1 Review of “Development of a C LL Risk Model for NIOSH-IREP”

David Richardson

Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill

August 25, 20092 BACKGROUND The Energy Employees Occupational Illn ess Compensation Program Act of 2000 (EEOICPA) is a compensation progr am for current and former employees in the U.S. nuclear weapons complex who developed cancer as a re sult of their occupational exposure to ionizing radiation. Under the EEOICPA, chronic lymphocy tic leukemia (CLL) current ly is regarded as a non-radiogenic form of cancer.

NIOSH is reconsidering this cl assification of CLL as a non-ra diogenic disease. SENES Oak Ridge, Inc., in collaboration with NIOSH, devel oped a prototype risk model for CLL that allows for non-zero calculations of probability of causa tion (Trabalka and Aposto aei, Development of a CLL Risk Model for NIOSH-IREP, June 30, 2009). This review comments on the proposed risk model for CLL, proposed radiation risk coeffi cients, and proposed latency assumption.

Proposed Risk Model for CLL Analyses of associations between estimate d radiation doses and cancer incidence among Japanese atomic-bomb survivors in the Life Sp an Study (LSS) provide estimates of the excess relative risk (ERR) for most cancer types in NIOSH-IREP. Given the small number of CLL cases in this atomic bomb survi vor cohort (reflecting th e fact that CLL is very uncommon in the Japanese population), the draf t report titled “Development ofa CLL Risk Model for NIOSHIREP” proposes using a broader group of maligna nt diseases for development of a CLL risk model. Specifically, the draft report proposes a risk model fo r CLL derived by modifying the current NIOSH-IREP risk model for the gr oup of non-Hodgkin’s lymphoma (NHL), Hodgkin’s3 disease, and multiple myeloma (MM). The draft report asserts that “Based on the information reviewed to date ... we thi nk that the risk model in IREP for NHL, Hodgkin’s disease (lymphoma), and multiple myeloma (lymphoma and multiple myeloma grouping; ICD-9 codes
200

− 203) (Preston et al. 1994; Land et al. 2003) could be a reasonabl e surrogate for a CLL risk model.”

As the draft report notes, there are major diffe rences between NHL, Hodgkin’s disease, and MM; and, the argument for inclusion of Hodgkin’s diseas e in this group of dis eases which are intended to serve as a “surrogate” for CLL is not co mpelling (pages 15-16). Contemporary lymphoma classification schemes consider B-cell CLL a nd small lymphocytic lymphoma to be a single disease entity, and a sub-type of non-Hodgkin’s lymphoma, in recognition of the biological and clinical similarities between these B-lymphocyte malignancies (1). The Life Span Study data encompass an adequate number of NHL cases w ith which to support a separate analysis of radiation-dose response associ ations for NHL. NIOSH should revise the proposed model for CLL to draw upon information derived from an an alysis of the associa tion between radiation dose and NHL in the LSS cohort.

The draft report further contends that the pr oposed grouping of NHL, Hodgkin’s disease, and MM is justified given the obstacles to devel oping a new risk model based on analysis of incidence of NHL. This is an argument for doing wh at is convenient, rather than logical. The report notes that an analysis of NHL would requi re data access, use of specialized software, and an independent regression analysis of these data. These are relatively modest obstacles to the proper conduct of this fede ral compensation program.4 Proposed Radiation Risk Coefficients The radiation risk estimates for NHL, Hodgkin’ s, and MM in IREP that are proposed for application to CLL analyses are derived via a m odel in which the ERR/Sv is time-constant for exposure ages greater than or e qual to 30 years and attained ages greater than or equal to 50 years (ERR/Sv=0.178; 95%CI: <0, 0.9465). Given that CLL is a disease of older ages and very rarely occurs at ages < 50 years, the modeled va riation in ERR/Sv with at tained age is of little consequence for claimants (i.e., terms in the ex pression shown on page 15 of the draft report for the modifier involving g ( a ) have little consequence since th e attained age of CLL cases is typically greater than 50 years) . In fact, for simplicity, a CLL model might be simplified by striking attained age effect modification. Similarl y, given that few workers were exposed at ages <18 years, and the modeled variation in ERR/Sv is modest over the age range 18-<30 years, the proposed model may largely behave as a time-c onstant model for the ERR/Sv (with an ERR coefficient of approximately 0.18 per Sv).

The radiation risk estimates for NHL, Hodgkin’ s, and MM in IREP that are proposed for application to CLL analyses (i.e, an ERR/Sv=0.178 for exposure ages greater than or equal to 30 years and attained ages greater than or equal to 50 years) is substantially smaller than the radiation risk estimate in Table 2 (page 16) for NHL among men (ERR/Sv=0.91). Moreover, Richardson et al. (2009) reporte d on the association between DS02 radiation dose estimates and mortality due to non-Hodgkin’s lymphoma among males aged 15-65 years in the Life Span Study cohort with mortality follow-up through 20 00 (2). The estimated ERR/Sv (ERR/Sv=0.86; 90%CI: 0.13, 2.03 under a minimal 5-year lag and ERR/Sv=1.12; 90%CI: 0.26, 2.51 under a 10- year lag) is larger in magnitude than the time-constant ERR/Sv proposed for exposure ages5 greater than or equal to 30 year s and attained ages greater than or equal to 50 years, and similar in magnitude to the estimate reported for NHL am ong males in Table 2 of the report. Richardson et al. (2009) also noted that when the LSS data were limited to survivors with doses in the range 0-<0.5 Sv (a dose range most comparable to the worker claimants in this compensation program) estimates of radiation-lymphoma mortality associ ations were of greater magnitude than when estimated over the entire dose ra nge. Under a 5-year lag assump tion (i.e., events occurring over the period 1950-2000), the estimated ERR/Sv for NHL was 2.86 (90% CI: 0.10, 7.24). This value is of much larger magnitude than the pr oposed time-constant ERR/Sv for exposure ages greater than or equal to 30 years and attained ages greater than or equal to 50 years.

Proposed Latency Assumption The preferred model for NHL, H odgkin’s disease and MM used in the draft report allows the ERR/Sv to vary as a function of age at exposure, a ttained age, and their join t effect. Jointly these parameters describe the effect of time-since-exposure in the LSS c ohort. It is therefore unclear what basis there would be for im posing a latency distribution that spans the period when there is empirical (i.e., observed) data on the evolution of lymphoma risk following irradiation in the LSS population. The draft report proposes allowing for age at exposure and attained age effects (and their interaction) as well as imposing a distri bution of latency effects that only reaches its maximum approximately 25 years after exposure. The preferred LSS model for the grouping of lymphomas (as implied by its use in NIOSH IREP ), allows for a time-constant ERR/Sv for exposure ages greater than or e qual to 30 years and attained ages greater than or equal to 50 years (once the interval between exposure and start of follow-up has transpired). This would imply that for exposure ages greater than or equa l to 30 years and attained ages greater than or6 equal to 50 years the exposure effect should be at its maximum once cancer incidence follow-up of the LSS cohort commences (approximately 13 years after exposure) and persist at that magnitude thereafter. Under the proposed model, the ERR/Sv only reaches its maximum value approximately 25 yr after exposure.

Under the proposed prototype model for CLL, the la tency function is notably different from that used for other cancers (including the current mo del for lymphoma and multiple myeloma). Data collection for incident cancers for the atomic bo mb survivor studies commenced 13 years after the bombings (with a special leukemia registry providing leukemia inci dence data commencing in 1950). The LSS risk models describe the te mporal evolution of the ERR/Sv (with age at exposure and attained age) in the period 1958 forwards (1950 forwards for leukemia). Rather than allow an abrupt transition from 0 excess risk to the modeled ERR/Sv in the LSS for a given attained age and age at exposure (or, extrapolating using the e xponential age functions that are modeled), a smooth latency function is used in NIOSH-IREP. Under the current IREP model, for lymphoma and multiple myeloma (and all solid cancers except thyroid and bone cancer), an S-shaped (sigmoid) function was used to descri be a smooth transition in the ERR/Sv over the latent interval. The nominal va lue of the midpoint of the sigmoi d latency function is assumed to be 7.5 yrs, and the shape parameter for this functi on is set so that the latency adjustment attains values of approximately 0.01 and 0.99 at 4 and 11 yrs, respectively. Given empirical data for lymphomas in the period approximately 13 years or more after exposure, it would make sense to employ a model that gives full weight to fitted ERR/Sv estimates in the period when there is empirical data available. As noted above, the inclusion of model terms for effect modification7 by attained age, age at exposure, and their joint eff ect, is used to describe variation in effect with time since exposure in the period wher e empirical data are available.

Epidemiological findings not covered in the draft report Richardson et al. (2009) reports on estimated ra diation dose-lymphoma mo rtality associations among male workers at the SRS. Positives associations between radiation dose and NHL mortality were observed in that cohort as well under 5- and 10 -year lag assumptions (ERR/Sv=6.45; 90%CI: 0.48, 17.95; and, E RR/Sv=7.62; 90%CI: 0.93, 20.77).

Given that CLL cases may be asymptomatic for many years, and that incidence data may have greater diagnostic accuracy than mo rtality data, there has been interest in results of incidence studies of CLL following radiation exposures. Some recent incidence studies of CLL among radiation workers have noted pos itive associations, including a study repor ting an increase in CLL among Czech uranium miners who had gamma radiation exposures (3), and studies reporting positive associations between estimated radiation dose and CLL incidence in the Ukrainian-American study of leukemia and rela ted disorders among Cher nobyl recovery workers (ERR/Gy = 4.09; 95% CI < 0-14.41) (4), and in the study of hematological malignancies was conducted among Chernobyl liquidators (accident r ecovery workers) from Belarus, Russia and Baltic countries (ERR/100 mGy= 0. 47; 90%CI: nd, 7.61)(5). In contrast, Muirhead et al. reported no evidence of an association between radiation dose under a 10 year lag and CLL incidence (ERR per Sv=-0.337, 90% CI: -1.72, 3.1) in their analysis of workers in the National Registry for Radiation Workers (6).8 Comment on the calculation of expe cted CLL counts for the LSS population It is unclear what contribution to this report is made by the calcul ation of the expected incidence of CLL in the LSS cohort (and Appendix A). Th e interpretation of the findings appears onesided; the authors contend that clear interpretatio n of the findings is only possible if the evidence suggests that ionizing radiation is protective for CLL. “If the es timated number of CLL cases in the absence of exposure had been greater than 4 [the observed number] then we might have been able to conclude that the dos e-response for CLL in the LSS cohort should be negative.”

The authors should clarify why they have tabu lated the expected count over the period 1945- 1987 (rather than over the period Oct 1, 1950-1987). The report currently includes “estimates for the number of cases of CLL expected in the LSS cohort over the 42-y period from 1945

− 1987.” In contrast, the cited LSS analysis spans the pe riod Oct 1, 1950-1987; it is unclear why the report includes expected counts spanni ng a non-comparable period (and l onger period). In Preston et al. (1994) cancer cases ascertained by the Leuke mia registry prior to Oct 1, 1950 were excluded. The estimated number of expected cases should be somewhat reduced when re-tabulated over the period Oct 1, 1950-1987.

The observed number of CLL cases (4 cases obser ved) is 4.44 times the number expected based on the Japanese population (0.9 cases expected ) and 3.33 times the number expected based on incidence rates for Hiroshima and Nagasaki (1.5 cases expected), leaving aside the problem in derivation of the expected counts noted above. The report should revise the calculations of expected counts to correspond to the period of CLL ascertainment in the cited LSS report,9 include an estimate of the ratios of observed to e xpected counts (i.e., SIRs), and report associated 90% confidence intervals for these ratios.

Conclusion This report provides a useful star ting point for consideration of a risk model for CLL to apply via NIOSH-IREP. This model may be strengthen ed by several suggested revisions, described below.

Firstly, NIOSH should revise the proposed model for CLL to draw solely upon information for
NHL.

Secondly, the proposed ERR/Sv for exposure ages gr eater than or equal to 30 years and attained ages greater than or equal to 50 years (E RR/Sv=0.178; 95%CI: <0, 0.9465) is substantially smaller than the radiation risk estimate in Table 2 (page 16) for NHL among men (ERR/Sv=0.91) and substantially smaller than va lues reported for the association between radiation dose and mortality due to non-Hodgki n’s lymphoma among males aged 15-65 years in the Life Span Study cohort with mortality follow-up through 2000 (ERR/Sv=0.86; 90%CI: 0.13, 2.03 under a minimal 5-year lag and ERR/Sv=1 .12; 90%CI: 0.26, 2.51 under a 10-year lag). Given that the LSS data sugge sts a significant excess risk fo r males (2, 7), sex-averaged estimates of association may unders tate the excess risk for male claimants. The revised NIOSH model should incorporate information regarding the magnitudes of radiation-lymphoma associations observed in these anal yses of male LSS survivors.10 Thirdly, the proposed risk model allows ERR/Sv to vary as a function of age at exposure, attained age, and their joint effect. However, the model in the draft report further includes a distribution of latency intervals. Under the proposed model the ERR/Sv reaches 0.999 of the maximum 25 years after exposure. The revise d NIOSH model should follow the current IREP model for lymphoma and multiple myeloma by employing a sigmoid latency function with a midpoint of the sigmoid latency function at 7.5 yr s and shape parameter set so that the latency adjustment attains valu es of approximately 0.01 and 0.99 at 4 and 11 yrs, respectively. Such a model would allow the terms for effect modifica tion by attained age and age at exposure to describe latency functions in the period for which there is empirical data.

The general approach for evaluation of compen sation claims for CLL described in the report “Development of a CLL Risk Model for NIOSH-IR EP” fits well within the approach currently implemented under the EEOICPA. However, work ers would be better served, in terms of fairness and in terms of the soundness of the scientific basis for evaluating CLL claims, by addressing the issues raised above.11 REFERENCES Harris NL, Jaffe ES, Diebold J, et al. World Health Organizati on classification of neoplastic diseases of the hematopoietic and lymphoid tissu es: report of the Clinical Advisory Committee meeting-Airlie House, Virginia, November 1997. [see comment]. Journal of Clinical Oncology 1999;17:3835-49. Richardson DB, Sugiyama H, Wing S, et al. Positive associations between ionizing radiation and lymphoma mortality among men. American journal of epidemiology 2009;169:969-76. Rericha V, Kulich M, Rericha R, et al. Incide nce of leukemia, lymphoma, and multiple myeloma in Czech uranium miners: a case-cohort study. Environmental health perspectives 2006;114:818-
22. Romanenko AY, Finch SC, Hatch M, et al. The Ukrainian-American study of leukemia and related disorders among Chornobyl cleanup worker s from Ukraine: III. Radiation risks. Radiation research 2008;170:711-20. Kesminiene A, Evrard AS, Ivanov VK, et al . Risk of hematological malignancies among Chernobyl liquidators. Radiat ion research 2008;170:721-35. Muirhead CR, O'Hagan JA, Haylock RG, et al. Mortality and cancer incidence following occupational radiation exposure: th ird analysis of the National Re gistry for Radiation Workers. British journal of cancer 2009;100:206-12. Preston DL, Kusumi S, Tomonaga M, et al. Cancer incidence in atomic bomb survivors. Part III. Leukemia, lymphoma and multiple myeloma, 1 950-1987 [published erratum appears in Radiat Res 1994 Jul;139(1):129]. Radia tion research 1994;137:S68-97.