Abel J. González

1. Plausibility vis-à-visAttributability in considering Health Effects due to Low Radiation Dose Exposures Abel J. González Representative to the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) Vice-President of the International Commission on Radiological Protection (ICRP) Member of the Commission of Safety Standards of the IAEA Autoridad Regulatoria Nuclear;Av. Del Libertador 8250; (1429)Buenos Aires,Argentina+54 1163231306;agonzale@sede.arn.gov.ar

2. The conundrum: ‘Effect or no Effect’Is that the question?

3. Apparently contradictory premises • It is highly plausible that lowrad-induced mutations in the DNA may eventually evolve into detrimental health effects. • Detrimental health effects cannot not be attributedto lowrad.

4. Thesis Thetwo premises are not contradictorybut in fact are complementary!  …therefore…

5. (i)  It is plausible that exposure to lowradmight induce detrimental health effects. –consequently radiation protection ought to be required! (ii) Individual health effects cannot be attributed to lowrad situations. (theoretical enumerations of these effects are technically wrong!)

6. The link between the two premises/theses is the intrinsic uncertainty of current knowledge onradiation health effects at lowrad. This implies limitation in the epistemology, namely restrictions to the theory of knowledge on the phenomena linking lowrad exposure and health effects, especially with regard to its methods, validity, and scope.

7. The Facts

8. Likelihoodof effects Limit of pathological knowledge Limit of epidemiological knowledge Burns, sickness & death 100% (certainty) Clinically observable (pathology of individuals) Statistically estimated (epidemiology of populations)  Decreasing risk of cancer 5% ? Dose (mSv) ~100 ~1000 31 October, 2014 8

9. Clinical Diagnosis Epidemiological Estimations Epistemological limitations Knowledge Animal Experimentation Human Biology

10. Timing of events leading to radiation effects.

11. Timing of events leading to radiation effects.

12. Timing of events leading to radiation effects.

13. Timing of events leading to radiation effects.

14. Timing of events leading to radiation effects.

15. Physiology ? Biology Physics and chemistry Epidemio- logy Time 100 years 10-15s. 10-9s. 10 2 m. 10-3s. Manifestation of effects Exposure The time scale of the phenomena limits knowledge.

16. A simple example of epistemological limitation

17. Deterministic effects: Do we know all? What is the threshold for protracted exposures? Likelihood 100% ?  >1000mSv  Dose Time

18. Misunderstandings

19. Likelihood Certainty (100%) • SLOPE • Is 0.005%/mSv the probability of cancer at lowrad? Doses 31 October, 2014 19

20. ‘Modeling’ effects

21. UNSCEAR estimates

22. UNSCEAR modeling for ‘estimating’ effects (‘estimating’ because it is an approximate calculation, appraisal or judgment) • Risk of exposure-induced cancerincidence(REIC) • Risk of exposure-induced death (REID) • Excess cancer deaths (ECD) • Years of life lost per unit dose (YLL) • Years of life lost/radiation-induced cancerdeath(YLLRIC)

23. China Puerto Rico U.S.A. Japan Distribution of the REID from solid cancer for various current populations, assuming a testdoseof 0.1 Sv, and using generalized linear–quadratic excess relative risk models fitted by Bayesian Markov Chain Monte Carlomethods, calculated for a population in equilibrium.

24. ‘Nominal’ statistical uncertainty distribution for REID approximately log-normal

25. UNSCEAR Summary The estimated average REID (lifetime risk of death) following an acute dose of 1 sievert (Sv) is: • between 4.3 and 7.2 per cent for allsolid cancers, and • between 0.6 and 1.0 per cent for leukaemia. • (namely, about 5% per Sv for all malignancies)

26. Modeling of protection Modeling of effects

27. Radiation Protection Epistemology Paradigm P r a t i c e 27

28. The radiation protection ‘model’orradiation protection paradigm

30. ICRP ought to introduceDetriment-adjusted Nominal Risk Coefficients

31. Detriment-adjusted Nominal Risk Coefficients • Risk Coefficient: A numeral, expressed in % Sv-1, which –multiplied by dose– quantifies the plausibility of harm. • Nominal: The stated numeral does not necessarily correspond to its real value: it relatesto hypothetical, rather than real, people averaged over age and sex. • Detriment-adjusted: The numeral is multidimensional, expressing plausible expectation of harm, and includinginter aliathe weighted plausibility of fatal and non-fatal harm, and life-lost should the harm actually occur.

32. Rounded value used in RP standards~5%Sv-1

33. Plausible Probability of Stochastic Effects, p average 2.4 mSv typical 10 mSv high 100 mSv increment ofp Background incidence In this zone the relationship is irrelevant for radiation protection increment ofD Dose, D backgroundannual dose BARC 31 October, 2014 33

34. An unpractical alternative

35. Plausible Probability of Stochastic Effects, p D1 = D2 p1  p2 (p1<<p2) increment ofp2 Background incidence increment ofp1 increment ofD1 increment ofD2 Dose, D backgroundannual dose BARC 31 October, 2014 35

36. Likelihood But uncertainty remains! (not known, not completely confident or sure) Certainty (100%) Doses 31 October, 2014 36

37. The Fight

38. LOWRAD IS BAD Mutagenic properties Genetic instability Bystandards effects & clastogenic plasma factors Epidemiological evidence LOWRAD IS GOOD Minute mutagen Adaptive response Apoptosis >> cancerogenesis… then.. …hormesis! Epidemiological evidence The Fight

39. The challenge: Plausibility versus Attributability 31 October, 2014 39

40. Plausible(from L. plausibilis, from plaus-, plaudere ‘applaud’) Detriment-adjusted nominal risk coefficients are plausible because they are apparently reasonable, likely, and probable, …but…without compulsorily being so! 40

41. The detriment-adjusted nominal risk coefficientsare presumed to be seemingly or apparently likely, fair, reasonable, valid and valuable and therefore acceptable. However, they should not give a deceptive impression of reliability, although this limitation should not be construed to mean that they arespecious, namely superficially plausible, butactually wrong, –misleadingly attractive only in appearance!

42. Formalization of plausibility • The product of nominal risk coefficientstimes dose is a probability; but it is aprobabilityconditional to the LNT model assumption. • Whether the assumption is valid or not is unknown, but its validity may be assigned a weight indicating the expert's degree of belief in it. • If the weighting factor were a true probability, the weighted probability wouldbe the unconditional probabilityof the effect actually occurring. • However, the weighting factor is not a true stochastic quantity (even though in Bayesian statistics it may be treated as a probability). • It follows that the weighted probabilityis not an unconditional probabilityin the formalBernoullian definition of probability. • Thus, Beninson and Lindell suggested that it be termed ‘plausibility’. [J.Radiol.Prot. 21(2001):39-44]

43. ‘Nominal’ statistical uncertainty distribution for REID approximately log-normal Cumulative plausibility confidence limits 1.2–8.8% Sv-1

44. 95% upper limit 1.0- Cumulative plausibility Assuming a 20% degree of ‘disbelief’ 0.8- 0.6- 8.8%/Sv 0.4- 0.2- Risk (%)/Sv 5% ‘ 2 ‘ 4 ‘ 8 ‘ 14 ‘ 6 ‘ 10 ‘ 12

45. 95% upper limit 1.0- Cumulative plausibility Assuming a 50% degree of ‘disbelief’ 0.8- 0.6- 8.8%/Sv 0.4- 7%/Sv 0.2- Risk (%)/Sv 5% ‘ 2 ‘ 4 ‘ 8 ‘ 14 ‘ 6 ‘ 10 ‘ 12

46. 95% upper limit 1.0- Cumulative plausibility Assuming a 80% degree of ‘disbelief’ 0.8- 0.6- 8.8%/Sv 0.4- 5%/Sv 0.2- Risk (%)/Sv 5% ‘ 2 ‘ 4 ‘ 8 ‘ 14 ‘ 6 ‘ 10 ‘ 12

48. There are other subjective qualifiers ofplausibility

49. Verisimilitude Plausibility(also require) Believability Logicalness Admissibility Acceptability Fidelity Integrity

50. Namely: given the epistemological limitations • we should assume that lowradmay plausibly be detrimental to health; and, therefore, • we ought to protect people against lowrad;although protection must be commensurate (optimization).