regarding DDREF are important because they directly model human populations that are highly heterogeneous with respect to innate susceptibility and exposure co-factors.  Ultimate judgements regarding DDREF, however, will need to integrate information about associated biological mechanisms, experimental studies of dose and dose-rate factors in controlled animal experiments, and the epidemiologic observations.

Epidemiologic Data and DDREF Assessment

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