RADIATION RESEARCH 178, 191–201 (2012)0033-7587/12 $15.00
Ó2012 by Radiation Research Society.
All rights of reproduction in any form reserved.
DOI: 10.1667/RR2819.1

Radiation and Smoking Effects on Lung Cancer Incidence by HistologicalTypes Among Atomic Bomb Survivors
Hiromi Egawa,a Kyoji Furukawa,b,1 Dale Preston,c Sachiyo Funamoto,b Shuji Yonehara,d Takeshi Matsuo,eShoji Tokuoka,b Akihiko Suyama,b Kotaro Ozasa,b Kazunori Kodamab and Kiyohiko Mabuchifa
Hiroshima City Asa Hospital, Hiroshima, Japan; b Radiation Effects Research Foundation, Hiroshima and Nagasaki, Japan; c Hirosoft
International, Eureka, California; d Welfare Association Onomichi General Hospital, Japan; e Nagasaki Health Promotion Corporation, Nagasaki,
Japan; and f Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Marylandcancers as a group, such complicated interactions did notdescribe the data significantly better than either simple
additive or multiplicative interaction models for any of thetype-specific analyses. Ó 2012 by Radiation Research Society

Egawa, H., Furukawa, K., Preston, D., Funamoto, S.,
Yonehara, S., Matsuo, T., Tokuoka, S., Suyama, A., Ozasa,
K., Kodama, K. and Mabuchi, K. Radiation and Smoking
Effects on Lung Cancer Incidence by Histological Types
Among Atomic Bomb Survivors. Radiat. Res. 178, 191–201(2012).

INTRODUCTION

While the risk of lung cancer associated separately withsmoking and radiation exposure has been widely reported, it
is not clear how smoking and radiation together contribute to
the risk of specific lung cancer histological types. With
individual smoking histories and radiation dose estimates, wecharacterized the joint effects of radiation and smoking on
type-specific lung cancer rates among the Life Span Study
cohort of Japanese atomic bomb survivors. Among 105,404
cohort subjects followed between 1958 and 1999, 1,803 firstprimary lung cancer incident cases were diagnosed andclassified by histological type. Poisson regression methods
were used to estimate excess relative risks under several
interaction models.
Adenocarcinoma (636 cases), squamous-cell carcinoma(330) and small-cell carcinoma (194) made up 90% of thecases with known histology. Both smoking and radiation
exposure significantly increased the risk of each major lungcancer histological type. Smoking-associated excess relative
risks were significantly larger for small-cell and squamouscell carcinomas than for adenocarcinoma. The genderaveraged excess relative risks per 1 Gy of radiation (fornever-smokers at age 70 after radiation exposure at age 30)
were estimated as 1.49 (95% confidence interval 0.1–4.6) forsmall-cell carcinoma, 0.75 (0.3–1.3) for adenocarcinoma,
and 0.27 (0–1.5) for squamous-cell carcinoma. Under amodel allowing radiation effects to vary with levels ofsmoking, the nature of the joint effect of smoking andradiation showed a similar pattern for different histologicaltypes in which the radiation-associated excess relative risk
tended to be larger for moderate smokers than for heavy
smokers. However, in contrast to analyses of all lung

Lung cancers arise in various cell types. While themixture of different histological types varies considerably
between countries and populations and has changed overtime, squamous cell carcinoma (SqCC), small cell carcinoma (SmCC) and adenocarcinoma (AC) account for the
majority of microscopically diagnosed cases (1). Cigarettesmoking is associated with increased rates for most types oflung cancer with the largest (relative) increases forsquamous cell carcinoma and small cell carcinoma (2, 3).
Adenocarcinoma predominates in never-smokers for mostcountries, but recent increases in adenocarcinoma rates also
seem to be attributed to smoking (4, 5). Ionizing radiation
exposure has been shown to be associated with significant
increases in lung cancer rates (6, 7). There has also been
considerable interest in the nature of the joint effect ofradiation and smoking among uranium miners (8), populations exposed to residential radon (9–11), radiation-treated
Hodgkin’s disease patients (12, 13) and Japanese atomic
bomb survivors (14, 15).
In the Life Span Study (LSS) cohort of atomic bomb
survivors, a rather complex radiation-smoking interaction
was found for the risk of all lung cancers as a group. This
interaction was best described as super-multiplicative forlow-intensity smokers and additive or subadditive for highintensity smokers (15). In addition, smoking-associatedrelative risks of lung cancer in this Japanese cohort were
somewhat smaller than those reported from Western
populations (16–18). These results pertained to the risk oflung cancer as a group, but little is known about the natureof the joint effects of radiation and smoking on different
histological types of lung cancer. In this paper, we describe
the distribution of lung cancer by histological type in the

Editor’s note. The online version of this article (DOI: 10.1667/
RR2819.1) contains supplementary information that is available to all
authorized users.
1Address for correspondence: 5-2 Hijiyama Park, Minami-ku,
Hiroshima, Japan; e-mail: furukawa@rerf.or.jp.
191

192

EGAWA ET AL.

LSS and characterize, to the extent possible, the radiationsmoking interaction for the three major histological types oflung cancer.
MATERIALS AND METHODS
Study Cohort and Case Ascertainment
The LSS cohort consists of 120,321 subjects who were residents ofHiroshima and Nagasaki in October 1950, including 93,741 atomic
bomb survivors who were within 10 kilometers of the hypocenters at
the time of bombing and an age, gender, and city frequency-matchedgroup of 26,580 people who were temporarily away from the cities atthat time, as described elsewhere (6, 19). After excluding subjects who
did not have dose estimates (7,070 people), could not be traced (71people), or were known to have died or had cancer prior to theinception of the Hiroshima and Nagasaki Tumor registries on January
1, 1958 (7,776 people), 105,404 cohort members were eligible foranalyses in this study.
As in the previous report, lung cancer diagnoses and histologicaltypes were derived from a pathology review carried out to identify
LSS lung cancer cases through the end of 1999. At the first stage ofthe case review, 5,711 members with potential lung tumors wereidentified using information from the Hiroshima and Nagasaki Tumorand Tissue Registries, an autopsy program of the Radiation Effects
Research Foundation, and mortality data collected as part of the LSS
mortality follow-up. Additional information, including registry
records, tissue slides, and relevant clinical and pathology records
were sought for those cases. In reviewing the available data, the study
pathologists identified and classified 2,368 lung cancers based on thelatest WHO diagnostic criteria (20). Lung cancers were consideredineligible if they were not the first primary tumor (216 cases), if theindividual was not a resident in Hiroshima or Nagasaki Prefecture at
the time of diagnosis (171 cases diagnosed primarily from deathcertificates) or was diagnosed prior to 1958 (47 cases), or if a dose
estimate was unavailable (131 cases), resulting in 1,803 eligible cases
for use in analysis.
Radiation and Smoking Data
The radiation dose-response analyses were based on individual
weighted DS02 lung doses (19) calculated as the c-ray dose plus 10
times the neutron dose in Gy with adjustment to reduce bias in risk
estimates associated with the uncertainty in individual dose estimates(21).
Smoking histories were obtained for 61% of the cohort members
from a series of mail surveys conducted in the LSS between 1965 and1991 and from interviews conducted in a clinical subcohort of the
LSS. For the present analyses, individual smoking history wassummarized by a time-dependent indicator of smoking status (never/past/current/unknown), the year (if any) in which smoking data werefirst obtained, and, for ever-smokers, ages started or stopped smoking
and the average number of cigarettes smoked per day. For smokers,
smoking duration was defined as the difference between the reported
age at start of smoking and the minimum of the current age and theage at which one reported having stopped smoking. Time sincequitting was defined as the difference between the current age and theage at smoking cessation for reported past smokers and as 0 otherwise.
Cohort members for whom data on smoking habits had never beenobtained were treated as having unknown smoking status throughout
their time at risk. In addition, for the period prior to the date at which
information on an individual’s smoking habits was first obtained, his/her smoking status was treated as unknown. This was done to avoid
biasing risk estimates by overcounting person years in known
smoking-status categories. Additional details on the smoking variables
are available elsewhere (15).

Statistical Analysis
Primary analyses were based on a highly stratified person-year tablecontaining about 120,000 cells with non-zero person-years at risk.
Each cell contained the number of person-years, cases (by histologicaltype) and person-year weighted means of attained age, age at
exposure, calendar year, radiation dose, and smoking summary
variables. Details of the categorization are given in the previous
report (15).
Analyses were carried out using Poisson regression models forcancer rate functions of the form:RateðB; S; DÞ ¼ k0 ðBÞRRðS; DÞ;
where k0 is a function of background factors B that describes theincidence rate for unexposed never-smokers (baseline rate), and RR isa relative risk function that can depend on smoking- (S) and radiationdose- (D) related variables as well as variables that modify the effects.
We considered several forms for the joint effects of smoking andradiation:
Additive model ðAMÞRRðS; DÞ ¼ 1 þ /ðSÞ þ qðDÞMultiplicative model ðMMÞRRðS; DÞ ¼ ½1 þ /ðSÞ½1 þ qðDÞ
Generalized additive model ðGAMÞ
RRðS; DÞ ¼ 1 þ /ðSÞ þ qðDÞxðSÞ
Generalized multiplicative model ðGMMÞ
RRðS; DÞ ¼ ½1 þ /ðSÞ½1 þ qðDÞxðSÞ
where / and q describe the excess risks associated with smoking- andradiation-related variables, respectively. Under the additive model, q
is the excess relative risk (ERR) of exposed subjects relative to
unexposed never-smokers, while under the multiplicative model it is
the ERR relative to unexposed subjects with the same smoking
history. Similar interpretation applies to the smoking excess risk. The
generalized models allow for departures from either additive or
multiplicative interactions by allowing the radiation ERR to vary as afunction x of smoking variables.
An analysis model is specified by the interaction type (AM, MM,
GAM or GMM) and a set of model-component forms (k0, /, q andx). For all type-specific analyses in this study, we used the same
set of component forms considered in analysis for all lung cancers
combined (15), which are described as follows: The baseline rate model k0(B) assumed the log rate to be
proportional to gender-specific quadratic functions of log attained
age with additional effects of city and birth year. In addition,
cohort members who were not in the cities at the times ofbombing were distinguished from the other members with anindicator. Thus, radiation effects were quantified relative to rates
for survivors who were in the cities at the times of bombing but
received little radiation from the bombs.
 The smoking excess risk /(S) was described as a function of the
cumulative amount smoked (packs of cigarettes smoked per day
times years smoked), or pack-years (p), times an effectmodification function that depended on gender (g), birth-cohort(b), smoking duration (y) and time since quitting (q): u( S) ¼
hgpexpfnb þ g1log(y) þ g2log(y)2 þ vlog(q þ 1)g. For thefollow-up during which smoking status was unknown, the‘‘smoking’’ effect was allowed to vary with gender and birthcohort strata.
 The radiation excess risk q(D) was described by the product of agender-specific function of dose (d) and an effect-modification
function that depended on age at exposure (e) and attained age(a). With the linear dose-response, the excess risk was describedas q(D) ¼ dgdabexpfceg. Departure from the linear dose-response
was tested by using various nonlinear functions.

LUNG CANCER INCIDENCE BY HISTOLOGICAL TYPES

The generalized radiation-smoking interaction was expressed as afunction of smoking intensity (s), x(S) ¼ expfx1log(s) þx2log(s)2g with x(S) [ 1 for lifelong never-smokers.

Model parameters were estimated by maximum likelihood using
Epicure software (22). Likelihood ratio tests were used to compute P
values for hypothesis tests (two sided) and to determine confidence
intervals (CIs).
Although we made some efforts to develop more parsimonious
models for specific histological types, goodness of fit measures suchas the Akaike information criterion (AIC) (23) suggested that
improvements gained by using more parsimonious models werelimited. Therefore, the results presented herein were limited to those
based on the component forms described above to facilitatecomparisons across types. The rule for these comparisons was thatAIC differences (for a given outcome) of less than about 6 should not
be regarded as significant (24).
In the main text we focus on the nature of radiation and of smoking
effects on rates for the most common histological types (AC, SqCC,
SmCC) of lung cancer. Results for the relatively large proportion ofcases for which histological type could not be determined and thosefor the combined cases of the three common histological types arepresented as supplementary materials.

RESULTS

Table 1 provides information on the number of cases andcrude rates by histology and sex in the study cohort.
Adenocarcinoma accounted for 35% of all lung cancer cases
and almost half of those with identified types. Squamouscell carcinoma accounted for 18% of all cases and 25% of
the type-identified cases, and small cell carcinoma for 11%
and 15%, respectively. The histological type could not be
determined for 28% of all cases (labeled ‘‘not otherwise
specified’’), about half of which were reported as lungcancers solely on the basis of death certificates. Crude rates
were generally higher for men than for women with thesmallest relative differences for adenocarcinoma and nototherwise specified.
Table 2 provides summary information on case counts
and crude rates for the three major types. Crude rates weresimilar for Hiroshima and Nagasaki and increased over thefollow-up period in part due to the aging of the cohort, but
trend for adenocarcinoma was remarkable.
Table 3 provides type-specific case counts and crude rates
by radiation dose, smoking status at diagnosis and gender.
Crude rates for each type appeared to be strongly associatedwith smoking status. Crude rates were consistently higher
for men than for women, although sex-specific rates weresimilar in men and women for small cell carcinoma among
the current-smokers and for adenocarcinoma among neversmokers. While crude rates were higher for adenocarcinoma
than for squamous cell carcinoma or small cell carcinoma,
the crude risks for smokers relative to never-smokers wereseveral-fold larger for squamous cell carcinoma or small cell
carcinoma than for adenocarcinoma. Information on
smoking status was available for 59% of men and 62% of
women, among whom 86% of men but only 18% of womenreported having smoked, while among these ever-smokers,
30% of men and 34% of women reported having quit as of

193

their last survey responses (not shown). While interpretations of risk patterns with radiation dose by smoking status
in Table 3 are hampered by the small number of cases, the‘‘total’’ row for each type suggests a radiation-related
increase in the risks. Tables S2 and S3 in the supplementarymaterial (http://dx.doi.org/10.1667/RR2819.1.S1) present
information similar to Tables 2 and 3, respectively, for all
lung cancers, the not otherwise specified group, and thethree major types as a group.
For each of the three histological subtypes, Table 4
presents estimates and 95% CIs for selected parameters in
the radiation and smoking excess risk functions under thegeneralized multiplicative model together with AIC values
for the four interaction models, as described above, andmodels with only radiation or smoking effects. While thegeneralized multiplicative model performed better than theother interaction models for all lung cancers as a group (15),there was no strong evidence to prefer or reject any of thefour interaction models in any type-specific analysis. The
simple interaction models (additive or multiplicative) had
the smallest AIC values but the differences were not large.
Table S4 in the supplementary material (http://dx.doi.org/
10.1667/RR2819.1.S1) shows that the generalized multiplicative model was significant over the simpler model for the
not otherwise specified group (P ¼ 0.003) or when the threemajor types were combined (P ¼ 0.03).
Baseline Rate

Fitted baseline incidence rates were higher for adenocarcinoma than for the other two histological types at all
ages. For each histological type, baseline rates were greaterfor men than for women, with the female:male ratio at age
70 estimated as 0.62 for adenocarcinoma, 0.49 forsquamous cell carcinoma and 0.57 for small cell
carcinoma. Age-specific rates tended to be lower for
younger cohorts, decreasing by 23% (P , 0.001) per
decade increase in birth year for adenocarcinoma, 14% (P¼ 0.28) for squamous cell carcinoma, and 16% (P ¼ 0.28)
for small cell carcinoma. Baseline rate estimates weresignificantly higher in Nagasaki than in Hiroshima for all
lung cancers combined (P ¼ 0.002) and adenocarcinoma (P¼ 0.03) but the city difference was not significant for eithersquamous cell carcinoma (P . 0.5) or small cell carcinoma(P ¼ 0.39). Overall, there was little variation in fitted
baseline rates among the interaction models for each type(not shown).
Smoking Effects

The effect of cumulative smoking amount was statistically significant for each type (P , 0.001), withconsistently higher risks for women than for men with thesame smoking history (Table 4, upper section). The
smoking effect, expressed as the ERR at 50 pack-years
for people with no exposure (unexposed), was significantly
higher for small cell carcinoma (17.5/41.4 for men/women)

194

EGAWA ET AL.

TABLE 1LSS Lung Cancer Cases and Crude Rate (Cases per 10,000 Person-Years) by Histological Type and Sex
Male
Epithelial cancers
Adenocarcinoma
Squamous-cell carcinoma
Small-cell carcinoma
Large-cell carcinoma
Other epithelial cancers
Non epithelial cancers
Mesothelioma
Lymphoma
Unclassified lung cancers
Not otherwise specified (NOS)
Total
Person-years
Subjects

Female

Total

Cases

(%)

Rate

Cases

(%)

Rate

Cases

(%)

Rate

315
254
129
33
45

(29.4)(23.7)(12.0)
(3.1)
(4.2)

2.99
2.41
1.22
0.31
0.43

321
76
65
13
29

(43.9)(10.4)
(8.9)
(1.8)
(4.0)

1.84
0.43
0.37
0.07
0.17

636
330
194
46
74

(35.3)(18.3)(10.8)
(2.6)
(4.1)

2.27
1.18
0.69
0.16
0.26

13
2

(1.2)
(0.2)

0.12
0.02

4
2

(0.5)
(0.3)

0.02
0.01

17
4

(0.9)
(0.2)

0.06
0.01

281
1072

(26.2)(100)
1,053,713
42,889

2.67
10.17

221
731

(30.2)(100)
1,749,254
62,515

1.26
4.18

502
1803

(27.8)(100)
2,802,967
105,404

1.79
6.43

and squamous cell carcinoma (12.7/21.1) than for adenocarcinoma (2.4/3.4). The difference in smoking effects
among the models was relatively large for small cell
carcinoma (the gender-averaged ERRs per 50 pack-years
were estimated as 27, 29, 35 and 35 for MM, GMM, AM
and GAM, respectively). Smoking ERR estimates wereconsistently larger under the additive model than under themultiplicative model, reflecting the fact that the ERR in the
additive model is relative to unexposed never-smokers
while, in the multiplicative model, it is relative to neversmokers with the same radiation exposure.
Smoking cessation led to a significant reduction in risk
compared to the risk that would have been incurred if theindividual had continued smoking for small cell carcinoma(P , 0.001) and squamous cell carcinoma (P ¼ 0.004). The
reduction in risk for adenocarcinoma was not statisticallysignificant (P ¼ 0.44), but similar in magnitude to that forthe other types. There were some indications of variation insmoking effects among birth-cohort groups for squamouscell carcinoma (P ¼ 0.03) and small cell carcinoma (P ¼0.08); the ERR tended to be increasing for earlier-birthcohorts for both of these types, while there was no
indication of a significant birth-cohort effect for adenocarcinoma (P . 0.5).
Figure 1 plots the fitted gender- and age-specificincidence rates (upper panel) and smoking ERR (lower

TABLE 2
Subjects, Cases and Crude Rate (Cases per 10,000 Person-Years) by Histological Subtype of Lung
Cancer in the Study Cohort (1958–1999)
Adenocarcinoma
Subjects
City
Hiroshima
73,414
Nagasaki
31,990Attained age (years)
0–39
40–49
50–59
60–69
70–79
80þ
Age at exposure (years)
0–9
22,681
10–19
23,057
20–39
30,07340þ
29,593
Calendar year
1958–19691970–1979
1980–1989
1990–1999

Squamous cell

Small cell

Cases

Rate

Cases

Rate

Cases

Rate

439
197

2.20
2.44

246
84

1.23
1.04

141
53

0.71
0.66

4
19
113
211
183
106

0.06
0.38
1.90
3.96
5.28
6.82

0
2
33
103
131
61

0
0.04
0.56
1.93
3.78
3.92

0
5
22
63
76
28

0
0.10
0.37
1.18
2.19
1.80

53
124
282
177

0.76
1.72
3.07
3.78

8
46
119
157

0.12
0.64
1.29
3.35

4
23
92
75

0.06
0.32
1.00
1.60

113
124
195
204

1.00
1.75
3.40
5.08

83
86
90
71

0.75
1.20
1.57
1.76

55
42
51
46

0.49
0.59
0.89
1.14

195

LUNG CANCER INCIDENCE BY HISTOLOGICAL TYPESTABLE 3
Cases and Crude Rate (Cases per 10,000 Person-Years) by Radiation Dose, Smoking Status at Diagnosis, and Sex
Radiation dose (Gy)
, 0.005
Histologic type
Men
Adenocarcinoma

Squamous cell

Small cell

Subjects
Women
Adenocarcinoma

Squamous cell

Small cell

Subjects

0.005–0.2

0.2–1

1þ

Total

Smoking status

Cases

Rate

Cases

Rate

Cases

Rate

Cases

Rate

Cases

Never
Past
Current
Unknown
Total
Never
Past
Current
Unknown
Total
Never
Past
Current
Unknown
Total

11
4.0
20
5.0
100
7.7
54
1.3
185
3.1
2
0.7
11
2.8
83
6.4
56
1.4
152
2.5
1
0.4
5
1.3
35
2.7
23
0.6
64
1.1
24,644

4
16
50
25
95
1
9
36
18
64
1
3
21
17
42

2.0
4.9
6.4
1.2
2.9
0.5
2.7
4.6
0.9
1.9
0.5
0.9
2.7
0.8
1.3

0
3
15
4
22
0
1
16
10
27
0
1
6
6
13

0.0
3.5
6.4
0.8
2.5
0.0
1.2
6.8
2.0
3.1
0.0
1.2
2.6
1.2
1.5

0
2
6
5
13
0
2
6
3
11
0
0
5
5
10

0.0
7.4
7.1
3.3
4.6
0.0
7.4
7.1
2.0
3.9
0.0
0.0
6.0
3.3
3.6

15
2.7
41
4.9
171
7.1
88
1.3
315
3.0
3
0.5
23
2.7
141
5.9
87
1.3
254
2.4
2
0.4
9
1.1
67
2.8
51
0.8
129
1.2
42,889

72
2.3
5
3.3
16
3.8
68
1.1
161
1.6
8
0.3
4
2.6
8
1.9
19
0.3
39
0.4
3
0.1
0
0.0
9
2.2
23
0.4
35
0.4
35,417

37
3
11
42
93
3
1
6
7
17
3
1
7
7
18

9.3
0.0
17.7
0.9
4.9
0.0
0.0
3.5
2.3
1.6
1.5
0.0
7.1
0.0
1.0

152
2.7
9
2.6
39
4.7
121
1.1
321
1.8
13
0.2
6
1.8
23
2.8
34
0.3
76
0.4
8
0.1
2
0.6
22
2.7
33
0.3
65
0.4
62,515

Never
Past
Current
Unknown
Total
Never
Past
Current
Unknown
Total
Never
Past
Current
Unknown
Total

13,436

panel) for lifetime never-smokers, smokers who havecontinuously smoked a pack (20 cigarettes) per day sinceage 20, and smokers who started smoking a pack per day at
age 20 and quit at age 50 (among unexposed people born in1915). Adenocarcinoma had the smallest smoking ERR, but
its incidence was still the highest of the three types amongsmokers of the same smoking history. While the smoking
ERRs were consistently higher for females than for males,
the absolute rates were higher among males than amongfemales for adenocarcinoma and squamous cell carcinoma,
but not for small cell carcinoma.
Radiation Effects

Radiation exposure significantly increased the risk foreach histological type. As shown in Table 4, the radiation
effect, expressed as the gender-averaged ERR per Gy (atage 70 for never-smokers exposed at age 30), was highest
for small cell carcinoma (1.49, 95% CI: 0.1–4.6), followedby those for adenocarcinoma (0.75, 0.3–1.3) and for

3,609
1.9
2.1
4.0
1.3
1.7
0.2
0.7
2.2
0.2
0.3
0.2
0.7
2.5
0.2
0.3

19,864

31
1
7
9
48
2
1
8
3
14
0
1
4
3
8

1,200
5.8
2.6
6.8
1.0
3.0
0.4
2.6
7.7
0.3
0.9
0.0
2.6
3.9
0.3
0.5

5772

12
0
5
2
19
0
0
1
5
6
2
0
2
0
4
1442

Rate

squamous cell carcinoma (0.27, 0.0–1.5). The large
radiation ERR for small cell carcinoma, however, had awide confidence interval due to the small number of cases
among never-smokers. There was no evidence of astatistically significant departure from the simple linear
dose response in any of the type-specific analyses.
The ERR/Gy tended to be higher among females thanamong males for both adenocarcinoma (female:male ratio ¼
7.9, P ¼ 0.01) and for squamous cell carcinoma (6.9, P ¼
0.01). For small cell carcinoma, however, radiation ERRs
were slightly, but not significantly, lower for women thanfor men (0.35, P ¼ 0.27). Given the smoking history, theradiation effect tended to decrease with increasing attained
age: rapidly and significantly for squamous cell carcinoma(P ¼ 0.03), but somewhat less rapidly and not significantly
for either adenocarcinoma (P ¼ 0.13) or for small cell
carcinoma (P ¼ 0.43). Age-specific radiation risks forsquamous cell carcinoma showed a rapid increase withincreasing age at exposure (P ¼ 0.01). However, there waslittle evidence of age at exposure effects for either

196

EGAWA ET AL.

TABLE 4
Parameter Estimates (95% CI) for Smoking Effects and Radiation Effects from a Generalized Multiplicative Model and AIC
Values for the Alternative Joint Effect Models
Smoking parameters
ERRa (male)
ERRa (female)
Birth year (percentage change per decade decrease)
Log (duration/50)
Log (duration/50)2
Log (years since quitting þ1)
Radiation parameters
ERR/Gyb (gender-averaged)
ERR/Gyb (male)
ERR/Gyb (female)
Female/male ratio
Age at exposure (percentage change per decade increase)
Attained age (power)
P for generalized interaction
AIC
Radiation only
Smoking only
Additive
Multiplicative
Generalized additive
Generalized multiplicative

Adenocarcinoma

Squamous cell

Small cell2.42 (1.4, 3.8)
3.41 (0.9, 7.3)
6.02 (25.1, 47)
1.58 (1.5, 5.5)
18.43 (41.3, 4.9)
0.39 (12.9, 0.2)

12.71 (4.8, 51.2)
21.12 (9.7, 44.7)
45.32 (3.7,104.2)
0.72 (2.5, 1)
2.27 (6.6, 0.4)
0.37 (0.7, 0.1)

17.51 (4.6, 112.4)
41.39 (16.8, 107.9)
40.24 (3.8, 103.9)
0.91(2.9, 0.7)
0.23 (4.4, 0.5)
0.59 (1.1, 0.3)

0.75 (0.3, 1.3)
0.17 (0.0, 0.8)
1.34 (0.6, 2.3)
7.94 (1.8, Inf)
8.74 (33, 72)
2.34 (5.3,0.8)
0.26

0.27 (0.0, 1.5)
0.07 (0.0, 0.7)
0.48 (0.0, 2.6)
6.89 (1.6, Inf)
212.4 (26, 3476)
8.91 (25.9, 0.7)
0.54

1.49 (0.1, 4.6)
2.21 (0.2, 7.6)
0.78 (0.0, 3.3)
0.35 (0.0, 2.3)
4.36 (48,221)
2.63(9.7, 4.6)
0.18

4714
4691
4666
4667
4668
4668

2762
2630
2618
2617
2622
2619

1941
1854
1848
1850
1852
1850

a

Risk at age 70 for an unexposed person who was born in 1915 and smoked a pack of cigarettes per day for 50 years since age 20.
Risk for a never-smoker at age 70 after an exposure at 1 Gy at age 30.

badenocarcinoma (P . 0.5) or small cell carcinoma (P .
0.5). Alternatively, we fitted a model with the radiation
ERR replacing both attained age and age at exposure withtime since exposure only. For each type, as well as all lungcancers combined, these models showed a slight improvement in AIC, with risk estimates little affected, indicatingthat the time dependent variation of the radiation risk might
be more parsimoniously explained by a risk decrease withtime since exposure only (not shown).
Smoking-Radiation Joint Effects

Figure 2 presents two summaries of estimated radiation
ERRs/Gy as a function of smoking intensity. The upper
panel presents gender-averaged ERRs/Gy relative to thosefor unexposed people with the same smoking history under
the four interaction models and the lower panel presents
gender-averaged and gender-specific ERRs/Gy relative tothose for unexposed never-smokers under the generalized
multiplicative model. These were all computed as the risks
at age 70 for those who were exposed at age 30 and smokeda fixed number of cigarettes per day since age 20.
Although inclusion of the generalized interaction termx(S) did not significantly improve the fit over the simple
interactions in any of the type-specific analyses, the fitted
curves in Fig. 2 suggest that, given the duration of smoking,the nature of the variation in the ERR/Gy with smoking
intensity might be similar across the three histologicalgroups. As the smoking intensity increased, the ERR/Gytended to increase relatively rapidly (up to about 10
cigarettes per day) and then decrease toward no radiationassociated excess risk (at 20 or more cigarettes per day).
This trend was most evidently demonstrated in analysis forsmall cell carcinoma. Similar patterns were observed for the
not otherwise specified group and the three major types as agroup (see Supplementary Material: http://dx.doi.org/10.
1667/RR2819.1.S1, Fig. S2) and for both of these groups,
the generalized models described the data markedly better
than simple additive or multiplicative models (see Supplementary Material: http://dx.doi.org/10.1667/RR2819.1.
S1,Table S4).
Table 5 summarizes the distribution of observed and fitted
cases over dose categories for the generalized multiplicativemodel. The fitted cases are broken down into baseline cases,
excess cases associated with radiation exposure, smoking,or radiation-smoking interaction, and among those with nosmoking data over predictions for unexposed never-smokers
in the same dose group. About 26% (111 of 427 cases) of
the cases among subjects with smoking history data
appeared to be associated with smoking for adenocarcinoma, while this proportion was much higher for squamouscell carcinoma (81%; 170 of 209) and for small cell
carcinoma (84%; 92 of 110). About 7% of the adenocarcinoma cases, 3% of the squamous cell carcinoma cases,
and 4% of the small cell carcinoma cases appeared to be
associated with radiation exposure; this proportion increased to 56%, 26% and 22%, respectively, among theLUNG CANCER INCIDENCE BY HISTOLOGICAL TYPES

197

FIG. 1. Age- and gender-specific absolute rate (upper panel) and excess relative risk of smoking (lower panel). Solid curves are for smokers
who started at age 20 and never stopped. The dotted curves are for past smokers who started at age 20 and stopped at age 50. The dashed curves
are for lifetime never-smokers. The curves correspond to risk for an unexposed person born in 1915.

highest dose category (.1 Gy). Excess cases associatedwith the radiation-smoking interaction accounted for 1–3%of the cases with known smoking history for each type andabout 10% of the radiation-associated cases for adenocarcinoma, 53% for squamous cell carcinoma and 44% forsmall cell carcinoma. Regardless of the type of interaction,
the total estimated numbers of smoking-associated cases
were generally similar for each type but the model with nosmoking adjustment provided the largest estimate ofradiation-related excess cases.
DISCUSSION

It has been recognized that the association between
smoking and lung cancer incidence varies by histologicaltype (25–28). Our analyses demonstrated that smoking
ERRs were markedly higher for small cell carcinoma (18/41
per 50 pack-years for men/women born in 1915) andsquamous cell carcinoma (13/21) than for adenocarcinoma(2.4/3.4). These results were comparable to the risk
estimates reported in another large Japanese cohort study(29). For each of the three histological types, and all lungcancers as a group, the estimated smoking risks appeared tobe smaller than those reported for Western populations (1,18). As suggested by the ‘‘smoking-only’’ excess caseestimates (Table 5), histology-type differences in excess
cases were not as marked as those in the ERRs with thelargest increases for squamous cell carcinoma and thesmallest increases for small cell carcinoma.
Previous studies of radiation effects by lung cancer
histological type have provided rather inconsistent results.
Prior studies among atomic bomb survivors (30–32) werebased on limited numbers of cases diagnosed histopathologically by means of autopsies, surgical resections, or
biopsies. Land et al. noted that radiation-induced cancers
appeared more likely to be small cell carcinoma and lesslikely to be adenocarcinoma both in atomic bomb survivors(exposed predominately to penetrating c rays) and anothercohort of American uranium miners (exposed to low-energy
a particles with low entrance) (30). In studies of radiationtreated patients, the largest ERRs/Gy were seen for
adenocarcinoma and large-cell carcinoma among Hodgkin’s
disease patients (13), while squamous cell carcinoma was
the most closely related to radiotherapy among breast cancer

198

EGAWA ET AL.

FIG. 2. Excess relative risk at 1 Gy as a function of smoking intensity, relative to unexposed smokers with the same smoking history (upper
panel) and to unexposed non-smokers (lower panel). The curves correspond to risk at age 70, for one exposed at age 30 who smoked a pack/day
for 50 years since age 20. In the upper panel, gender-averaged risks were plotted for each fitted interaction model. In the lower panel, the genderaveraged and gender-specific risks were plotted for the generalized multiplicative model. All points are categorical estimates of the ERRs (with
95% confidence intervals in the upper panel) based on a generalized multiplicative model in which smoking intensity categories replaced thelinear-quadratic function of log intensity.

patients with a significant effect only among smokers (33).
In a Swedish case-control study of residential-radon
exposure and lung cancer, stronger associations withincreasing levels of residential-radon exposure were suggested for small cell carcinoma and adenocarcinoma thanfor squamous cell carcinoma (9), while a larger excess odds
ratio was observed for small cell carcinoma than for
adenocarcinoma and squamous cell carcinoma in a
combined analysis of seven case-control studies in North
America (11). In our study, conducting formal tests
comparing ERRs across types was difficult in the presenceof relatively strong modification of radiation effects bysmoking levels. However, visual inspection of Fig. 2, as
well as ERR/Gy coefficient estimates in Table 4, suggeststhat the relative effect of radiation might be larger for small
cell carcinoma and adenocarcinoma than for squamous cell
carcinoma in the LSS.
It has been previously noted that the age-specificradiation-associated excess risk for lung cancers tends toincrease with increasing age at exposure in the LSS (6, 15).
Our type-specific analyses suggest that this increase could
be largely due to that for squamous cell carcinoma. The
possibility of non-decreasing patterns of radiation-associated cancer risks with increasing age-at-exposure has been amatter of recent interest (34–36). Using a biologically-basedmodel that allows radiation to act as both an initiator and a
promoter of lung cancer, Shuryak et al. suggested thatvariations in the age at exposure pattern for different cancer
types might be explained by differences in the relative
importance of initiation and promotion effects of the
exposure (36). In this context, our findings suggest that
promotion (or late stage) effects of radiation might be more
important for lung cancer, particularly squamous cell
carcinoma, than they are for many other types of solidcancers.
To our knowledge, this is the first epidemiological study
to quantify the joint interaction effects of radiation andsmoking on lung cancers of different histological types. For

199

LUNG CANCER INCIDENCE BY HISTOLOGICAL TYPESTABLE 5Observed and Fitted Cases by Dose Category for the Generalized Multiplicative Model with Totals for Alternative Models

Model
Adenocarcinoma
Generalized multiplicative model

Radiation only model
Additive modelMultiplicative model
Generalized additive model
Squamous cell carcinoma
Generalized multiplicative model

Radiation only model
Additive modelMultiplicative model
Generalized additive model
Small cell carcinoma
Generalized multiplicative model

Radiation only model
Additive modelMultiplicative model
Generalized additive model

Dose (Gy)

Excess cases
Total
Total
radiation smoking
Baseline Radiation Radiation Smoking Unknown
only and smoking only
smoking Total excess excess
Cases (no smoking),0.005346
0.005–0.2 188
0.2–1
70
1þ
32
Total
636

,0.005191
0.005–0.2 81
0.2-1
41
1þ
17
Total
330

,0.005990.005–0.2 60
0.2-1
21
1þ
14
Total
194

271.3
146.4
41.6
11.2
470.5
586.0
465.5
474.1
465.1

0.2
7.0
18.6
16.5
42.3
50.0
48.0
43.2
43.5

34.6
19.6
5.6
1.5
61.3
310.0
63.2
63.0
61.8

0.0
0.9
2.2
1.7
4.9
20.0
14.0
4.8
13.8

14.2
7.9
2.3
0.6
24.9
174.9
22.6
28.2
22.2

0.0
0.6
1.6
1.7
3.9
19.1
14.5
2.2
15.6

all lung cancers as a group, many previous reports
concluded that the interaction could be more multiplicative
than additive (8, 9, 12, 13). Our type-specific analyses did
not conclusively identify the type of interaction, in contrast
to our previous analysis pooling all lung cancers (15) inwhich the generalized multiplicative model fit statistically
better than the multiplicative model or additive model.
However, despite the lack of statistical significance, ouranalyses suggest that the type-specific radiation effects
might share a complex dependence on smoking intensity
like that seen in the pooled analysis. Specifically, the effectof a given radiation dose tends to be larger for moderatesmokers than for heavier smokers given the duration ofsmoking. The slight variations in this pattern observed
among different histological types seem to reflect thedifferences in the strength of association with smoking orradiation. The lung cancer not otherwise specified groupmay be mostly a collection of the three major types, withsome unknown numbers of metastatic cancer misclassified
as lung cancer. It is of interest to note that the interaction
pattern seen for this group is similar to that for all three
types of lung cancer combined. The reductions in radiationassociated risk with increasing smoking intensity might be

0.0
0.7
2.2
1.6
4.5

60.6
31.6
10.7
3.5
106.3

6.6
3.9
1.3
0.4
12.3

67.4
43.2
32.8
22.0
165.5

0.0
3.8
4.4

107.2
103.8
106.7

15.3
11.0
16.3

170.5
161.9
170.9

0.0
0.7
2.3
2.7
5.7

92.1
50.3
17.0
5.1
164.6

51.9
26.8
10.2
4.7
93.5

144.0
78.7
31.7
14.2
268.7

0.0
4.3
2.6

168.3
165.2
166.4

84.6
92.8
85.5

266.8
267.0
268.2

0.0
0.4
1.4
1.4
3.1

48.6
27.4
9.6
3.0
88.6

39.2
19.9
8.8
5.4
73.5

87.8
48.3
21.4
11.5
169.1

0.0
7.8
0.7

88.6
83.2
88.8

68.3
72.6
68.2

171.4
165.8
171.8

0.2
7.7
20.8
18.1
46.8
50.0
48.0
47.0
47.9

60.6
32.3
12.9
5.1
110.8
107.2
107.6
111.0

0.0
1.6
4.5
4.4
10.6
20.0
14.0
9.1
16.3

92.1
51.0
19.3
7.8
170.3

0.0
1.0
3.0
3.1
7.0
19.1
14.5
10.0
14.9

48.6
27.8
11.0
4.4
91.7

168.3
169.5
168.9

88.6
91.0
88.1

related to the inverse exposure rate effect in the smokingassociated lung cancer risks that is seen in the LSS and otherpopulations (15, 37); namely, smoking at a lower intensity
for a longer duration tends to be more deleterious thansmoking at a higher intensity for a shorter duration.
Potential explanations for this leveling-off include intensity-dependent molecular mechanisms and nicotine-related
smoking behavioral factors (37). Our findings suggest thatradiation might contribute most markedly to lung cancer
risks in smokers of intensities at which the intensitydependent modification of the smoking effects is the largest.
With largely complete cancer ascertainment, long-term
follow up of a large cohort of men and women of all ages,
and of detailed smoking information, the LSS cohort is an
excellent resource for the study of the joint effect ofradiation and smoking on lung cancer risks. However, theLSS data have some limitations, particularly with regard to
the completeness of the smoking data. In the analyses weassumed that people’s smoking habits had not changed
since the last time they provided information on smoking,which was no later than 1992. In view of the age of thecohort members it is unlikely that many have begun tosmoke in recent years, but it is likely that many have quit

200

EGAWA ET AL.

smoking. This will possibly lead to some downward bias inestimates of the effect of smoking cessation, but how this
impacts estimates of radiation effects is unclear. In addition,
despite the size of the cohort and the relatively large numberof cases, the amount of information relevant to inference
about the nature of the radiation-smoking interaction was
still limited due to the highly skewed dose distribution andthe unavailability of histology information for about 30% of
the cases. Furthermore, the smaller relative risks associatedwith smoking in Japan make it challenging to apply the
results to non-Japanese populations.
In summary, our analyses of the LSS demonstrated thatboth smoking and radiation significantly increased the risks
for the three major types of lung cancer (AC, SqCC and
SmCC). Despite some variation in magnitude of the main
effects of smoking and radiation among the types, all ofthese lung cancer types shared a relatively consistent pattern
for the smoking-radiation interaction; radiation effects
tended to be largest for those who smoked modest amounts
and much lower for heavy smokers. This pattern might berelated to the inverse exposure-rate pattern generally
observable for smoking-related cancer risks. Our findings
provide information on smoking effects for various types oflung cancer in Japan and contribute to the sparse literatureon the radiation-smoking interaction effects on lung cancer
histological type.
ACKNOWLEDGMENTS
This work was supported by the Radiation Effects Research Foundation(RP1-94), Hiroshima and Nagasaki, Japan, and the U.S. National Cancer
Institute intramural research program (NO2CP-2009-00005). The
Radiation Effects Research Foundation is a private nonprofit foundation
funded by the Japanese Ministry of Health, Labour and Welfare and the
U.S. Department of Energy, the latter in part through the National
Academy of Sciences.
Received: October 7, 2011; accepted: March 21, 2011; published online:
August 3, 2012

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