RADIATION RESEARCH 179, 361–382 (2013)0033-7587/13 $15.00
Ó2013 by Radiation Research Society.
All rights of reproduction in any form reserved.
DOI: 10.1667/RR2892.1

The Incidence of Leukemia, Lymphoma and Multiple Myeloma among
Atomic Bomb Survivors: 1950–2001
Wan-Ling Hsu,a Dale L. Preston,b,1 Midori Soda,a Hiromi Sugiyama,a Sachiyo Funamoto,a Kazunori Kodama,a Akiro
Kimura,c Nanao Kamada,d Hiroo Dohy,e Masao Tomonaga,f Masako Iwanaga,g Yasushi Miyazaki,h Harry M.
Cullings,a Akihiko Suyama,a Kotaro Ozasa,a Roy E. Shorea and Kiyohiko MabuchiiaRadiation Effects Research Foundation, Hiroshima and Nagasaki, Japan; b Hirosoft International, Eureka, California; c Department of Hematology
and Oncology, Hiroshima University, Hiroshima, Japan; d Hiroshima A-bomb Survivors Relief Foundation, Hiroshima, Japan; e Hiroshima Red
Cross Hospital and Atomic-Bomb Survivors Hospital, Hiroshima, Japan; f The Japanese Red Cross Nagasaki Genbaku Hospital, Nagasaki, Japan;gGraduate School of Public Health, Teikyo University, Tokyo, Japan; h Department of Hematology, Nagasaki University, Nagasaki, Japan; andi
Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Marylandmodels. The leukemia results indicated that there was anonlinear dose response for leukemias other than chronic
lymphocytic leukemia or adult T-cell leukemia, which variedmarkedly with time and age at exposure, with much of theevidence for this nonlinearity arising from the acute myeloid
leukemia risks. Although the leukemia excess risks generally
declined with attained age or time since exposure, there wasevidence that the radiation-associated excess leukemia risks,
especially for acute myeloid leukemia, had persisted throughout the follow-up period out to 55 years after the bombings.
As in earlier analyses, there was a weak suggestion of aradiation dose response for non-Hodgkin lymphoma amongmen, with no indication of such an effect among women.
There was no evidence of radiation-associated excess risks for
either Hodgkin lymphoma or multiple myeloma. Ó 2013 by

Hsu, W. L., Preston, D. L., Soda, M., Sugiyama, H.,
Funamoto, S., Kodama, K., Kimura, A., Kamada, N., Dohy,
H., Tomonaga, M., Iwanaga, M., Miyazaki, Y., Cullings, H.,
Suyama, A., Ozasa, K., Shore, R. and Mabuchi, K. The
Incidence of Leukemia, Lymphoma and Multiple Myeloma
among Atomic Bomb Survivors: 1950–2001. Radiat. Res. 179,
361–382 (2013).

A marked increase in leukemia risks was the first and moststriking late effect of radiation exposure seen among theHiroshima and Nagasaki atomic bomb survivors. This article
presents analyses of radiation effects on leukemia, lymphoma
and multiple myeloma incidence in the Life Span Study
cohort of atomic bomb survivors updated 14 years since thelast comprehensive report on these malignancies. These
analyses make use of tumor- and leukemia-registry based
incidence data on 113,011 cohort members with 3.6 million
person-years of follow-up from late 1950 through the end of
2001. In addition to a detailed analysis of the excess risk for
all leukemias other than chronic lymphocytic leukemia oradult T-cell leukemia (neither of which appear to beradiation-related), we present results for the major hematopoietic malignancy types: acute lymphoblastic leukemia,
chronic lymphocytic leukemia, acute myeloid leukemia,
chronic myeloid leukemia, adult T-cell leukemia, Hodgkin
and non-Hodgkin lymphoma and multiple myeloma. Poisson
regression methods were used to characterize the shape of theradiation dose-response relationship and, to the extent thedata allowed, to investigate variation in the excess risks withgender, attained age, exposure age and time since exposure.
In contrast to the previous report that focused on describing
excess absolute rates, we considered both excess absolute rate(EAR) and excess relative risk (ERR) models and found that
ERR models can often provide equivalent and sometimes
more parsimonious descriptions of the excess risk than EAR

Radiation Research Society

INTRODUCTION

A radiation-related excess of leukemia in radiologists andphysicians was recognized in the early 1940s (1, 2). By thelate 1940s, physicians in Hiroshima and Nagasaki had
noticed an apparent increase in leukemia incidence among
survivors (particularly children) who were near the
hypocenters at the time of the atomic bombs. The firstpublished report of an increased risk of leukemia among theatomic bomb survivors appeared in 1952 (3). Since then,risks of leukemia and other hematological malignancies
have been the subject of special and continuing interest in
studies of the survivors conducted at the Radiation Effects
Research Foundation (RERF), formerly the Atomic Bomb
Casualty Commission (ABCC).
The latest comprehensive analysis of the incidence ofhematological malignancies in the RERF Life Span Study(LSS) cohort of the atomic bomb survivors (4) consideredradiation effects on all leukemias as a group and on selectedleukemia subtypes for the period from 1950–1987.
Radiation effects on leukemia mortality have been considered in most of the periodic LSS mortality reports andNote. The online version of this article (DOI: 10.1667/RR2892.1)
contains supplementary information that is available to all authorizedusers.
1Address for correspondence: Department of Statistics, Radiation
Effects Research Foundation, 5-2 Hijiyama Koen, Minami-Ku,
Hiroshima 732-0815, Japan; e-mail: preston@hirosoft.net.
361

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HSU ET AL.

reports on dosimetry changes and temporal patterns of risk
(5–7).
Incident cases used in the analyses presented here wereidentified by the Leukemia and Tumor/Tissue Registries in
Hiroshima and Nagasaki with follow-up through the end of
2001, fifty-five years after the bombings and 14 years
beyond that used in the previous comprehensive report.
Analyses are presented for all leukemias other than chronic
lymphocytic leukemia (CLL) or adult T-cell leukemia(ATL) as a group (leukemia other than CLL or ATL) as
well as for major leukemia subtypes [acute myeloid
leukemia (AML), acute lymphoblastic leukemia (ALL),
chronic myeloid leukemia (CML)] and CLL, ATL, nonHodgkin lymphoma (NHL), Hodgkin lymphoma (HL) andmultiple myeloma (MM). In the leukemia analyses herein,
we focus on how the excess risk varies with gender, age at
exposure and attained age or time since exposure, as well as
the characterization of curvature in the leukemia dose
response. In contrast to the previous incidence analyses that
focused solely on excess absolute rates (4), the present
analyses focused on both excess relative risks and excess
rates. A question of particular interest with regard toleukemia was whether or not there were any indications of aradiation-associated increase in risks 30 or more years after
exposure. For lymphomas and MM, where the excess risks,
if any, appear to be considerably lower than those forleukemia, our analyses primarily focused on the evidence
for a statistically significant dose response.
MATERIAL AND METHODS
Study Population and Cohort Follow-up
In the late 1950s, records from the 1950 special national census of
atomic bomb survivors were used by ABCC researchers to establish a
fixed cohort of atomic bomb survivors: the LSS cohort. The LSS
cohort includes 93,741 survivors who were residents of Hiroshima andNagasaki, were present within 10 km of the hypocenters at the time of
the bombs and were alive on October 1, 1950, and 26,580 Hiroshima
and Nagasaki residents who were not in the cities at the time of thebombings. The latter group, which is referred to as the not-in-city(NIC) group, is similar in size and frequency-matched on gender andage at the time of the bombings to survivors in the cohort who were
within 2.5 km of the hypocenters. The present analyses were based on
the 113,011 cohort members for whom dose estimates are available.
Dose estimates are not available for 7,044 cohort members because of
uncertain locations or shielding configurations. Almost 60% of thecohort members are women and 41% were less than 20 years old at thetime of the bombings. As of the end of follow-up for the present
analyses (December 31, 2001), 43% of the cohort members were still
alive. Additional information on the characteristics and history of the
LSS cohort can be found in previously published articles (4–6, 8).
Until recently, it has been customary to exclude the NIC group fromrisk analyses because concerns about possible differences insocioeconomic status or other factors that might affect risk estimates.
However, as in the most recent LSS solid cancer incidence analyses(9), the NIC group was used in this work to augment the information
on variation in baseline rates by gender, attained age and birth cohort,
but not on the overall level of the rates. This was accomplished by the
inclusion of fitted increments associated with a city-specific NIC
indicator in the baseline risk model.

Vital status for individual LSS cohort members is ascertained bylinkage to the national family registration (koseki) system on a 3-year
cycle. Given the comprehensive nature of the koseki system, only 175(,1%) cohort members have been lost to follow-up. Information fromkoseki records is used to trace death certificates, which provide
information on causes of death for those known to have died.
Incidence follow-up began on October 1, 1950. The end of follow-up
is the earliest date of diagnosis of the first primary malignancy (of anytype), the date of death, the date of loss to follow-up or December 31,
2001.
Ascertainment of Hematological Malignancies
Leukemia registry. Two to three years after the atomic bombings ofHiroshima and Nagasaki, a number of physicians in Hiroshima andNagasaki noted a markedly increased rate of leukemia in children
living near the hypocenters (3). Therefore, in the early 1950s, ABCC
researchers together with hematologists in Hiroshima and Nagasakilaunched the Leukemia Registry program to ascertain all potential
cases of leukemia and other hematological malignancies in the twoareas, including cases that occurred in the late 1940s. The Leukemia
Registry remained active until the late 1980s when it was supplantedby the city and prefecture cancer registries. Leukemia Registry data
were the basis for a number of reports on radiation-related risk ofleukemia and related diseases in the survivors (10–15).
The Leukemia Registry also gathered blood smears or otherbiological specimens used for diagnosis, clinical information,
laboratory records and other material relevant to the diagnosis. Thesematerials and information stored at ABCC and later at RERF werereviewed by at least two Leukemia Registry hematologists to develop
a consensus diagnosis. Additional information on the Leukemia
Registry procedures is available elsewhere (4, 16). Accepted cases
were assigned a diagnosis date and the type of malignancy was coded.
In the mid-1980s, the materials collected by the Leukemia Registrywere re-reviewed and 60% of the leukemia diagnoses were classified
using the French-American-British (FAB) classification system (17–20).
Tumor registries. As the Leukemia Registry activities declined in
the mid-1980s, the population-based Tumor Registries, independent of
the Leukemia Registry, became the primary source for ascertaining
leukemias and other hematological malignancies in Hiroshima andNagasaki. The Tumor Registries were established in 1957 inHiroshima and 1958 in Nagasaki (21). The Hiroshima and Nagasaki
Tumor Registries are operated by RERF entrusted by Hiroshima andNagasaki prefectures and cities. Active ascertainment from hospitalrecords in the two cities and their outlying areas is the primary methodof case identification employed by the registries. Furthermore, this issupplemented by linkage to the cause of death information and torecords from the ABCC surgical pathology program, which wassuperseded in the early 1970s by the regional tissue registries. Records
are reviewed by RERF personnel trained in nosology and coded using
the International Classification of Diseases for Oncology (ICD-O)
codes that were current at the time of coding (22).
Assembling the present case series. Incident cases considered forthese analyses were ascertained and assembled from the Leukemia
Registry and the Hiroshima and Nagasaki Tumor Registries using aseries of rules to give precedence to the better information when there
were discrepancies. Since the Leukemia Registry involved detailed
hematology review, precedence was given to the Leukemia Registry
diagnosis if it was at least as detailed as the Tumor Registry diagnosis.
Additional review was carried out for a small number of cases inwhich the Leukemia Registry and Tumor Registry diagnoses appeared
to be inconsistent. More detailed information can be found in (4).
Classification of hematologic malignancies has been modified andrefined over time, particularly for myeloid leukemias. Since most of
the cases in these analyses cannot be classified according to the moredetailed modern classifications and the number of cases of specific363

INCIDENCE OF HEMATOPOIETIC MALIGNANCIES

subtypes tends to be small, we used a broad classification of types forthese analyses that parallels the classification used in earlier reports onrisks for these cancers in the LSS. In particular, cases identified as
aleukemic/subleukemic myeloid leukemias and myeloid leukemia nototherwise specified are included in the AML group. The aleukemic/
subleukemic lymphoid leukemias are combined with ALL. The CLLgroup includes CLL and hairy cell leukemia. ICD-O morphology
codes included in the various analysis groups are given insupplementary Table S1 (http://dx.doi.org/10.1667/RR2892.1.S1)
Organization of the data for analysis. The primary Poisson
regression analyses for this report were based on a highly stratified
tabulation of person-years and case counts. The stratifying factors
were: city, gender, age at exposure (5-year categories to age 69 and 70
and over), attained age (5-year categories from age 5–84 and 85 andover), calendar time period (from October 1, 1950, with subsequentcut points on January 1 of 1953, 1956 and 1958, and every 5 years
from 1961–2001 except for an additional cut-point at 1988 to facilitatecomparison with the previous report), exposure status (,3 km fromthe hypocenter, 3–10 km from the hypocenter and not in a city),
adjusted and truncated weighted (gamma plus 10 times the neutron)bone marrow dose (22 dose categories for survivors), and whether or
not an individual’s shielded kerma estimate was greater than 4 Gy
based on the latest dosimetry system (DS02). The lowest dose
category included people whose DS02 weighted bone marrow dose
estimates were less than 5 mGy. The lower dose bounds (in Gy) for
the subsequent categories were: 0.005, 0.02, 0.04, 0.06, 0.08, 0.10,
0.125, 0.150, 0.175, 0.20, 0.25, 0.30, 0.50, 0.75, 1.0, 1.25, 1.5, 1.75,
2.0, 2.5, and 3.0. As in other LSS incidence reports (4, 9), personyears were adjusted by birth cohort, time period, gender and cityspecific residence probabilities to correct for migration from theTumor Registries’ catchment areas (23). A table with information on
the proportion of person-years lost due to migration is given insupplementary Table S3 (http://dx.doi.org/10.1667/RR2892.1.S2).
The data for each stratum included migration-adjusted person-years,
counts of the number of eligible cases by outcome type, and personyear-weighted mean values of weighted bone marrow dose, attained
age, age at exposure and time since exposure.
Risk Models and Statistical Methods
The previous analyses (4) focused on age at exposure dependent
excess absolute rate (EAR) models in which the radiation dose effectcould vary with time since exposure within age at exposure groups. As
we examined the current data, it became apparent that simpler models
similar to those used for solid cancers (9), in which the excess risk
varies smoothly with age at exposure and time can often describe thedata at least as well as the models used in the previous analyses.
Therefore, we considered both EAR and excess relative risk (ERR)
models in which the excess risk varies with age at exposure and either
attained age or time since exposure. In an EAR model, the disease rate
can be written as:
k0 ðc; s; a; bÞ þ qðdÞea ðc; s; a; bÞ:

descriptions of these models, unless explicitly noted, they are based onlog attained age and log time since exposure. In general, age at
exposure and time since exposure were centered or scaled so that thedose-effect parameters correspond to the risk for a person who was 30
years old at the time of the bombings for incidence 25 (attained age55) or 40 (attained age 70) years after exposure. For some outcomes,
we considered extensions of the effect modification model, including
gender-dependent age at exposure and time effects, interactions
between age at exposure and time, or categorical age at exposure andtime effects.
The dose response functions considered in this report included:
ðaÞ linearqðdÞ ¼ b1 d;

ðbÞ linear  quadraticqðdÞ ¼ b1 d þ b2 d 2 ;ðcÞ pure  quadraticqðdÞ ¼ b2 d2 ;ðdÞ single knot linear spline=threshold modelsqðdÞ ¼ h1 d þ h2 ðd  cÞðd.cÞ;ðeÞ nonparametricqðdÞ ¼ hdcat :b1 and b2 are the linear and quadratic dose-response parameters,
respectively. In a linear-quadratic model, the curvature of the dose
response is defined as the ratio of the quadratic and linear dose effects:
i.e., b2/b1. In the single-knot linear-spline/threshold models, c is a dose
join point and when h1 equals 0 this is a threshold model. In the
nonparametric dose-response model the dose response varies by dose
category without any smoothing (q(d) ¼ hdcat). Although the bonemarrow dose estimates used in all of these analyses were adjusted toallow for the effects of dose uncertainty (24), dose-response models
also included a multiplicative dichotomous factor for those withshielded kerma estimates in excess of 4 Gy to allow for dose
uncertainties not captured by the standard adjustment methods or for
high-dose effects such as cell killing.
Analyses were limited to first primary malignancies diagnosed
during the follow-up period among cohort members with DS02 dose
estimates. Cases that were diagnosed outside of Hiroshima or
Nagasaki prefectures were excluded. Maximum likelihood estimatesof the parameters in these models were computed using the data in the
person-year (PY) table described above. P values and confidence
intervals (CI) for model parameters were based on the profile
likelihood function. Uncertainty in the various risk estimates weresummarized using 95% confidence intervals. The models were fit
using the Epicure risk regression software (25). Akaike information
criteria (AIC) (26) values were used to aid in the comparison ofnonnested models. The models used are described and estimates ofsome of the key parameters are given in the Results section. However,details of the parameterizations used and the parameter estimates forour preferred models are presented in supplementary Table S2 (http://dx.doi.org/10.1667/RR2892.1.S1).

While in the ERR model it is
k0 ðc; s; a; bÞ½1 þ qðdÞer ðc; s; t; eÞ:RESULTS

The term k0(c,s,a,b) is a parametric model for the baseline (zerodose) rates that depends on attained age (a), gender (s), and factors
such as birth cohort (b) and city (c). In the primary dose-responsemodel, q(d)e(c,s,t,e), q(d) describes the shape of the dose response ande(c,s,t,e) describes effect modification associated with the effect ofdose d, i.e., how the level of the radiation-related excess risk varies
with city (c), gender (s), age at exposure (e) and time (t), where time
can be functions of either time since exposure or attained age. For thisreport (as in most analyses of the LSS data) effect modification was
described using log-linear functions of the variables of interest. In

A total of 1,215 hematological malignancies wereidentified among 113,011 LSS cohort members and 944
of these cases were eligible for inclusion in the analyses
between 1950 and the end of 2001. Almost 40% of theeligible hematopoietic malignancies were diagnosed after
the end of the follow-up (1987) used in the lastcomprehensive analyses of the LSS data (4). Table 1
provides a summary of the numbers of cases eligible for364

HSU ET AL.

TABLE 1
Eligible and Ineligible Cases by Exclusion Reason
Ineligible
Malignancy

EligibleNot first primary

Nonresident

Unknown dose

Before 10/1/1950

Total

Leukemia
Leukemia other than CLL or ATL
Acute myeloid (AML)zChronic myeloid (CML)
Acute lymphoblastic (ALL)§
Other
Chronic lymphocytic (CLL)
Adult T-cell (ATL)
Any leukemia

312
176
75
43
18
12
47
371

28
20
3
4
1
4
3
35

31
13
5
9
4
0
7
38

36
18
11
4
3
0
2
38

9
2
5
2
0
0
0
9

416
229
99
62
26
16
59
491

Lymphoma and Myeloma
Non-Hodgkin lymphoma (NHL)Hodgkin lymphoma (HL)
Multiple myeloma (MM)
Total

402
35
136
944

34
1
26
96

33
4
10
85

27
1
9
75

5
1
0
15

501
42
181
1,215

Residing outside of Hiroshima or Nagasaki prefectures at the time of diagnosis.
Includes acute myeloid leukemia (146 eligible cases) as well as acute monocytic leukemia (10 eligible cases), a-/sub-leukemic myeloid
leukemia (16 eligible cases) and myeloid leukemia NOS (4 eligible cases).
§
Includes 41 cases classified as acute lymphoblastic leukemia (41 cases) and 2 cases classified as aleukemia/subleukemic lymphoid leukemia.
Includes 10 cases classified as chronic lymphocytic leukemia and 2 as hairy cell leukemia.
zdose-response analyses by type of malignancy together withinformation on the reasons why cases were deemed
ineligible. About 40% of the cases were leukemias, another
40% were identified as NHL and almost 15% were MM.
Hodgkin lymphoma was uncommon. Almost half of theleukemia cases were classified as AML, 20% were CML
and about 12% were ALL. All but five of 47 ATL cases
were diagnosed in Nagasaki and constitute almost 40% of
all of the Nagasaki leukemia cases. As with otherpopulations in Japan, the incidence of CLL is remarkably
low. All except 3 of 18 cases in the other leukemia groupwere diagnosed in Hiroshima. Eleven of the cases in thisgroup were classified as acute leukemia not otherwise
specified (NOS) and other specific types of leukemia while
7 were classified as aleukemia, subleukemia or leukemia
NOS. The cases in this group were included in the leukemia
other than the CLL or ATL analyses discussed below but
were not analyzed separately. The crude rates for leukemia,
lymphoma and multiple myeloma by age at exposure,period and dose category are given in supplementary Tables
S4 and S5 (http://dx.doi.org/10.1667/RR2892.1.S2).
Leukemia Other Than CLL or ATL

While a few studies suggest that CLL risk may be affectedby radiation exposure (27–30), a number of others do not(31, 32). It is generally believed that radiation has little
effect on CLL rates and it is common practice in studies ofradiation effects to focus on the risk of leukemia other than
CLL. In view of the unusual nature of ATL incidence, we
also excluded ATL from the pooled leukemia analyses. A
total of 312 cases of leukemia other than CLL or ATL wereused in these analyses (Table 1).

Baseline rates for this outcome were described reasonably
well by a model in which the rates increased in proportion
to age. This simple pattern was significantly improved (P ,0.001) by allowing the power to increase with increasing
attained age (i.e., by adding a quadratic term in log attainedage). The nature of the increase with attained age did not
differ significantly by gender (P . 0.5), nor did it appear tovary significantly with birth cohort (P ¼ 0.30). However, at
any given age the risk for women was about half that formen (female:male ratio 0.50 95% CI 0.40–0.63). Baseline
rates in Nagasaki were 35% lower than in Hiroshima (P ¼
0.004). There was a significant (P , 0.001) nonlinear birthcohort effect with the highest age-specific rates for thoseborn around 1920, which decreased by about 30% for
people born 20 years earlier or later than this—a patternsimilar to that seen in the Japanese national leukemia
mortality rates (33). The fitted age-specific baseline rateestimates for three birth cohorts are shown in Fig. 1a. The
baseline rate model and parameter estimates for leukemias
other than CLL or ATL are given in supplementary Table
S2 (http://dx.doi.org/10.1667/RR2892.1.S1).
Dose response and effect modification. Using a simple
time-constant linear ERR model with no effect modification, there was a statistically significant (P , 0.001) doseresponse relationship. Allowing for attained age and timesince exposure effects (discussed below), a concave upward
linear-quadratic (LQ) model described the data significantly
better than either a linear dose response (P ¼ 0.001) or purequadratic (P ¼ 0.04) dose-response model. The estimatedlinear dose effect in the LQ ERR model at attained age 70
after exposure at age 30 was 0.79 per Gy and the estimatedcurvature was 1.20, as given in Table 3. Figure 1b illustrates
the fitted dose response together with dose-category-INCIDENCE OF HEMATOPOIETIC MALIGNANCIES

365

FIG. 1. Summaries of the risk of leukemia other than CLL or ATL in the LSS. Plot (panel a) shows age-specific baseline (zero dose) rates in
Hiroshima for men (black lines) and women (gray lines) for LSS cohort members born in 1895 (dash-dot line; age at exposure 50), 1915 (dashline; age at exposure 30) and 1935 (solid line; age at exposure 10). Panel b: illustrates the radiation dose response based on the ERR model withrisks standardized to attained age 70 for a person exposed at age 30 (born in 1915). The solid-black line illustrates the fitted linear-quadratic dose
response. The points are based on a nonparametric dose-response model, while the middle-dashed-gray line is a smoothed version of the dose
category-specific estimates from the nonparametric fit. The upper- and lower-dashed-gray line are plus and minus one standard error from thesmoothed fit. Panels c and d: illustrate the temporal pattern and age-at-exposure effects for our preferred ERR model. The fitted ERR did notdepend on either gender or city. Panels e and f: present the temporal pattern and age-at-exposure effects for Hiroshima males based on thepreferred EAR model. The points in panels c–f are nonparametric estimates for exposure at age 10.

specific standardized ERR estimates and a dose-response
function defined by smoothing the category-specificstandardized estimates.
Based on our preferred ERR model (described below), it
was estimated that about 94.1 of the 312 cases of leukemia
other than CLL or ATL used in these analyses wereassociated with the radiation exposure (Table 2). The
radiation-associated excess cases account for about 49% of
the 192 cases among cohort members with doses in excess
of 5 mGy.

Parameter estimates and confidence intervals for the
preferred model for leukemia other than CLL or ATL aregiven in Table 3. The ERR was found to depend jointly on
log attained age (P , 0.001) and either age at exposure (P ¼
0.01) or time since exposure (P ¼ 0.003). These two models(age and age at exposure or age and time since exposure)
led to similar patterns of the excess risk. However, since thefit of the age and time since exposure model (AIC ¼
2431.89) was somewhat better than that for the age and age
at exposure model (AIC ¼ 2433.97), our preferred model

366

HSU ET AL.

TABLE 2
Observed and Fitted Cases of Leukemia Other than CLL or ATL by Weighted Bone Marrow Dose Categories
Fitted cases
Dose (Gy)

Person years

Mean dose (Gy)

Observed cases

Background

Excess,0.005
–0.1
–0.2
–0.5
–1
–2
2þ
Total

2,039,093
957,889
201,935
206,749
117,855
64,122
25,761
3,613,404

0.0006
0.03
0.14
0.32
0.71
1.37
2.68
0.10

120
63
16
25
24
35
29
312

116.9
60.7
13.7
13.6
7.5
4.0
1.5
217.9

0.1
3.6
4.1
11.1
18.2
28.4
28.6
94.1

Estimates based on the preferred ERR linear-quadratic model described in the text and Table 3 with additional details in supplementary Table
S2 (http://dx.doi.org/10.1667/RR2892.1.S1).

includes age and time since exposure as effect modifiers. As
indicated in the upper portion of Table 3, with both of these
temporal factors in the model, the decrease in the ERR withincreasing attained age was proportional to attained age tothe power 1.09 and simultaneously proportional to timesince exposure to the power 0.81. The model predictedthat the highest ERRs were seen shortly after exposure
among those exposed early in life (Fig. 1d). However, due
to the rapid decline in the ERR with time, at any given
attained age the ERR was greater for those who were
exposed at older ages (Fig. 1c). There was no indication that
the ERR varied significantly with gender (P ¼ 0.29) or city
(P ¼ 0.42), nor did it appear that the dose-response
curvature varied with city (P . 0.5). The precise form of
this model is indicated in supplementary Table S2 (http://dx.
doi.org/10.1667/RR2892.1.S1) and information on the fit ofalternative models is given in supplementary Table S6(http://dx.doi.org/10.1667/RR2892.1.S2).
The excess absolute rates for leukemia other than CLL or
ATL could also be described by a linear-quadratic EAR
model in which the radiation-associated excess ratedepended on attained age (P , 0.001), age at exposure (P, 0.001) and city (P ¼ 0.03), with a suggestion of astatistically significant gender difference (P ¼ 0.08). ThisEAR model (AIC ¼ 2433.2) describes the data slightly
worse than the preferred ERR model discussed above. An
EAR model with log-time since exposure and age-atexposure effects (AIC ¼ 2,438.8) fit worse than thepreferred attained age and age-at-exposure model. Adding
attained age to this time-since-exposure model led to astatistically significant improvement in fit (P ,0.001). The
resulting model was virtually identical to the attained-age
model. Thus, attained age with an age-at-exposure effectprovided a better description of the temporal variation of
EAR than did attained age with a time-since-exposure
effect.
In our preferred EAR model (Table 3 and supplementary
Table S6: http://dx.doi.org/10.1667/RR2892.1.S2), the linear dose coefficient estimates (standardized to age 70 after
exposure at age 30) in Hiroshima were 1.06 excess cases per
10,000 PY per Gy for men and 0.7 for women withestimated curvature similar to the ERR model. The decrease

TABLE 3Preferred Model, Excess Risk Parameter Estimates for Leukemia Other than CLL or ATL
Dose coefficients (at 1 Gy)
Risk model
ERR
EARz
Women
Men

LinearQuadratic

Curvature

0.79(0.03, 1.93)

0.95(0.34, 1.80)

1.20(0.23, 49.35)

0.70(0.13, 1.53)
1.06(0.16, 2.42)

0.71(0.24, 1.41)
1.09(0.37, 2.13)

1.03(0.20, 8.52)

Gender ratio( F:M)

0.66(0.41, 1.04)

City ratio
(N:H)

0.52
(0.26, 0.93)

Attained age(power)Time since
exposure (power)

1.09(2.01, 0.27)

0.81(1.31, 0.28)

1.45(2.13, 0.80)

Age atexposure

0.41(0.2, 0.64)

The preferred ERR model is linear quadratic in dose with log-linear effect modification depending on log (attained age) and log (time since
exposure). The baseline model parameters and explicit details about the dose effect modification term are given in supplementary Table S2 (http://dx.doi.org/10.1667/RR2892.1.S1). Supplementary Table S6 (http://dx.doi.org/10.1667/RR2892.1.S2) presents information on other ERR models.
The dose coefficients describe the ERR at 1 Gy at age 70 after exposure at age 30.
z
The preferred EAR model is linear-quadratic in dose with log-linear effect modification depending on log (attained age) and age at exposure.
The baseline model parameters and explicit details about the dose effect modification term is given in supplementary Table S2 (http://dx.doi.org/
10.1667/RR2892.1.S1). Supplementary Table S6 (http://dx.doi.org/10.1667/RR2892.1.S2) presents information on other EAR models. The dosecoefficients describe the excess cases per 10,000 person years at 1 Gy at age 70 after exposure at age 30.

367

INCIDENCE OF HEMATOPOIETIC MALIGNANCIESTABLE 4
Observed and Fitted Excess Cases of Leukemia Other than CLL or ATL by Time Period and Age at Exposure with CategorySpecific ERR Estimates
Age at exposure
0–19

20–39

PeriodObs

Exc

1950–1955
1956–1959
1960–19691970–1979
1980–1989
1990–2001
Total
ERRz (95% CI)

18
16.2
17
5.4
14
6.3
11
4.7
17
4.4
29
4.3
106
41.3
6.5 (4.0 to 10.3)

Obs

40þ
Exc

11
6.5
4
4.1
17
6.5
33
5.3
25
4.3
32
3.0
122
29.7
3.9 (2.3 to 6.1)

Obs

Total
Exc

13
7.6
18
4.7
19
6.0
18
3.2
12
1.3
4
0.3
84
23.1
4.0 (2.1 to 6.9)

Obs

Exc

42
30.3
39
14.2
50
18.8
62
13.2
54
9.9
65
7.6
312
94.0
4.7 (3.3 to 6.5)

ERRz (95%CI)
15.2
13.3
4.8
3.4
1.8
2.1

(8.8 to 25)(7.2 to 23)(2.3 to 8.4)
(1.5 to 6.3)
(0.5 to 3.8)
(0.8 to 4.3)

Excess cases based on preferred ERR model described in the text and Table 3 with additional details in supplementary Table S2 (http://dx.doi.
org/10.1667/RR2892.1.S1).
z
ERR at 1 Gy for a linear dose response model with categorical period or age at exposure effects.

in the EAR with attained age was proportional to age to thepower 1.45, while the EARs for a given attained age were
estimated to increase by about 51% per decade increase in
age at exposure (95% CI 23–89%). Excess rates for
Nagasaki survivors were estimated to be about 52% of
those for Hiroshima survivors of the same gender andexposure age, and excess rate estimates for women wereabout 66% of those for men. The variation in the fitted EAR
estimates with attained age and time since exposure forvarious ages at exposure are shown in Fig. 1e and f,
respectively.
We used a simple ERR model with categorical main
effects for six time periods and three age-at-exposure groups
to examine whether or not the risks had persisted throughout
the follow-up period. As indicated by the results summarized in Table 4, there was evidence of statisticallysignificant increased risks in each of the six time periods
considered. The largest ERRs were seen for the two earlier
periods. However, even for the last 12 years of follow-up(1990–2001 or 45–55 years after exposure), the radiationassociated leukemia risk at 1 Gy was estimated to be twice
the baseline risk.
Acute Myeloid Leukemia (AML)

There were 176 eligible AML cases, including 42 cases
diagnosed after 1987 among LSS cohort members who werein the cities at the time of the bombings and 15 cases amongcohort members who were NIC at the time of the bombings.
As indicated in Fig. 2a, AML baseline rates increased
with attained age, but the level of risk and the nature of theincrease with age differed for men and for women (P ,0.001). Baseline rates for women were about 40% (95% CI
29–56%) of those for men, and the rate of increase withattained age was more rapid for men than for women (P ¼
0.04). The baseline rates also exhibited a complex birthcohort effect. Age-specific rates were larger for people born
between 1915 and 1925 than for people born before or after

this period (P , 0.001). This pattern is similar to that seenin the Japanese national leukemia mortality rates, butsomewhat more pronounced in the LSS cohort. The baseline
AML rates in Nagasaki were 25% lower, though notsignificantly lower (P ¼ 0.14), than those in Hiroshima. The
AML baseline rate model and parameter estimates are given
in supplementary Table S2 (http://dx.doi.org/10.1667/
RR2892.1.S1).
Dose response and effect modification. There was strong
evidence for a radiation dose-response relationship (P ,0.001). As shown in Fig. 2B, the dose-response curve wasconcave upward (P ¼ 0.01). A pure-quadratic model with anestimated ERR at 1 Gy of 1.11 (95% CI 0.53–2.08,
standardized to age 70 after exposure at age 30) as shown in
Table 6 described the data as well as a linear-quadraticmodel (P . 0.5). Inference about effect modification in the
ERR and EAR was based on a pure-quadratic model. In our
preferred AML models (described below), the number ofradiation-associated cases was estimated to be 37.4 (Table5). The fraction attributable to radiation was 38% amongcohort members with doses in excess of 5 mGy.
ERRs for AML exhibited a statistically significant [P ¼0.004, with 2 degrees of freedom (df)] non-monotone
dependence on age at exposure. As suggested in Fig. 2c, for
any attained age (after exposure), the ERR for the people
exposed around age 30 tended to be lower than for those
exposed later or younger in life. The decrease in the ERR
with attained age (AIC ¼ 1,552.14) was well described as
proportional to age to the power 0.89 (Table 6). Morecomplex patterns for the age/time dependence were also
considered. Neither the addition of a quadratic term in log
age nor the use of splines in log age significantly improved
the fit, nor did the use of functions of time since exposure
result in better fits (P . 0.5 in every case). There was no
indication of an attained age by age-at-exposure interaction(P . 0.5), nor did the attained age or age-at-exposure
effects appear to vary with gender (P . 0.5). Parameter
estimates with confidence intervals for the preferred AML,

368

HSU ET AL.

FIG. 2. LSS acute myeloid leukemia risk summary plots. Panel a: shows age-specific rates in the Hiroshima baseline (zero dose) for men (blacklines) and women (gray lines) for LSS cohort members born in 1895 (dash-dot line; age at exposure 50), 1915 (dash line; age at exposure 30) and1935 (solid line; age at exposure 10). Panel b: illustrates the radiation dose response based on the preferred ERR model with risks standardized toattained age 70 for a person exposed at age 30 (born in 1915). The solid-black line illustrates the fitted pure-quadratic dose response. The points
are based on a nonparametric dose-response model, while the middle-dashed-gray line is a smoothed version of the dose category-specificestimates from the non-parametric fit. The upper- and lower-dashed-gray lines are plus and minus one standard error from the smoothed fit. Panelsc and d: illustrate the temporal pattern and age-at-exposure effects for our preferred ERR model. Panels e and d: present the temporal pattern andage-at-exposure effects for Hiroshima males based on the preferred EAR model. Black lines are shown for ages at exposure of 10 (solid line), 30(dash line) and 50 years (dash-dot line). The gray lines are the EAR temporal patterns using the model specified in a previous report (4). For the
ERR and EAR models shown here, the excess risks did not depend on either gender or city.

ERR and EAR models are given in Table 6. Additionally,
the precise form of this model is given in supplementary
Table S2 (http://dx.doi.org/10.1667/RR2892.1.S1) and information on the fit of alternative models is given insupplementary Table S7 (http://dx.doi.org/10.1667/
RR2892.1.S2).
The AML EAR was also described equally well (AIC ¼
1,550.0) using a model with a linear-quadratic effect in log
attained age. This description of the temporal pattern of the

AML, which is illustrated in Fig. 2e, is considerably simpler
than the model used in the previous LSS leukemia incidence
report (4). In that model, there were separate temporal
patterns for each of three age-at-exposure groups, while allof the temporal variation excess rates in the current modelare expressed in terms of age without the need for
dependence on either age at exposure or time since
exposure. Figure 2e and f shows the variation of the AML
EAR with attained age and time since exposure based on the369

INCIDENCE OF HEMATOPOIETIC MALIGNANCIESTABLE 5Observed and Fitted Background and Excess Cases of Acute
Myeloid Leukemia by Weighted Bone Marrow Dose Category
Fitted cases

Dose (Gy)

Personyears

Observedcases

Background

Excess,0.005
–0.1
–0.2
–0.5
–1
–2
2þ
Total

2,039,093
957,889
201,935
206,749
117,855
64,122
25,761
3,613,404

77
36
9
12
11
18
13
176

75.6
37.7
8.2
8.4
4.9
2.8
1.0
138.6

0.0
0.2
0.6
2.7
6.9
14.0
13.0
37.4

Estimates based on the preferred quadratic ERR model describedin the text and Table 6 with additional details in supplementary Table
S2 (http://dx.doi.org/10.1667/RR2892.1.S1).

current model together with using lighter lines, the patternfrom an EAR model of the form used in the 1994 report.
The new model predicts somewhat lower excess rates
shortly after the bombings for those exposed as children,and somewhat higher rates throughout the follow-up for
those exposed at age 50.
The fitted models illustrated in Fig. 2f reveal an upward
trend in the AML excess rates in recent years, suggestingthat excess risks have persisted throughout the entire followup period. Categorical analyses based on a simple modelwith main effects for three age-at-exposure and six period
effects were used to assess the persistence of the risk. As
seen in Table 7, there was evidence of increased risks in thelast 12 years of follow-up with a significantly elevated ERR
at 1 Gy of 1.5, representing about 6 excess cases during thisperiod.
Acute Lymphoblastic Leukemia (ALL)

There were 43 eligible ALL cases. This relatively small
number of cases, coupled with a large proportion (about
half, described below) being associated with radiation
exposure, makes it difficult to make precise inferences
about the baseline rates. However, it appeared that ALL

baseline rates increased with attained age (P ¼ 0.01). This
increase was estimated to be proportional to attained age tothe power 1.70 (95% CI 0.34–3.36) (supplementary Table
S2; http://dx.doi.org/10.1667/RR2892.1.S1), and allowing
for more complex age patterns did not improve the fit.
Population data for Japan and other countries (34) suggestthat ALL baseline rates have a U-shaped pattern in which
the rates reach a minimum in the 30–40 age range andincrease at older ages. We did not find evidence for such apattern in our data, most likely reflects the limited power
due to the small number of cases in the cohort. There was noevidence of gender differences in either the level of risk (P. 0.5) or the age pattern (P . 0.5), nor were there any
indications of a trend in the baseline rates with birth cohort(P ¼ 0.17) or of city differences (P ¼ 0.43). Figure 3aillustrates how the fitted baseline ALL rates vary withattained age. The ALL baseline rate model and parameter
estimates are given in supplementary Table S2 (http://dx.
doi.org/10.1667/RR2892.1.S1).
Dose response and effect modification. There was asignificant linear dose-response relationship (P , 0.001)
with some indication of upward curvature (P ¼ 0.05), muchof which was influenced by 4 cases with unweighted
shielded kerma estimates in excess of 4 Gy. After adjustingfor the high-dose cases by including a dichotomousindicator, there was no evidence of significant curvature(P ¼ 0.13). Figure 3b shows the estimated linear dose
response. In our preferred ALL model (described below),
the number of radiation-associated ALL cases was estimated to be 21.6 (Table 8). About 67% of the cases amongcohort members with doses in excess of 5 mGy wereassociated with radiation exposure.
The ERR for ALL decreased markedly over time (P ,0.001). This decrease was described as proportional toattained age to the power 3.51 (Table 9). The ERR for
women was about 40% of that for men. This gender- andattained-age-dependent ERR model (AIC ¼ 496.4) described the data better than a model that included joint
effects of age at exposure (higher for younger ages) andtime since exposure (decreasing with time) (AIC ¼ 502.7).
As illustrated in Fig. 3c, this model predicted extremely

TABLE 6Preferred Model, Excess Risk Parameter Estimates for Acute Myeloid Leukemia
Attained age
Risk model
ERR
EARz

Quadratic dose coefficient (at 1 Gy)

Linear

1.11 (0.53, 2.08)
1.59 (0.95, 2.41)–0.89 (2.29, 0.41)
2.59 (0.90,4.26)

Age at exposure
Quadratic

LinearQuadratic

0.17 (0.15, 0.50)

0.25 (0.09, 0.41)

1.43 (0.44, 2.32 )The preferred ERR model is quadratic in dose with log-linear effect modification depending on log(attained age) and a linear-quadratic
function of age at exposure. The baseline model parameters and explicit details about the dose effect modification term are given in supplementary
Table S2 (http://dx.doi.org/10.1667/RR2892.1.S1). Supplementary Table S7 (http://dx.doi.org/10.1667/RR2892.1.S2) presents information on
alternative ERR models. The dose coefficients describe the ERR at 1 Gy at age 70 after exposure at age 30.
z
The preferred EAR model is quadratic in dose with log-linear effect modification depending on a linear-quadratic function of log(attainedage). The baseline model parameters and explicit details about the dose effect modification term is given in supplementary Table S2 (http://dx.doi.
org/10.1667/RR2892.1.S1). Supplementary Table S7 (http://dx.doi.org/10.1667/RR2892.1.S2) presents information on alternative EAR models.
The dose coefficients describe the excess cases per 10,000 person years at 1 Gy at age 70.

370

HSU ET AL.

TABLE 7
Observed and Fitted Excess Cases of Acute Myeloid Leukemia by Time Period and Age at Exposure with Category-Specific ERR
Estimates
Age at exposure
0–19

20–39

PeriodObs

Exc

1950–1955
1956–1959
1960–19691970–1979
1980–1989
1990–2001
Total
ERRz (95% CI)

4
3.1
7
1.3
7
2.1
7
2.3
12
3.0
19
3.9
56
15.7
2.3 (1.0 to 4.5)

Obs

40þ
Exc

3
0.7
3
0.7
7
1.7
21
2.1
20
2.2
23
1.9
77
93
2.0 (0.9 to 3.8)

Obs

Total
Exc

4
2.5
8
2.2
10
3.9
13
2.4
7
1.1
1
0.3
43
12.2
3.4 (1.5 to 6.6)

Obs

Exc

11
6.4
18
4.2
24
7.7
41
6.8
39
6.3
43
6.1
176
37.4
2.4 (1.5 to 3.7)

ERRz (95%CI)
3.6
9.0
3.1
1.9
1.8
1.5

(0.7 to 10.2)(3.5 to 19.2)(1.1 to 6.7)
(0.4 to 4.7)
(0.6 to 4.0)
(0.4 to 3.4)

Excess cases based on preferred ERR model described in the text and Table 6 with additional details in supplementary Table S2 (http://dx.doi.
org/10.1667/RR2892.1.S1).
z
ERR at 1 Gy for a quadratic dose response model with categorical period and age-at-exposure effects.

large ERRs for those exposed as children. Virtually all of
the 22 cases among those exposed before age 20 could be
attributed to radiation exposure.
The radiation effect on the ALL risk could be described
equally well (AIC ¼ 496.4) using an EAR model, as
illustrated in Fig. 3e. In our preferred EAR model, theexcess rate decreased in proportion to age to the power
1.81 (Table 9). There was a significant gender difference(P ¼ 0.05) with an estimated female:male EAR ratio of 0.40.
The gender-averaged EAR at age 70 was 0.16 radiationassociated cases per 10,000 person years per Gy (95% CI
0.05– 0.38). Parameter estimates with confidence intervals
for the preferred ALL ERR and EAR models are given in
Table 9. The precise form of this model is given insupplementary Table S2 (http://dx.doi.org/10.1667/
RR2892.1.S1) and information on the fit of alternativemodels is given in supplementary Table S8 (http://dx.doi.
org/10.1667/RR2892.1.S2). The ALL EAR could be
described almost as well using a combination of age-atexposure and time-since-exposure effects in place of theattained age effect (supplementary Table S8; http://dx.doi.
org/10.1667/RR2892.1.S2).
Both the ERR and EAR results indicated that theradiation-associated risks have decreased over time, butalso suggested that dose-related increased risks may persist
for many years after exposure. Using a simple ERR model inwhich the dose response was allowed to differ for the three
periods of October 1950 through December 1952, 1953–
1965 and 1966–2001, we found statistically significant
dose-related increases in the risk for each period. Although
the ERR decreased over time, the ERR for the last period
was statistically significant and had a population average 3.1(95% CI 0.6–10.4, P ¼ 0.001) (results not shown).
Chronic Myeloid Leukemia (CML)

There were 75 eligible CML cases (63 in Hiroshima, 12 inNagasaki) including 13 cases that occurred after 1987. The

CML baseline rate increased with attained age (P , 0.001)
with a significant difference in the age pattern for men andwomen (P ¼ 0.004) (Fig 4a). Baseline rates for men werehigher than those for women prior to age 75, but women
had higher rates later in life, because the rates for womenrose more rapidly than those for men. There was no
indication of a birth cohort effect (P . 0.5). After allowing
for a city difference in the dose response (described below),the baseline rates did not differ significantly by city (P .
0.5). The CML baseline rate model and parameter estimatesare given in supplementary Table S2 (http://dx.doi.org/10.
1667/RR2892.1.S1).
Dose response and effect modification. CML rates
exhibited a statistically significant (P , 0.001) linear doseresponse relationship that was not improved by the additionof a quadratic term (P . 0.5). The dose-response curve isshown in Fig. 4b. In our preferred ERR model for CML, theERR was dependent on city and both time since exposureand attained age. As shown in Table 11, the estimated ERR
was 5.24 per Gy standardized to attained age 55 and 25 years
after exposure, and the ERR in Nagasaki was estimated to be
22% of that in Hiroshima (P ¼0.01). There was no indicationthat the ERR differed by gender (P . 0.5).
The ERR decreased significantly in proportion to timesince exposure to the power 1.59 at any attained age. The
ERR decreased significantly in proportion to attained age tothe power 1.42. Using the preferred ERR model theobserved number of radiation-associated cases was estimated to be 33.4 with the attributable fraction among those
exposed to 5 mGy or more estimated to be 64% (Table 10).
Parameter estimates with confidence intervals for the
preferred CML ERR and EAR models are given in Table
11, respectively. The precise form of this model is given insupplementary Table S2 (http://dx.doi.org/10.1667/
RR2892.1.S1). Figure 4c and d illustrate the temporal
pattern for the Hiroshima ERR for this model as a functionINCIDENCE OF HEMATOPOIETIC MALIGNANCIES

371

FIG. 3. LSS acute lymphoblastic leukemia risk summary plots. Panel a: shows age-specific Hiroshima baseline rate for LSS cohort members.
Panel b: illustrates the radiation dose response based on the ERR model with gender average risks standardized to attained age 70. The solid-blackline illustrates the fitted linear dose response. The points are based on a nonparametric dose response model, while the middle-dashed-gray line is asmoothed version of the dose category-specific estimates from the nonparametric fit. The upper- and lower-dashed-gray lines are plus and minus
one standard error from the smoothed fit. Panels c and d: exhibit the temporal patterns for men (black line) and for women (gray line) in either city
based on the preferred ERR model. Plots (e) and (f) present the temporal pattern for males (black) and females (gray) based on the preferred EAR
model. In panels e and f: different line patterns are shown for ages at exposure of 10 (solid line), 30 (dash line) and 50 years (dash-dot line).

of attained age and time since exposure for exposure ages of
10, 30 and 50 years, respectively.
A model in which the ERR varied jointly with age at
exposure, time since exposure and city (AIC ¼ 777.7)
described the data as well as the attained age, time since
exposure and city model described above (AIC ¼ 776.4).
However, a model in which the ERR varied with attained
age, age at exposure and city fit less well (AIC ¼ 782.0).
Parameter estimates and AIC values for these and otheralternative models for the CML excess risk are given insupplementary Table S9 (http://dx.doi.org/10.1667/
RR2892.1.S2).
In our preferred EAR model, the excess rate depended
on city, time since exposure and a gender-dependentattained age effect. The gender-averaged EAR at age 55
after exposure at age 30 was 0.62 cases per 10,000 PY perGy (95% CI 0.27–1.15). Excess rates for Nagasaki wereabout 23% of those in Hiroshima (P ¼ 0.01). Figure 4e andf show the CML EAR temporal trends by gender anddifferent age-at-exposure groups based on the preferred
EAR model. For a given age at exposure, the decrease in
the EAR was proportional to time since exposure to thepower 1.63 (P , 0.001). The attained age effect differedsignificantly for men and women (P ¼ 0.01). For any given
time since exposure, the EAR for men exhibited little
variation with attained age, decreasing in proportion toattained age to the power 0.20 (P . 0.5). Conversely, forwomen the EAR increased significantly (P ¼ 0.009) with

372

HSU ET AL.

TABLE 8Observed and Fitted Background and Excess Cases of Acute
Lymphoblastic Leukemia by Weighted Bone Marrow Dose
Category
Dose (Gy)

Person years

Observedcases,0.005
–0.1
–0.2
–0.5
–1
–2
2þ
Total

2,039,093
957,889
201,935
206,749
117,855
64,122
25,761
3,613,404

11
8
4
2
5
5
8
43

Fitted cases
Background

Excess

12.0
5.7
1.2
1.3
0.7
0.4
0.1
21.4

0.06
1.6
1.6
3.4
4.0
4.5
6.4
21.6

Estimates based on the preferred linear ERR model described in
the text and Table 9 with more details in supplementary Table S2(http://dx.doi.org/10.1667/RR2892.1.S1).

increasing attained age. This increase was proportional toattained age to the power 2.10. The preferred EAR (AIC ¼
779.7) and ERR model (AIC ¼ 776.4) described the data
about equally well.
Joint Analysis of AML, ALL and CML Dose Response

The results described provide clear evidence of a timevarying radiation dose response for AML, ALL and CML.
As noted in the text and illustrated in Figs. 2, 3 and 4, thetemporal patterns and shapes of the dose response appear todiffer for these three broad leukemia subgroups. We carriedout a joint analysis using the methods described in refs. (4)and (35) to formally examine the evidence for differences in
the nature of the temporal patterns and shapes of the dose
response for these three subgroups.
When the subgroups are fit with group-specific baseline
rates and the linear-quadratic ERR model developed for all
leukemias other than CLL or ATL (‘‘common model’’), theAIC was 2,848.8. This is considerably larger than the AIC
of 2,825.0 obtained using the preferred subgroup-specificmodels described above. For EAR models, the AIC using
the common EAR model was 2,858.1, while the AIC basedon the preferred subgroup-specific EAR models was
2,827.5. Although a formal test of statistical significanceis not possible, based on a comparison of the differences
between the AICs for the common and group-specificmodels, there is a clear indication of subgroup differences
for both the ERR and EAR models.
In the ERR model, there is evidence of significant
heterogeneity relative to the common model with regard tovariation in the risk with attained age (P ¼ 0.01), time since
exposure (P ¼ 0.004) and city (P ¼ 0.03). When the effectmodification was allowed to have the form of the preferredmodel in each subgroup, there was little evidence ofsignificant inter-subgroup variability in the dose-response
curvature (P ¼ 0.14).
Test for heterogeneity in EAR effect modification relative
to the common EAR model indicates some evidence ofheterogeneity with regard to gender (P ¼ 0.04). Afterallowing for gender variation, there is evidence of heterogeneity with regard to time-since-exposure (P ¼ 0.01) or ageat-exposure (P ¼ 0.04) effects. As with the ERR model, there
was little evidence of significant inter-subgroup variability inthe dose-response curvature (P ¼ 0.17).
Table 12 contains estimates of the possible number ofradiation-associated excess cases by time period (for all ageat-exposure groups together) based on the preferred ERR
models for AML, ALL and CML. The largest number ofexcess cases was seen during the first 5 years of follow-up.
Table 12 also provides information on the within-period
distribution of the excess over the three subtypes consideredhere. It can be seen that, while most of the excess cases in
the 1950–1955 period are CML, as time has gone on AML
has come to account for most of the excess.
Chronic Lymphocytic Leukemia (CLL)

CLL is rare in Japan. In the previous report, there were
only four CLL cases, which were analyzed with the otherleukemias. With additional follow-up time, 12 CLL cases

TABLE 9Preferred Model, Excess Risk Parameter Estimates for Acute Lymphoblastic Leukemia
Risk modelLinear dose coefficient (at 1 Gy)

Gender ratio (F:M)

Attained age (power)

ERR Female
Male
EARz Female
Male

0.95 (0.23, 3.37)
2.40 (0.63, 7.90)
0.09 (0.03, 0.25)
0.23 (0.07, 0.58)

0.40 (0.14, 0.99)–3.51 (5.29, 1.92)

0.40 (0.14, 0.99)–1.81 (2.56, 1.08)

The preferred ERR model is linear in dose with log-linear effect modification depending on log (attained age) and gender. The baseline model
parameters and explicit details about the dose effect modification term are given in Table S2 in the supplementary material (http://dx.doi.org/10.
1667/RR2892.1.S1). Supplementary Table S8 (http://dx.doi.org/10.1667/RR2892.1.S2) presents information on alternative ERR models. The
dose coefficients describe the ERR at 1 Gy at age 70.
z
The preferred EAR model is linear in dose with log-linear effect modification depending on log (attained age) and gender. The baseline model
parameters and explicit details about the dose effect modification term are given in Table S2 in the supplementary material (http://dx.doi.org/10.
1667/RR2892.1.S21). Supplementary Table S8 (http://dx.doi.org/10.1667/RR2892.1.S2) presents information on alternative EAR models. The
dose coefficients describe the excess cases per 10,000 person years at 1 Gy at age 70.

INCIDENCE OF HEMATOPOIETIC MALIGNANCIES

373

FIG. 4. LSS chronic myeloid leukemia risk summary plots. Panel a: shows age-specific Hiroshima baseline rate for LSS cohort members formen (black line) and women (gray line). Panel b: illustrates the radiation dose response based on the ERR model with gender average risks
standardized to time since exposure at 25 and at attained age 55. The solid-black lines illustrates the fitted linear dose response. The points are
based on a nonparametric dose response model, while the middle-dashed-gray line is a smoothed version of the dose category-specific estimatesfrom the nonparametric fit. The upper- and lower-dashed-gray lines are plus and minus one standard error from the smoothed fit. Panels c and d:illustrate the temporal pattern and age-at-exposure effects for our preferred ERR model. Curves are shown for ages at exposure 10 (solid curve), 30(dash line) and 50 years (dash-dot line) in Hiroshima. The ERR does not depend on gender. Panels e and f: present the temporal pattern and age-at
exposure effects by gender based on the preferred EAR model in Hiroshima. Curves are shown for age at exposure 10 (solid line), 30 (dash line)
and 50 years (dash-dot line) with black and gray lines for men and for women, respectively.

were identified including 10 cases classified as chronic
lymphocytic leukemia and 2 as hairy cell leukemia. The
newly identified cases included only one case among thenot-in-city cohort members and 7 cases diagnosed after
1987. Using a simple age- and gender-adjusted baselinemodel, a significant linear dose response was detected,
which suggested that CLL risk might be increased at higher
doses (P , 0.05).
Adult T-Cell Leukemia (ATL), Nagasaki Only

There were a total of 47 eligible ATL cases. Due to thefact that there were only 5 ATL cases in Hiroshima, theanalyses were limited to Nagasaki. The background rate
exhibited a rapid increase with attained age that was
proportional to the power 4.07 (95% CI 2.59–5.74, P ,0.001). Age-specific ATL rates in Nagasaki have changed
significantly over time (P ¼ 0.01), with rates estimated tohave increased by about 34% for each decade increase in theyear of birth (95% CI 7–71%). There were no statisticallysignificant gender differences in the ATL baseline rates (P. 0.5). Figure 5 shows the increasing rates of ATL by age.
The ATL baseline rate model and parameter estimates are
given in supplementary Table S2 (http://dx.doi.org/10.1667/
RR2892.1.S1).

374

HSU ET AL.

TABLE 10Observed and Fitted Background and Excess Cases ofChronic Myeloid Leukemia by Weighted Bone Marrow Dose
Category
Dose (Gy)

Person years

Observedcases, 0.005
0.1
0.2
0.5
1
2
2þ
Total

2,039,093
957,889
201,935
206,749
117,855
64,122
25,761
3,613,404

22
17
2
11
6
9
8
75

Fitted cases
Background

Excess

22.5
11.6
2.5
2.6
1.4
0.7
0.3
41.6

0.1
2.9
3.0
6.5
7.5
7.5
5.9
33.4

Estimates based on the preferred linear ERR model described in
the text and Table 11 with more details in supplementary Table S2(http://dx.doi.org/10.1667/RR2892.1.S1).

Dose response and effect modification. There was noevidence of a dose response for ATL (P . 0.5) and the
ERR/Gy in a linear model was estimated as 0.05 (95% CI
0.51–1.54). Because of a lack of cases among women
who received high doses, the ERR/Gy for women was
estimated to be les than zero. After restricting the excess
risk for women to be zero, the fit of the model was
improved and the ERR/Gy estimate for men was 0.88
(95% CI 0.60–4.52, P ¼ 0.28), which was not statisticallysignificant.
Lymphoma

The 437 eligible lymphoma cases include 402 NHL and
35 HL cases with 143 of these cases diagnosed since 1987
among cohort members who were in the cities at the time of
the bombings. Another 102 cases were among cohort

members who were not in the cities at the time of bombings.
NHL and HL risks were analyzed separately.
Non-Hodgkin lymphoma (NHL). Background rates for
NHL increased rapidly with attained age. While thisincrease was roughly proportional to attained age to thefourth power, the fit was significantly improved when thenature of the increase was allowed to vary with increasing
age, with knots at age 40 and 70 (P ¼ 0.007, with 3 df).
Age-specific rates for women were 58% of those for men(95% CI 48–72%, P , 0.001) with no significant (P . 0.5)
gender difference in the nature of the increase with attained
age. NHL baseline rates also exhibited a complex nonlinear
birth cohort effect (P , 0.001) with the highest age-specificrates for cohort members born around 1940 and lower agespecific rates for people born in earlier or later years. As
shown in Fig. 6a, the age-specific baseline rates for the 1935birth cohort were at least twice those for the 1895 birthcohort. This pattern was similar to that seen for the LSS
leukemia baseline rates and for Japanese national NHL rates(33). There was no indication of a city difference in thebaseline rates (P . 0.5). The NHL baseline rate model andparameter estimates are given in supplementary Table S2(http://dx.doi.org/10.1667/RR2892.1.S1).
Dose response and effect modification. There was noevidence of a significant dose response in the ERR (P ¼
0.23) in a simple linear dose-response model. However,when the ERR was allowed to differ for men and women,
there was a suggestion of an elevated risk in men (ERR/Gy¼ 0.46; 95% CI 0.08 to 1.29, P ¼ 0.11), but no indicationof an effect for women (ERR/Gy ¼ 0.02; 95% CI ,–0.44 to
0.64, P . 0.5). Allowing the ERR for men to vary withattained age led to a significant improvement in the fit
relative to a model with no radiation effects (P ¼ 0.005, with
2 df). Thus, while there was some evidence of a statistically

TABLE 11
Preferred Model, Excess Risk Parameter Estimates for Chronic Myeloid Leukemia
Risk model
ERR Hiroshima
Nagasaki
EARz
FemaleHiroshima
Nagasaki
Male
Hiroshima
NagasakiLinear dose coefficient (at 1 Gy) City ratio (N:H) Gender ratio (F:M) Attained age (power) Time since exposure (power)
5.24 (1.92, 11.8)
1.17 (0.10, 4.71)
0.57 (0.23, 1.10)
0.13 (,0, 0.47)
0.68 (0.24, 1.49)

0.22 (0.03, 0.75)
0.23 (0.03, 0.76)

0.84 (0.34, 2.21)–1.42 (3.04, 0.01)–1.59 (2.34, 0.95)

2.10 (0.48, 4.21)

1.63 (2.38, 0.97)

0.20 (1.03, 0.66)

0.15 (,0, 0.60)

The preferred ERR model is linear in dose with log-linear effect modification depending on log (attained age), log (time since exposure) andcity. The baseline model parameters and explicit details about the dose effect modification term are given in Table S2 in the supplementarymaterial (http://dx.doi.org/10.1667/RR2892.1.S21). Supplementary Table S9 (http://dx.doi.org/10.1667/RR2892.1.S2) presents information on
alternative ERR models. The dose coefficients describe the ERR at 1 Gy at age 55 after exposure at age 30.
z
The preferred EAR model is linear in dose with log-linear effect modification depending on city, sex, log(time since exposure) andlog(attained age) with the attained age effect differing in the two cities. The baseline model parameters and explicit details about the dose effectmodification term is given in Table S2 in the supplementary material (http://dx.doi.org/10.1667/RR2892.1.S1). Supplementary Table S9 (http://dx.doi.org/10.1667/RR2892.1.S2) presents information on alternative EAR models. The dose coefficients describe the excess cases per 10,000
person years at 1 Gy at age 55 after exposure at age 30.

375

INCIDENCE OF HEMATOPOIETIC MALIGNANCIESTABLE 12
Radiation-Associated Excess Leukemia Cases by Subtype and Period
Leukemia subtype
AML
Period1950–1955
1956–1960
1961–1970
1971–1980
1981–1990
1991–2001
Total

ALL

CML

Excessz

Percent§

ExcessPercent

ExcessPercent

Total

6.3
4.3
7.6
6.8
6.2
6.1
37.3

20%
29%
43%
57%
68%
78%
41%

8.3
4.1
4.5
2.4
1.4
0.8
21.5

27%
28%
25%
20%
15%
10%
23%

16.3
6.2
5.7
2.7
1.5
0.9
33.3

53%
43%
32%
23%
17%
12%
36%

30.9
14.6
17.8
11.9
9.1
7.8
92.1

The subtypes considered here are acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), and chronic myeloid leukemia(CML).
z
Radiation-associated excess case estimates based on the preferred ERR models described in the text and in Tables 6, 9 and 11 with additional
details given in supplementary Table S2 (http://dx.doi.org/10.1667/RR2892.1.S1).
§
Percentage of radiation associated excess cases within the time period.

significant radiation effect in men, there was no indicationof a radiation effect in women.
As indicated by the dose-response curves in Fig. 6c, the
ERR/Gy for men (dark solid curve) was large at younger
ages, but declined dramatically and approached 0 by age 40.
It is difficult to interpret the large ERRs for the very young
since baseline rates are highly variable and imprecise due tothe small number of children and young adults at risk fordeveloping NHL. The EAR model provided a more simple
and perhaps more useful description for small excess risks
when baseline rates are low. There was a suggestion of adose response (P ¼ 0.10) in a simple constant EAR model.
Letting the EAR depend on gender led to a significant
improvement in the fit (P ¼ 0.048). The estimated EAR for
men was 0.54 (95% CI 0.09–1.32, P ¼ 0.003) while that for
women was essentially 0 (95% CI 0.02–0.31, P . 0.5).
There was no indication that the EAR varied with attainedage (P ¼ 0.3), time since exposure (P ¼ 0.46), or age at
exposure (P ¼ 0.15). Supplementary Table S2 (http://dx.doi.
org/10.1667/RR2892.1.S21) contains information on theform of the final model than the parameter estimates for thismodel.
Figure 6d presents the fitted constant EAR for men (darksolid line) and the EAR estimate derived from the agedependent ERR model (lighter dashed line) describedabove. While the EAR model suggested a persistentincrease in risk, the ERR model suggested that the excess
rate peaked around age 20 and that there was little excess
after age 30, which also implies that the radiation effects
were seen primarily among those exposed as children or
young adults. Despite striking differences in the pattern ofthe excess risk, the goodness of fit of the ERR (AIC ¼
2,374.8) and EAR (AIC ¼ 2,378.8) models was comparable.
Based on the time-constant EAR model, the estimatednumber of radiation-associated cases over the follow-up
period was estimated to be 7.8 for men and 0 for women(Table 13), with about 10% of the cases among men withdoses in excess of 5 mGy attributable to the radiation
exposure. The time-dependent ERR model predicts about
half the number of excess cases as does the EAR model.
Hodgkin Lymphoma (HL)

There were only 35 eligible HL cases in the cohort. Ageand birth-cohort adjusted baseline rates in women wereabout 40% of those in men (95% CI 21–82%, P ¼ 0.01).
Baseline rates tended to increase with increasing attained
age, but the increase was not statistically significant (P ¼
0.35). However, age-specific rates in later birth cohorts weresignificantly lower than those for earlier birth cohorts (P ¼
0.003). There was no indication of a city difference in thebaseline rates (P ¼ 0.16). HL baseline rates are plotted inFig. 7. The HL baseline rate model and parameter estimates
are described in supplementary Table S2 (http://dx.doi.org/
10.1667/RR2892.1.S1).

FIG. 5. LSS adult T-cell leukemia risk summary plots. The plotshows age-specific Nagasaki baseline rates (zero dose) for LSS cohort
members born in 1895 (dash-dot line), 1915 (dash line) and 1935
(solid line). There is no significant dose response.

376

HSU ET AL.

FIG. 6. LSS non-Hodgkin lymphoma risk summary plots. Panel a: shows age-specific Hiroshima baseline rates for LSS cohort members.
Curves are shown for birth cohorts 1895 (dash-dot line), 1915 (dash line) and 1935 (solid line) model with black and gray lines for men and for
women, respectively. Panel b: illustrates the radiation dose response based on the EAR model with black and gray lines for men and for women,
respectively. Panel c illustrates the ERR temporal pattern for men. The solid line shows the predicted ERR based on our preferred ERR model, andthe dotted line is the ERR derived from our preferred EAR model. Panel d: presents the EAR temporal pattern for men. The dotted line shows thepredicted EAR based on our preferred EAR model and the solid curve is the EAR derived from our preferred ERR model.

Dose response and effect modification. No significant
dose response was found for HL (ERR/Gy ¼ 0.20; 95% CI
1.03–2.63, P . 0.5). Allowing the dose response todepend on gender did not improve the fit of the model (P .
0.5), nor was there any indication of statistically significant
variation in the ERR with age (P . 0.5). The estimated time
constant EAR was essentially 0 (P . 0.5).
Multiple Myeloma (MM)Among the 181 cases of MM identified in this study, 136
were eligible for use in the risk analyses including 36 cases
diagnosed in survivors after 1987 and 31 cases diagnosed
among cohort members who were not in the cities at thetime of the bombings.
Baseline rates varied significantly with both attained age(P , 0.001) and birth cohort (P , 0.001). The birth cohort
effect appeared to be non-monotonic, with the largest agespecific rates seen for people born around 1920 anddecreasing by about 35% per decade for earlier and later
birth cohorts. This pattern was generally similar to thatseen in leukemia other than CLL or ATL in this cohort.
The increase in rates was roughly proportional to attained

age to the power 5.45 (95% CI 4.41–6.55, P , 0.001).
However, the model was significantly improved (P ¼ 0.01)
when the baseline rate was allowed to increase to about
age 80 and level out, or even decrease later in life (Fig. 8).
TABLE 13
Observed and Fitted Background and Excess Cases of NonHodgkin Lymphoma Cases by Weighted Bone Marrow Dose
Category
Fitted cases

Dose (Gy)

Person years

Observedcases

Background

Excess,0.005
–0.1
–0.2
–0.5
–1
–2
2þ
Total

2,039,093
957,889
201,935
206,749
117,855
64,122
25,761
3,613,404

226
99
21
28
13
14
1
402

221.6
104.2
22.7
22.9
13.2
7.1
2.5
394.2

0.02
0.6
0.6
1.3
1.7
2.0
1.6
7.8

Estimates based on the preferred linear EAR model described in
the text with additional details in supplementary Table S2 (http://dx.
doi.org/10.1667/RR2892.1.S1). This is gender-dependent, time-constant linear EAR model with an EAR of 0.54 cases per 10,000 PY at 1
Gy and no excess risk for women.

377

INCIDENCE OF HEMATOPOIETIC MALIGNANCIES

is no evidence of a statistically significant radiationassociated excess risk of incident MM in the atomic bomb
survivors.
DISCUSSION

FIG. 7. LSS Hodgkin lymphoma. The plot shows age-specificbaseline rates (zero dose) for LSS cohort members born in 1895 (dashdot line), 1915 (dot line) and 1935 (solid line). The black lines are formen and the gray lines are for women. There is no significant dose
response.

The background risk did not vary significantly with either
gender (P ¼ 0.16) or city (P ¼ 0.12). Supplementary Table
S2 (http://dx.doi.org/10.1667/RR2892.1.S1) contains information on the form of the final baseline rate model withthe associated parameter estimates.
Dose response and effect modification. The ERR/Gyestimate of 0.38 from a linear dose-response model was notstatistically significant (95% CI 0.23–1.36, P ¼ 0.21) The
fit was not improved by the addition of a quadratic term (P¼ 0.44). There was no evidence of statistically significant
variation in the ERR with gender (P . 0.5), attained age (P¼ 0.31) or age at exposure (P . 0.5).
When the data were described using a constant linear
EAR model, the estimated EAR was 0.07 cases per 10,000
PY per Gy (95% CI ,–0.05–0.29, P ¼ 0.25), with noindication of variation with gender (P ¼ 0.5), attained age (P¼ 0.33) or time since exposure (P . 0.5). This point
estimate of the EAR is almost identical to that reported 15
years ago. As in the previous report, we conclude that there

Our study extends the follow-up 14 years beyond thatused in the last major report on hematological malignancies
in the LSS cohort (4), providing incidence follow-up for 55
years. This has been made possible because of the active
ascertainment and review of hematopoietic malignancies
already in place when the cohort was established in late1950, together with the subsequently established tumor
registries in Hiroshima and Nagasaki. Due to incomplete
ascertainment of incident cases among cohort members who
moved away from Hiroshima or Nagasaki, a probabilistic
adjustment for migration was included in the analyses aswith all other major LSS incidence reports. Diagnostic
criteria and type definitions for hematopoietic malignancies
have evolved and been refined over time, but thereclassification of leukemia types for cases diagnosed
before the mid-1980s using the recent classifications has
enabled us to use diagnostic categories that are consistent
with and generally as detailed as those used in other studiesof radiation effects on these malignancies.
In contrast to the earlier report (4) that focused
exclusively on time-since-exposure dependent EAR models
with, in most cases, categorical age-at-exposure effects, we
assessed excess risk in this report using ERR and EAR
models with simple continuous functions of age at exposureand either attained age or time since exposure. We foundthat those smooth models describe the data as well as thepartially categorical models used in ref. (4). We also foundthat while both ERRs and EARs for leukemia other than
CLL or ATL as a group have declined over the follow-up
period for all ages at exposure (Fig. 1d and f), the excess
risks do not appear to have fallen to zero by the end of thefollow-up—55 years after exposure. The temporal variationof either the ERR or EAR as described in terms of (post-

FIG. 8. LSS multiple myeloma summary plots. Panel a: shows age-specific baseline rate (zero dose) for LSS cohort members born in 1895
(dash-dot line), 1915 (dash line) and 1935 (solid line). Panel b: shows the baseline rate by birth year at attained age 70.

378

HSU ET AL.

TABLE 14Comparison of Risk Estimates to Selected Cohort Studies

Study cohort
3rd NRRW
A-bomb LSS cohort (males,
20,¼age at exposure ,60)
Techa River cohort
A-bomb LSS cohortz

Cancerend point

Follow-up

incidenceincidence

1955–2001
1950–2001

incidenceincidence

1953–2005
1950–2001

Cases

Average dose(range)

Dose response
model

ERR: Leukemia
excluding CLL(95% CI)234
93

0.025 Sv (.0, 0.1þ)
0.50 Gy (0, 3.16)

LinearLinear

1.78 (0.17, 4.36)
2.04 (0.33, 6.85)

70
312

0.3 Gy (0, 2.0)
0.64 Gy (0, 4.54)

LinearLinear

4.9 (1.6, 14.3)
2.78 (1.84, 4.01)

The analysis is restricted to men who were exposed to A-bomb radiation at age 20–60 with weighted bone marrow dose 4 Gy. The ERR
coefficient describes the excess RR at 1 Gy at age 50 after exposure at age 25.
zThis analysis is for the full LSS cohort excluding unknown dose. The ERR coefficient describes the excess RR at 1 Gy at age 60 after
exposure at age 25.

exposure) attained age highlights that, while highest excess
risks are seen shortly after exposure for those exposed as
children, at any given attained age the excess risks are
generally higher for those exposed later in life (Fig. 1c ande). In addition, the NIC group was used in this study toaugment the information on the variation in baseline rates.
When all leukemias (or subtypes) other than CLL/ATL
were examined, the inclusion or exclusion of the NIC group
did not substantially change the risk estimates.
Richardson et al. (7) recently considered an ERR modelfor the LSS leukemia mortality in which the temporalvariation was described in terms of an age-at-exposure
dependent log cubic spline in time since exposure. Thatmodel (AIC ¼ 2,445.6) did not describe the leukemia
incidence data as well as did our preferred ERR model (AIC
¼ 2,431.9).
In the BEIR VII study (36) and some other recent work on
the LSS leukemia mortality data (7), the age-at-exposure
effect on the excess risks was not allowed to vary amongpeople who were more than 30 years old at the time of
exposure. Imposing this constraint on our models resulted ina markedly poorer fit (AIC ¼ 2,438.4 for the constrainedmodel versus 2,431.89 for our preferred leukemia other than
CLL or ATL model).
A major focus of this report was on the leukemia otherthan CLL or ATL as a group, which includes data on
several different types of leukemia. To the extent that thecell-type distribution of the cases in this group in the LSS
resembles that of many non-Japanese populations, the LSS
risk data for this group can be useful for prediction orcomparison with the radiation-related risk of leukemia otherthan CLL in other irradiated populations. Carrying out such
additional analyses, we found that the predicted ERRs in the
LSS cohort are consistent and comparable to thoseestimated in the studies of the National Registry ofRadiation Workers (37) and the Techa River Cohort (38).
Table 14 gives the comparison of risk estimate of the LSS
cohort based on a relevant subset to the aforementioned
cohorts.
Another focus was to characterize the radiation-related
risk for specific types of leukemia. Leukemias other than

CLL or ATL as a group, as well as ERRs for AML, ALL
and CML considered separately, declined over time for all
age groups. The temporal patterns in the type-specific EAR
estimates are more complicated. Our analyses suggested
that AML excess rates may have increased slightly overtime, especially among people exposed after about age 30,
while the EARs for ALL and CML have decreased overtime. Those declines have often been interpreted assuggesting that the leukemia excess rates among theexposed returned to baseline levels 10–20 years after
exposure. However, the analyses in this paper indicated that
this is not the case for AML and ALL, as there was evidenceof persistent risks 30 to 50 years after exposure for each ofthese types.
Cell-type specific leukemia risks and especially how they
are modified by age and time, may be more useful inconsidering possible biological mechanisms for radiationassociated leukemogenesis than from analyses of aheterogeneous group of several types of leukemia combined. Some striking contrasts were noted between the typespecific excess rates. First, while AML exhibited anonlinear upward-curving dose response, there was noevidence against linearity for either ALL or CML. Also, as
noted above, AML excess rates tended to increase withincreasing attained age for those exposed as adults, while
ALL and CML excess rates appeared to decrease over time.
While the radiation-related risk of CML seemed to declinewith both age at exposure and time since exposure, the ALL
excess rates decreased with attained age, but did not varywith either age at exposure or time since exposure.
The data suggest that the radiation associated excess rates
for AML follow a U-shaped pattern in age, with excess rates
falling for the youngest cohort members (who had to havebeen exposed early in life) and then increasing with attained
age regardless of age at exposure. Although the current
preferred EAR model for AML is much more simple than
the 1994 model that involved complex interactions between
age at exposure and time since exposure, the variation in thefitted excess rates with age are quite similar as shown in Fig.
2e and f. The temporal patterns for the ALL and CML
excess rates differ significantly from those seen for AML. In

INCIDENCE OF HEMATOPOIETIC MALIGNANCIES

particular, excess rates for both ALL and CML, which wereconsiderably greater than those for AML in the period
shortly after the bombings, have decreased markedly overtime. Thus, as indicated in Table 12, ALL and CML cases
were the most common radiation-associated types andaccount for about 75% of the excess cases during the first 5
years of follow-up, i.e., years 5–10 after radiation exposure.
If radiation markedly increased leukemia risks prior to1950, as seems especially likely for ALL and CML, then the
proportion of the radiation-associated excess ALL and CML
cases in the first decade after exposure is likely to be evenmore striking than that which was suggested by theavailable data.
As the cohort members have aged, AML has become thepredominant radiation-associated leukemia, accounting forover 80% of excess leukemia cases during the last 15 years
of follow-up. It has been suspected that leukemia may be
induced by specific translocations caused by radiation.
However, spontaneous translocations specific to ALL aremuch more frequent than AML cases bearing the translocations. In addition, radiation-induced DNA damage isessentially random in the genome. Based on theseobservations, Nakamura (39) recently speculated that theradiation-related ALL risk in a population is almost entirely
attributable to a small number of predisposed individuals inwhom translocation-carrying pre-ALL cells have accumulated. He suggested that the short latency period forradiation-related ALL risk at young ages may be due tothe small number of events needed for the conversion of
pre-ALL cells present in newborns to full malignancy.
Although CML occurs primarily in the elderly, the temporalrisk pattern for CML is similar to that of ALL. BCR/ABL
fusions have been linked to the majority of CML cases, but
are also common in the general population (40). It may bethat a very few additional mutations are required to convert
the translocation-bearing pre-leukemic cells to tumor cells.
Nakamura suspected the possibility of two different
mechanisms: one for young-onset AML, which is clonallyexpanded similar to ALL, and the other for non-translocation-type AML, which like solid cancers, predominates in
middle- and older-aged individuals, requiring a multi-stepleukemogenesis process. The temporal patterns that we findfor these three leukemia subtypes are generally consistent
with Nakamura’s hypothesis.
A recent study of myelodysplastic syndrome (MDS) risks
among Nagasaki survivors for the period from 1985–2004(41) showed a significant excess risk of MDS with an ERR/
Gy estimate of 4.3 (95% CI 1.6–9.5), which is about twice
the AML ERR estimate for the post-1986 period. People
with MDS are known to have a higher risk of developing
AML. However, it is of interest to note that the ERR for
MDS after 1985 is larger than that for AML and that theshape of the dose response is quadratic for AML, but
approximately linear for MDS. Further data on MDS
incidence among LSS Nagasaki survivors and among

379

Hiroshima survivors would help to better understand therelationship between MDS and AML excess risks.
It is likely that some cases identified as AML in the earlyyears would have been classified as MDS if they werediagnosed with modern criteria. However, we feel that such
misclassification is unlikely to have much impact on theinferences about AML risk estimates in the LSS, since (1)AML cases prior to the mid-1980s identified as MDS in the
FAB review (18) were not used in the current analyses, (2)misclassification is less likely in the more recent years since
MDS was recognized as a distinct condition, and (3) the
AML baseline risk model includes a birth cohort effect that
reduces the impact of period-specific misclassification. Any
misdiagnosis of MDS as AML cases is likely to be
independent of dose in which case it would not affect the
ERR estimate of AML risk, though it would tend to increase
the EAR estimate.
Chronic lymphocytic leukemia is very rare in Japan. Dueto the small number of CLL cases in the LSS, radiation
effects on CLL have not been considered in previous LSS
reports. Although there were only 12 eligible cases, four ofwhich occurred among survivors with doses in excess of 0.2
Gy, a simple trend test suggested a statistically significant
dose response. Our results are consistent with findings ofsome, though not all, studies in the literature. A recent casecontrol study of leukemia in Chernobyl clean-up workers in
Ukraine (29) and another such study in Belarus, Russia andBaltic countries (42) have shown increased risk of both CLL
and leukemia other than CLL associated with radiation
exposure. Similarly, a significantly increased risk of CLL as
well as non-CLL leukemia was associated with radon and/or
gamma radiation exposures in uranium miners (28).
Conversely, no evidence of radiation-associated increases
in the risk of CLL were seen in various other studies
including the 15-country nuclear worker study (43), theTecha River cohort (38), the Mayak worker cohort (44), or
UK radiation workers (37). The suggestion of a radiation
effect on CLL risks in the LSS should be interpreted withcaution and generalization to other populations may be
unwarranted. In most Western populations, CLL accounts
for 20% or more of all leukemia cases and an even higher
proportion of leukemias seen late in life, but accounts for
only about 3% of the LSS cases. Clinical data suggest thatJapanese CLLs are largely dormant and genetically andbiologically different from nonsmoldering CLLs seen inWestern populations.
The large proportion of ATL in Nagasaki is not
surprising. As reported in a nationwide study on ATL in
Japan, ATL is endemic in Nagasaki (45). In the Nagasaki
LSS, 42 out of 66 leukemia incident cases (63.6%) werediagnosed with ATL. There is no evidence of a radiation
effect for ATL among Nagasaki LSS subjects, which may
be due to the unusually high HTLV-I infections in theregion.
The evidence for radiation effects on the risks of the othertypes of hematopoietic malignancies considered was less

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clear cut. While there is no evidence of a radiation effect ordose response for HL or MM, the finding of a significant
radiation-associated increase in NHL risks for men with noevidence of a radiation effect for women is similar to what
has been reported in earlier analyses of NHL incidence (4)and mortality in the LSS (46). In the recent mortality
analysis, Richardson et al. (46) considered ERR models for
NHL mortality among LSS men who were 15–64 years oldat the time of exposure and found a significant associationthat was most prominent 35 or more years after exposure.
This is quite different than what is seen for the incidence
data in which the ERR declines markedly with age (andhence time since exposure) whether or not the analysis isrestricted to working age males. In our view, at best the LSS
incidence data provide rather weak support for an NHL dose
response among men with no evidence to support the ideathat the risks are increasing with attained age or time since
exposure.
Some early reports on myeloma mortality and incidence
in the LSS have shown a statistically significant dose
response for MM. The reasons for the differences between
the findings of the incidence analyses and these earlier
analyses were discussed in (4). To understand thedifference, we also carried out an analysis of MM mortality
in the cohort used for the current study. There were 111
MM deaths during the follow-up period including 86 MM
cases used in the incidence analyses, and another 19 casesthat were not used in the incidence analyses because they
were either second primaries (10 cases) or not resident in thecatchment area at the time of diagnosis (9 cases). Four of theremaining 6 cases had been rejected by the registries, while
the other 2 cases had reports of solid cancers (both reported
as renal cell carcinoma) with no indication of MM or any
other hematopoietic malignancies. There was no evidenceof statistically significant increases in either the ERR (P ¼
0.12) or the EAR (P ¼ 0.3) with dose. The ERR and EAR
point estimates were similar to those given above for theincidence data. This difference is largely due to uncertainties about the diagnosis of a small number of high-dose
cases for which MM reported as the cause of death was notconfirmed by the in-depth hematological review conducted
for the incidence study. Taken together, the data provide
little, if any, evidence of a radiation effect on MM.
Although some worker studies including the most recent
analysis of UK National Registry for Radiation Workers(37) and a study based on records from the National Dose
Registry of Canada (47) provide some suggestion of a dose
response for MM, the dose-response trends seen in thosestudies were not statistically significant. Results for MM
mortality using extended follow-up are discussed in thelatest LSS mortality report (48).
Increases in leukemia risks were one of the earliest
significant long-term health effects detected among theatomic bomb survivors. However, in view of the declining
radiation-related risk over the years, it has been thought thatthe radiation-associated excess risks would disappear overtime. The present analyses that included information on
cases diagnosed 43–56 years after exposure have provided
important new insights into the persistent nature of theleukemia risks. The data suggest that, while radiationassociated excess risks for ALL and CML among theexposed have essentially returned to baseline levels by theend of follow-up, AML risks have persisted with excess
rates that appear to be increasing with attained age (albeit
not as rapidly as the baseline rates). It seems likely that theexcess AML risks will persist throughout lifetime for people
exposed at any age. This is similar to the temporal pattern
for solid cancers. Since 40% of the cohort including most of
those exposed as children, were still alive at the end offollow-up in this study, with continued follow-up of the
LSS and evolving analytical methods, we expect that further
insights will be gained into radiation effects on the leukemia
and other hematopoietic malignancies.
APPENDIXThe online appendix tables include a listing of the morphological codes
for the subtype groups and detailed descriptions of the parameterizations
and parameter estimates for the preferred baseline and excess rate (ERR
and EAR) models along with tables that describe (1) the impact of
migration adjustment on person years (by city, gender, birth cohort andtime period), (2) crude rates (by birth cohort, time period and dose
category) and (3) alternative models for leukemia other than CLL or ATL,
AML, ALL and CML (http://dx.doi.org/10.1667/RR2892.1.S3).

ACKNOWLEDGMENTS
The Radiation Effects Research Foundation is a private, non-profit
foundation funded by the Japanese Ministry of Health, Labour andWelfare and the U.S. Department of Energy, the latter in part throughDOE award DE-HS0000031 to the National Academy of Sciences, which
supported WLH, HMC and RES. This research was also supported by the
U.S. National Cancer Institute contract N02-CP-2009-00005 and in part by
the Intramural Research Program of the NIH Division of Cancer
Epidemiology and Genetics. The views of the authors do not necessarilyreflect those of the two governments. We are especially grateful to thediligent work of tracing and abstracting hospital records by the staff of theHiroshima and Nagasaki tumor registries and of the hematologists andothers who were engaged in the operation of the Leukemia Registry.
Received: December 7, 2011; accepted: November 19, 2012; published
online: February 11, 2013

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