1 

DIFFERENCES IN THE ESTIMATION OF LUNG CANCER RISK 

BETWEEN NIOSH-IREP AND NIH-IREP 

A. Iulian Apostoaei and John R. Trabalka 

SENES Oak Ridge, Inc. 

Center for Risk Analysis 

102 Donner Dr. 

Oak Ridge, TN 37830 

September 20, 2004 

Introduction

In May 2003, the National Cancer Institute updated the lung model in their version of IREP (i.e., 

NIH-IREP), based on the recently published re-analysis of lung cancer incidence in A-bomb 

survivors (Pierce et al. 2003). To date, NIOSH-IREP has not been updated to reflect the recent 

study by Pierce et al. (2003). Significant differences are observed between the probability of 

lung cancer causation estimated with NIH and NIOSH versions of IREP. This paper summarizes 

these differences and identifies their sources. 

Approaches for Modeling the Risk of Lung Cancer in NIH and NIOSH Versions of IREP

The approach for estimating the risk of lung cancer in NIH-IREP is described by Land et al. 

(2003) and reproduced in Appendix A of this document. The handling of lung cancer in NIOSHIREP is described in the May 17, 2002, Draft Report of the NCI-CDC Working Group to Revise 

the 1985 NIH Radioepidemiological Tables (Land et al., 2002), as mentioned in the NIOSHIREP Technical Documentation Final Report (NIOSH 2002, p. 35). A description of the 

NIOSH-IREP approach for lung cancer is given in Appendix B of this document. 

The major changes incorporated into NIH-IREP that are not currently reflected in NIOSH-IREP 

are discussed below and they are summarized in Table 1. 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

2

• The risk model in NIH-IREP is based on the analysis of lung cancer incidence and smoking 

history among the A-bomb survivors by Pierce et al. (2003). This analysis includes more 

follow-up years of the Japanese A-bomb survivors (1950-1994) as compared to the NIOSHIREP lung model, which is based on a follow-up period from 1950 to 1990. 

• The most important feature of the NIH lung model1, based on the results reported by Pierce 

et al. (2003), is dependency on age at exposure and attained age of the ERR/Sv (see Appendix 

A). No age-dependency is included in NIOSH-IREP lung model2 (see Appendix B). 

• The likelihood profile distribution for the main model parameter α was derived so that the 

model could be applied to estimate the statistical uncertainty distribution of the ERR/Sv for 

lung cancer. The approach to uncertainty analysis was employed in the interests of 

improving the computational speed of IREP in both the NIOSH and NIH versions, and it is 

applied in both NIOSH and NIH version of IREP for cancers other than lung. In this 

approach, the uncertainty evaluation was based on the assumption that the estimated value of 

model parameter α was independent of β, γ, and δ. The details of the approach (designated 

Approach 2) are described for NIOSH-IREP on page 27 of Land et al. (2002) and for NIHIREP on page 26 of the report by Land et al. (2003). 

In particular, for NIH-IREP, α is the ERR/Sv for age at exposure 30 and attained age 50, for 

a never smoker. In NIOSH-IREP, α is the ERR/Sv for any age at exposure or attained age 

and is an average over all smoking categories. 

• In NIH-IREP, one profile for α is provided and sex differences are specified using parameter 

β, while in NIOSH-IREP, α is pre-calculated for each sex. The likelihood profile for 

parameter α used in computation of statistical uncertainty for the ERR/Sv for lung cancer in 

never smokers in NIH-IREP is reproduced in Appendix A (Table A.1 and Fig. A.1). The 

 

1 ERR=αDexp[βs+γf(e)+δg(a)], where α,β,γ,δ are parameters, D is radiation dose, and s, f(e), and g(a) describe 

dependency on sex (s), age at exposure (e) and attained age (a). (see Appendix A). 2 ERR=α(s)D, where α is a sex-specific parameter, and D is radiation dose. There is no dependency on age at 

exposure (e) and attained age (a) (γ = δ = 0). (see Appendix B). 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

3

tabulated profile for α is the midway between the values for the two sexes. By contrast, in 

NIOSH-IREP, separate profiles for α are provided for males and females (see Appendix B, 

Table B1 and Fig. B.1). 

• The interaction of smoking and exposure to low-level radiation in the 1985 NIH report was 

based on an additive model that makes use of smoking-related adjustment factors. These 

factors are based on relative risks for lung cancer by smoking category given by Rogot and 

Murray (1980) and the distribution of the U.S. population by smoking status in 1964–1965. 

However, the factors used in both the NIH and NIOSH versions of IREP were updated using 

1993 information on smoking status distribution provided in a 1993 CDC report (CDC 1995). 

The revised factors (WS*) for additive interaction based on the updated distribution for US 

smoking status are given in Appendix A for NIH-IREP (Table A.3) and in Appendix B for 

NIOSH-IREP (Table B.2). The same factors are used in both NIH and NIOSH versions of 

IREP, but they are applied differently to scale the risk for different smoking categories. 

Thus, in NIOSH-IREP the factors are applied accounting for the fact that parameter α is an 

average for all smoking categories, while in NIH-IREP the factors are applied accounting for 

the fact that parameter α is for never smokers. 

• A similar mathematical approach is being used in both NIOSH and NIH versions of IREP to 

implement the interaction between smoking and radiation exposure. The approach 

(reportedly guided by BEIR VI findings for radon-related lung cancer risk; see page 41 in 

Land et al. 2003) consists of multiplying the calculated ERR/Sv by the term: 

[x + (1 – x)WS*], where WS* is the updated smoking adjustment factor described in the 

previous bullet and x is assumed to follow a triangular distribution (0, 1, 1.1). This 

uncertainty distribution for x allows the ERR/Sv for lung cancer to range from that obtained 

with an additive interaction (x = 0) to that obtained with a multiplicative interaction (x = 1), 

with a probability of about 0.10 for a super-multiplicative interaction (x > 1). This 

adjustment factor is heavily weighted towards the multiplicative interaction model. 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

4

In NIH-IREP, an additional weight is assigned to the additive model based on the more recent 

analysis of Pierce et al. (2003), which indicates that the radiation-smoking interaction among 

the A-bomb survivors is more nearly additive than that estimated for uranium miners. This 

additional weight to the additive interaction model is applied for exposure to all radiations 

types other than alpha radiation. That is, in current version of NIH-IREP, for exposure to all 

radiations types other than alpha radiation, the uncertainty model for the radiation-smoking 

interaction places a 50% probability on the purely additive model (x ≡ 0) and 50% on the 

assumed triangular distribution described in the preceding paragraph (which is weighted 

towards the multiplicative model). For exposure to alpha emitters, only the triangular 

distribution (which is weighted toward the multiplicative model) is used. This is consistent 

with the finding that radiation-smoking interaction is more nearly additive for the A-bomb 

survivors, but more nearly multiplicative for uranium miners (who where exposed mainly to 

alpha particles). In NIOSH-IREP, which was released before the results of Pierce et al. 

(2003) were implemented in NIH-IREP, additional weight to the additive model is not 

considered for exposure to low LET radiation types. 

Numerical Comparisons Between Probability of Causation for Lung Cancer Estimated by 

NIH and NIOSH versions of IREP

Differences between the 99th percentiles of the probability of causation (PC) for different 

smoking categories and different radiation types produced using NIH-IREP and NIOSH-IREP 

are compared in Tables 2, 3 and 4. Table 2 shows that, for exposure at age 20 and diagnosis at 

age 40, NIH-IREP is almost always more claimant-friendly. Table 3 however, shows that, for 

exposure at age 40 and diagnosis at age 60, NIOSH-IREP is more claimant-friendly for never 

smokers and light smokers (< 10 cigs/day) for both acute and chronic exposures, while for 

moderate to heavy smokers, the two codes produce fairly similar values of PCs (at the upper 99th

percentile). Table 4 provides PC estimates for a male exposed at age 20 and diagnosed at age 40. 

In this case NIOSH-IREP is more claimant friendly only for never smokers. For any other 

smoking status, NIH-IREP produces larger PCs than NIOSH-IREP for the same exposure 

conditions. 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

5

The effect of age at exposure and attained age for both males and females is investigated in more 

depth in Figures 1-8, for selected smoking categories. Comparison of the upper 99th percentile of 

the estimated PCs, NIOSH-IREP seems to be more claimant-friendly for never smokers. 

However, NIH-IREP produces larger upper 99th percentiles of PC for smokers for the majority of 

exposure conditions investigated, other than females who were exposed at older ages. The 

reason why NIH-IREP is more claimant friendly to smokers than to non-smokers is due to the 

larger uncertainty associated with the estimate of ERR at 1 Sv for all smoking categories. 

Figure 9 compares the PCs for males and females, for different smoking categories. A single 

acute exposure of 75 cSv was assumed to have taken place at age 20, with cancer diagnosed at 

age 60. Both NIOSH-IREP and NIH-IREP indicate that females are more sensitive than males, 

but the differences between the upper 99th percentiles of PC for the two genders is always larger 

in NIOSH-IREP. For males and females, NIOSH-IREP produces higher PCs than NIH-IREP 

only for never smokers. 

The magnitude of uncertainties in the estimated PCs is larger in NIOSH-IREP than in NIH-IREP 

for never smokers only. For all other smoking categories, NIH-IREP produces larger uncertainty 

ranges than NIOSH-IREP. The increased magnitude of the uncertainty for all smoking 

categories in NIH-IREP comes from the uncertain smoking adjustment factors that are applied to 

the parameter α specified for never-smoker (Table 1). The additional 50% weight to the additive 

model in NIH-IREP has the tendency to reduce the risk estimates and thus the PCs. This 

tendency is observed in the lower and central estimates (i.e. 50th percentile) of the PCs estimated 

with NIH-IREP, for all smoking categories (Figure 1-8). However, the upper bound of the risk 

estimates in NIH-IREP is still given by the multiplicative model, for which a substantial weight 

is still assigned [50% weight is assigned to the triangular distribution (0, 1, 1.1)] 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

6

Conclusions

The differences between the lung cancer models in the NIH and NIOSH versions of IREP appear 

to be quite significant. NIOSH-IREP is more claimant-friendly for never smokers and for 

females who were exposed at older ages. NIH-IREP is more claimant-friendly for male smokers, 

and for females smokers exposed at younger ages. 

Our recommendation to NIOSH is to update the lung model in NIOSH-IREP because the new 

lung model represents the most advanced state of knowledge about radiation-induced lung 

cancer. As opposed to the NIOSH-IREP lung model, which is based on the analysis of the 1950-

1990 data from the Japanese A-bomb survivors, the newer NIH lung model includes more 

follow-up years of the Japanese cohort (1950-1994; Pierce et al., 2003). Also, in perhaps more 

than half of the possible exposure situations the NIH lung model is more claimant-friendly. 

Since there are categories of people for whom the NIH-IREP lung model is less friendly, NIOSH 

could consider programming NIOSH-IREP to choose between the new NIH-IREP lung model 

and the current NIOSH-IREP lung model, and report whatever PC is larger for a given exposure 

situation (i.e., to "grandfather" the current NIOSH-IREP lung model). 

Other experts Who Can Evaluate the Lung Models in NIH and NIOSH Versions of IREP

Individuals who might be consulted to provide a formal evaluation of the significance of the 

differences include: Ethel Gilbert, Charles Land, Jay Lubin, and Kiyohiko Mabuchi of NCI; 

Donald Pierce of RERF; Jerome S. Puskin and David J. Pawel of EPA-ORIA, Radiation 

Protection Division, John Boice, International Epidemiology Institute; David Brenner of 

Columbia University; Roy Shore, NYU; Faith Davis, U. of Illinois; Jonathan Samet, Johns 

Hopkins U; David Richardson, U. of South Carolina. 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

7

References

Centers for Disease Control and Prevention (CDC). 1995. Morbidity and Mortality Weekly 

report: Cigarette Smoking Among Adults – United States, 1993; Excerpted in JAMA 1995; 

273(5):369-370. 

Land, C. E., Gilbert, E. S., Smith, J. M., Hoffman, F. O., Apostoaei, I., and Thomas, B. 2002. 

Draft Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological 

Tables. May 17, 2002. U.S. Department of Health and Human Services, National Institutes of 

Health, National Cancer Institute, Bethesda, MD. 

Land, C. E., Gilbert, E. S., Smith, J. M., Hoffman, F. O., Apostoaei, I., Thomas, B., and Kocher, 

D. C. 2003. Report of the NCI-CDC Working Group to Revise the 1985 NIH 

Radioepidemiological Tables. NIH Publication No. 03-5387. U.S. Department of Health and 

Human Services, National Institutes of Health, National Cancer Institute, Bethesda, MD. 

Pierce, D. A., Sharp, G. B., and Mabuchi, K. 2003. Joint effects of radiation and smoking on 

lung cancer risk among atomic bomb survivors. Radiat. Res. 159, 511–520. 

Rogot, E., and Murray, J. L. 1980. Smoking and causes of death among U.S. veterans: 16 years 

of observation. Public Health Rep. 95:213–222. 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

8

Table 1. Summary of differences in estimation of lung cancer risk 

between the NIOSH and NIH versions of IREP 

Areas NIOSH-IREP NIH-IREP 

Risk model • No age dependency (parameters γ and 

δ ≡ 0 under all conditions) 

• Age dependency (γ ≠ δ ≠ 0 under all 

conditions) 

• Values of parameters based on 

analysis by Pierce et al. (2003), 

including adjustment for smoking 

Parameter 

uncertainty 

• Sex-specific likelihood profiles for 

parameter α (given as an average over 

all smoking categories) 

• Sex-adjusted likelihood profiles for 

parameter α (given for never smokers) 

Radiation- 

 smoking 

 interaction 

• [x + (1 – x)WS*], where x is always 

described as a triangular distribution 

(0, 1, 1.1). Multiplicative model has a 

heavier weight than the additive 

model. 

• [x + (1 – x)WS*], 50% weight to case 

where x follows a triangular 

distribution (0, 1, 1.1), and 50% 

weight to case where x ≡ 0 (additive 

model). 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

9

Table 2. Comparison of 99th percentiles of assigned shares (probability of causation) for lung cancer 

calculated by the NIH and NIOSH versions of IREP for single doses of 50 cSv 

to a male age 20 at exposure and age 40 at diagnosis 

Acute exposure Chronic exposure

Photons >250 kev Photons >250 kev Alpha Electrons <15 kev 

Smoking 

status NIH NIOSH NIH NIOSH NIH NIOSH NIH NIOSH 

Never smoker 52.94 53.75 53.66 50.97 74.99 70.73 78.22 76.81 

Current smoker 

< 10 cigs/day 48.31 29.53 45.81 29.98 71.85 52.69 71.62 55.83 

10-19 cigs/day 47.91 25.62 44.78 25.35 70.76 47.34 70.88 50.85 

20–39 cigs/day 47.78 25.00 44.45 24.57 70.58 45.61 70.74 49.96 

40+ cigs/day 47.72 24.92 44.32 24.15 70.50 45.54 70.70 49.77 

Table 3. Comparison of 99th percentiles of assigned shares (probability of causation) for lung cancer 

calculated by the NIH and NIOSH versions of IREP for single doses of 50 cSv 

to a male age 40 at exposure and age 60 at diagnosis 

Acute exposure Chronic exposure

Photons >250 kev Photons >250 kev Alpha Electrons <15 kev 

Smoking 

status NIH NIOSH NIH NIOSH NIH NIOSH NIH NIOSH 

Never smoker 28.79 53.75 30.94 50.97 54.03 70.73 57.95 76.81 

Current smoker 

< 10 cigs/day 26.51 29.53 24.56 29.98 49.63 52.69 49.02 55.83 

10-19 cigs/day 25.94 25.62 23.57 25.35 48.97 47.34 48.85 50.85 

20–39 cigs/day 25.88 25.00 23.47 24.57 48.86 45.61 48.35 49.96 

40+ cigs/day 25.85 24.92 23.35 24.15 48.82 45.54 47.78 49.77 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

10

Table 4. Comparison of 99th percentiles of assigned shares (probability of causation) for lung cancer 

calculated by the NIH and NIOSH versions of IREP for single doses of 50 cSv 

to a male age 20 at exposure and age 60 at diagnosis 

Acute exposure Chronic exposure

Photons >250 kev Photons >250 kev Alpha Electrons <15 kev 

Smoking 

status NIH NIOSH NIH NIOSH NIH NIOSH NIH NIOSH 

Never smoker 44.34 53.75 44.60 50.97 67.76 70.73 71.31 76.81 

Current smoker 

< 10 cigs/day 39.66 29.53 37.21 29.98 64.21 52.69 64.07 55.83 

10-19 cigs/day 39.22 25.62 35.96 25.35 63.08 47.34 63.35 50.85 

20–39 cigs/day 39.17 25.00 35.80 24.57 62.87 45.61 63.12 49.96 

40+ cigs/day 39.13 24.92 35.78 24.15 62.79 45.54 63.02 49.77 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

11

0

10

20

30

40

50

60

70

80

90

100

10 15 20 25 30 35 40 45

Male, never smoker

Probability of causation [%]

Age at exposure

NIOSH-IREP

Cancer diagnosed at age 60

0

10

20

30

40

50

60

70

80

90

100

30 35 40 45 50 55 60 65

Probability of causation [%]

Attained age

NIOSH-IREP

Exposure at age 20

Fig. 1 Probability of lung cancer causation for never-smoker males for different ages at 

exposure and attained ages, from exposure to a constant dose of high-energy 

photons. The horizontal dashed and solid lines represent the probability of 

causation (PC) estimated by NIOSH-IREP, while the vertical lines and solid 

circles represent the PC obtained using NIH-IREP. The upper bounds of all the 

distributions represent the 99th percentile of each estimated PC. The magnitude of 

the lung dose is chosen so that upper 99th percentile of the PC estimated using 

NIOSH-IREP is 50%. The lower bounds represent the 1st percentile of PC. The 

horizontal solid line and the solid circles represent the 50th percentiles of PC. 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

12

0

10

20

30

40

50

60

70

80

90

100

10 15 20 25 30 35 40 45

Female, never smoker

Probability of causation [%]

Age at exposure

NIOSH-IREP

Cancer diagnosed at age 60

0

10

20

30

40

50

60

70

80

90

100

30 35 40 45 50 55 60 65

Probability of causation [%]

Attained age

NIOSH-IREP

Exposure at age 20

Fig. 2 Probability of lung cancer causation for never-smoker females for different ages at 

exposure and attained ages, from exposure to a constant dose of high-energy 

photons. The horizontal dashed and solid lines represent the probability of 

causation (PC) estimated by NIOSH-IREP, while the vertical lines and solid 

circles represent the PC obtained using NIH-IREP. The upper bounds of all the 

distributions represent the 99th percentile of each estimated PC. The magnitude of 

the lung dose is chosen so that upper 99th percentile of the PC estimated using 

NIOSH-IREP is 50%. The lower bounds represent the 1st percentile of PC. The 

horizontal solid line and the solid circles represent the 50th percentiles of PC. 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

13

0

10

20

30

40

50

60

70

80

90

100

10 15 20 25 30 35 40 45

Male, 10-19 cigs/day

Probability of causation [%]

Age at exposure

NIOSH-IREP

Cancer diagnosed at age 60

0

10

20

30

40

50

60

70

80

90

100

30 35 40 45 50 55 60 65

Probability of causation [%]

Attained age

NIOSH-IREP

Exposure at age 20

Fig. 3 Probability of lung cancer causation for males smoking between 10 and 19 

cigs/day for different ages at exposure and attained ages, from exposure to a 

constant dose of high-energy photons. The horizontal dashed and solid lines 

represent the probability of causation (PC) estimated by NIOSH-IREP, while the 

vertical lines and solid circles represent the PC obtained using NIH-IREP. The 

upper bounds of all the distributions represent the 99th percentile of each estimated 

PC. The magnitude of the lung dose is chosen so that upper 99th percentile of the 

PC estimated using NIOSH-IREP is 50%. The lower bounds represent the 1st

percentile of PC. The horizontal solid line and the solid circles represent the 50th

percentiles of PC. 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

14

0

10

20

30

40

50

60

70

80

90

100

10 15 20 25 30 35 40 45

Female, 10-19 cigs/day

Probability of causation [%]

Age at exposure

NIOSH-IREP

Cancer diagnosed at age 60

0

10

20

30

40

50

60

70

80

90

100

30 35 40 45 50 55 60 65

Probability of causation [%]

Attained age

NIOSH-IREP

Exposure at age 20

Fig. 4 Probability of lung cancer causation for females smoking between 10 and 19 

cigs/day for different ages at exposure and attained ages, from exposure to a 

constant dose of high-energy photons. The horizontal dashed and solid lines 

represent the probability of causation (PC) estimated by NIOSH-IREP, while the 

vertical lines and solid circles represent the PC obtained using NIH-IREP. The 

upper bounds of all the distributions represent the 99th percentile of each estimated 

PC. The magnitude of the lung dose is chosen so that upper 99th percentile of the 

PC estimated using NIOSH-IREP is 50%. The lower bounds represent the 1st

percentile of PC. The horizontal solid line and the solid circles represent the 50th

percentiles of PC. 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

15

0

10

20

30

40

50

60

70

80

90

100

10 15 20 25 30 35 40 45

Male, 40+ cigs/day

Probability of causation [%]

Age at exposure

NIOSH-IREP

Cancer diagnosed at age 60

0

10

20

30

40

50

60

70

80

90

100

30 35 40 45 50 55 60 65

Probability of causation [%]

Attained age

NIOSH-IREP

Exposure at age 20

Fig. 5 Probability of lung cancer causation for males smoking more than 40 cigs/day for 

different ages at exposure and attained ages, from exposure to a constant dose of 

high-energy photons. The horizontal dashed and solid lines represent the 

probability of causation (PC) estimated by NIOSH-IREP, while the vertical lines 

and solid circles represent the PC obtained using NIH-IREP. The upper bounds of 

all the distributions represent the 99th percentile of each estimated PC. The 

magnitude of the lung dose is chosen so that upper 99th percentile of the PC 

estimated using NIOSH-IREP is 50%. The lower bounds represent the 1st

percentile of PC. The horizontal solid line and the solid circles represent the 50th

percentiles of PC. 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

16

0

10

20

30

40

50

60

70

80

90

100

10 15 20 25 30 35 40 45

Female, 40+ cigs/day

Probability of causation [%]

Age at exposure

NIOSH-IREP

Cancer diagnosed at age 60

0

10

20

30

40

50

60

70

80

90

100

30 35 40 45 50 55 60 65

Probability of causation [%]

Attained age

NIOSH-IREP

Exposure at age 20

Fig. 6 Probability of lung cancer causation for females smoking more than 40 cigs/day

for different ages at exposure and attained ages, from exposure to a constant dose 

of high-energy photons. The horizontal dashed and solid lines represent the 

probability of causation (PC) estimated by NIOSH-IREP, while the vertical lines 

and solid circles represent the PC obtained using NIH-IREP. The upper bounds of 

all the distributions represent the 99th percentile of each estimated PC. The 

magnitude of the lung dose is chosen so that upper 99th percentile of the PC 

estimated using NIOSH-IREP is 50%. The lower bounds represent the 1st

percentile of PC. The horizontal solid line and the solid circles represent the 50th

percentiles of PC. 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

17

0

10

20

30

40

50

60

70

80

90

100

10 15 20 25 30 35 40 45

Male, former smoker

Probability of causation [%]

Age at exposure

NIOSH-IREP

Cancer diagnosed at age 60

0

10

20

30

40

50

60

70

80

90

100

30 35 40 45 50 55 60 65

Probability of causation [%]

Attained age

NIOSH-IREP

Exposure at age 20

Fig. 7 Probability of lung cancer causation for former smoker males for different ages at 

exposure and attained ages, from exposure to a constant dose of high-energy 

photons. The horizontal dashed and solid lines represent the probability of 

causation (PC) estimated by NIOSH-IREP, while the vertical lines and solid 

circles represent the PC obtained using NIH-IREP. The upper bounds of all the 

distributions represent the 99th percentile of each estimated PC. The magnitude of 

the lung dose is chosen so that upper 99th percentile of the PC estimated using 

NIOSH-IREP is 50%. The lower bounds represent the 1st percentile of PC. The 

horizontal solid line and the solid circles represent the 50th percentiles of PC. 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

18

0

10

20

30

40

50

60

70

80

90

100

10 15 20 25 30 35 40 45

Female, former smoker

Probability of causation [%]

Age at exposure

NIOSH-IREP

Cancer diagnosed at age 60

0

10

20

30

40

50

60

70

80

90

100

30 35 40 45 50 55 60 65

Probability of causation [%]

Attained age

NIOSH-IREP

Exposure at age 20

Fig. 8 Probability of lung cancer causation for former smoker females for different ages 

at exposure and attained ages, from exposure to a constant dose of high-energy 

photons. The horizontal dashed and solid lines represent the probability of 

causation (PC) estimated by NIOSH-IREP, while the vertical lines and solid 

circles represent the PC obtained using NIH-IREP. The upper bounds of all the 

distributions represent the 99th percentile of each estimated PC. The magnitude of 

the lung dose is chosen so that upper 99th percentile of the PC estimated using 

NIOSH-IREP is 50%. The lower bounds represent the 1st percentile of PC. The 

horizontal solid line and the solid circles represent the 50th percentiles of PC. 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

19

0

10

20

30

40

50

60

70

80

90

100

Male Female Male Female

Never smoker

Probability of causation [%]

NIOSH-IREP NIH-IREP

0

10

20

30

40

50

60

70

80

90

100

Male Female Male Female

Former smoker

Probability of causation [%]

NIOSH-IREP NIH-IREP

0

10

20

30

40

50

60

70

80

90

100

Male Female Male Female

10-19 cigs/day - current smoker

Probability of causation [%]

NIOSH-IREP NIH-IREP

0

10

20

30

40

50

60

70

80

90

100

Male Female Male Female

40+ cigs/day - current smoker

Probability of causation [%]

NIOSH-IREP NIH-IREP

Fig. 9 Probability of lung cancer causation for the two genders, for different smoking 

categories, from exposure to an acute dose of 75 cSv of high-energy photons. It 

was assumed that exposure took place at age 20 and the lung cancer was 

diagnosed at age 60. The upper bounds of all the distributions represent the 99th

percentile of each estimated probability of causation (PC). The lower bounds 

represent the 1st percentile of PC. The circles represent the 50th percentiles of PC. 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

20

Appendix A – Treatment of lung cancer in NIH version of IREP 

The risk model for lung cancer in NIH-IREP is described by the following equation (Land et al. 

2003; page 23; equation IV.D.1): 

ERR = D × α × exp[β s + γ × f(e)+ δ × g(a)] = D × ERR/Sv 

where 

- D = radiation equivalent dose (Sv) delivered to the organ responsible for 

induction of cancer. 

- α, β, γ, δ = parameters of the model associated with each modifier. 

- s = sex modifier (s = sexvar = - 0.5 males and + 0.5 for females).

- f(e) = min[max(-15,e-30),0] where e is the age at exposure. 

- g(a) = min(ln(a/50),0) where a is the attained age. 

In particular, α is the ERR/Sv for age at exposure 30 and attained age 50, for a never smoker. 

The profile for α is given in the Table A.1 and Fig. A.1. 

The joint distribution of β, γ, and δ is a multivariate normal with the specified means and 

covariance matrix (this distribution corresponds closely to the profiles for these parameters). 

Alpha is assumed to be uncorrelated with β, γ, and δ (Table A.2). This approach is similar to the 

treatment of most of the other cancer sites, except for the sex parameter, β. Alpha applies to 

both males and females, and gender differences are introduced by the sex modifier s. Thus, there 

is a unisex profile for parameter α for lung cancer, not separate ones for each sex. 

In the logarithmic scale, the ERR/Sv (for person of a given gender, given at exposure age e and 

given attained age a) is assumed to be normally distributed with the mean and variance of 

logarithms defined by the equations below. 

ERR/Sv(e,a) = ERR/Sv(e=30,a=50) × F(s,e,a) = α × F(s,e,a) 

The modifying factor F(s,e,a) is assumed to be independent α and is described by a lognormal 

distribution with a mean of logarithms and a variance of logarithms given by: 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

21

mean = β × s + γ × f(e) + δ × g(a), and 

variance = var(β)+var(γ)× f(e)2

+var(δ) × g(a)2 + 

 2 × cov(β,γ)× f(e)+ 2 × cov(β,δ)× g(a)+ 2 × cov(γ,δ)× f(e) × g(a)

For a given attained age, the ERR/Sv for these cancer types decreases exponentially between ages 

at exposure of 15 and 30 and is constant outside this interval. Similarly, for a given age at 

exposure, the ERR/Sv decreases linearly with attained age, up to attained age 50, after which it 

remains constant. 

By using the mean values and the covariance matrix (Table A.2) and the definition for functions 

f(e) and g(a), the means of logarithms and the variance of the logarithms are given by the 

following equations: 

mean = 0.843× s + (–0.05255) × min(max(-15,e-30),0)+ (– 1.626) × min(ln(a/50),0) and 

variance = 0.0625 s

2

 + 0.00033 × [min(max(-15,e-30),0)]2 + 

 0.56203 × [min(ln(a/50),0)]2 + 

 2 × (-0.000347) × s × min(max(-15,e-30),0) + 

 2 × 0.00836 × s × min(ln(a/50),0) + 

 2 × (-0.00708) × min(max(-15,e-30),0) × min(ln(a/50),0) 

To estimate risk and probability of causation for different smoking categories, the ERR for never 

smokers is multiplied by the term: [x + (1 – x)WS*], where WS* is the smoking adjustment factor 

(Table A.3). The uncertainty distribution for x allows the ERR/Sv for lung cancer to range from 

that obtained with an additive interaction (x = 0) to that obtained with a multiplicative interaction 

(x = 1). A 50% probability is given to the purely additive model (where x ≡ 0) and 50% to a 

triangular distribution with a minimum value of 0, a mode of 1.0 and a maximum value of 1.1. 

This triangular distribution has more weight towards the multiplicative model, with a probability 

of about 0.10 for a super-multiplicative interaction (x > 1). 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

22

Table A.1 The profile for α = ERR/Sv(e=30,a=50) used in NIH-IREP for an exposure age > 

30 and an attained age > 50. This distribution applies to both males and females. 

Sex differences are introduced by the parameter s in the risk model. 

Percentile α a

99.75 1.8218 

99.50 1.7243 

98.75 1.5899 

97.50 1.4825 

95.00 1.3681 

87.50 1.2002 

84.15 1.1519 

50.00 0.8603 

15.85 0.6127 

12.50 0.5792 

5.00 0.4750 

2.50 0.4133 

1.25 0.3610 

0.50 0.3024 

0.25 0.2642 

a

 Table IV.D.3, page 50 of Land et al. (2003) 

Table A.2 Mean values and covariance matrix for the parameters of the NIH-IREP risk 

model for lung 

 Covariance matrix 

Parameter variable 

Name Mean variable s f(e) g(e) 

β 0.4215 s 0.0625 

γ -0.05255 f(e) -0.000347 0.00033 

δ -1.626 g(a) 0.00837 -0.00708 0.56203 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

23

Table A.3 The smoking adjustment factor W* used in NIH-IREP a,b. 

Smoking category Male a Female a 

Never smoked 1.0000 1.0000 

Former smoker 0.2511 0.2513 

Current smoker (? cig/day) 0.0886 0.0897 

<10 cig/day (currently) 0.2574 0.2564 

10-19 cig/day (currently) 0.1034 0.1051 

20-39 cig/day (currently) 0.0591 0.0590 

>40 cig/day (currently) 0.0422 0.0410 

a

 Source: Table IV.I.1, page 69 of Land et al. (2003). 

b

 These adjustment factors are the same with the ones used in 

NIOSH-IREP (Table B.2) but, they are centered on never 

smokers 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

24

0.1

1

10

.01 .1 1 5 10 20 30 50 70 80 90 95 99 99.9 99.99

Original

Interpolated

ERR/Sv

Percent

Fig. A.1 Profile for α, the ERR/Sv for exposure age 30 and attained age 50 used in NIHIREP (Table IV.D.3, page 50 of Land et al., 2003) 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

25

Appendix B – Treatment of lung cancer in NIOSH version of IREP 

The risk model for lung cancer in NIOSH-IREP is described by the following equation (page 25 

in Land et al., 2002): 

ERR = D × α(s) × exp[γ × f(e)+ δ × g(a)] = D × ERR/Sv 

where 

- D radiation equivalent dose (Sv) delivered to the organ responsible for induction 

of cancer. 

- α, β, γ, δ = parameters of the model associated with each modifier. 

- s = sex modifier.

- f(e) = min[max(-15,e-30),0] where e is the age at exposure. 

- g(a) = min(ln(a/50),0) where a is the attained age. 

In particular, α is the ERR/Sv for any age at exposure and any attained age 50, for a population of 

both smokers and non-smokers smoker. The profile for α was obtained for males and females 

separately (Table B.1 and Fig. B.1). No age effects are included in the NIOSH version of IREP 

(i.e., γ = δ = 0). 

To estimate risk and probability of causation for different smoking categories, including never 

smokers, the population-averaged ERR is multiplied by the term: [x + (1 – x)WS*], where WS* is 

the smoking adjustment factor (Table B.2). The uncertainty distribution for x allows the ERR/Sv

for lung cancer to range from that obtained with an additive interaction (x = 0) to that obtained 

with a multiplicative interaction (x = 1). The parameter x is described by triangular distribution 

with a minimum value of 0, a mode of 1.0 and a maximum value of 1.1. This triangular 

distribution has more weight towards the multiplicative model, with a probability of about 0.10 

for a super-multiplicative interaction (x > 1). 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

26

Table B.1 The profile for α = ERR/Sv for males and females in NIOSH-IREP. This 

distribution applies to all ages at exposure and all attained ages. 

Percentile Male Female 

99.75 1.114 3.449 

99.50 1.053 3.307 

98.75 0.968 3.109 

97.50 0.8987 2.948 

95.00 0.8237 2.775 

87.50 0.7112 2.516 

84.15 0.6783 2.441 

50.00 0.474 1.973 

15.85 0.2953 1.563 

12.50 0.2681 1.504 

5.00 0.1885 1.323 

2.50 0.1408 1.214 

1.25 0.09998 1.119 

0.50 0.05369 1.012 

0.25 0.02386 0.9406 a

 Table IV.D.3 on page 83 in Land et al. (2002) 

Table B.2 The smoking adjustment factor W* used in NIOSH-IREP a,b. 

Smoking category Male Female 

Total 1.00 1.00 

Never smoked 4.74 3.9 

Former smoker 1.19 0.98 

Current smoker (? cig/day) 0.42 0.35 

<10 cig/day (currently) 1.22 1.00 

10-19 cig/day (currently) 0.49 0.41 

20-39 cig/day (currently) 0.28 0.23 

>40 cig/day (currently) 0.2 0.16 

a

 Source: Table IV.I.1, page 97 of Land et al., 2002. 

b

 The adjustment factors in NIH-IREP (Table A.3) are the same 

with the ones in this table, but NIH-IREP factors are centered on 

never smokers. That is, the values in Table A.3 ore obtained by 

dividing the W* values in this table by 4.74 for males and 3.9 for 

females. 
Lung Cancer in NIOSH and NIH SENES Oak Ridge, Inc. 

Versions of IREP Sept 20, 2004 

27

0.01

0.1

1

10

.01 .1 1 5 10 2030 50 7080 90 95 99 99.999.99

Male

Female

ERR/Sv

Percent

Fig. B.1 Profile for α, the ERR/Sv for males and females used in NIOSH-IREP for all ages 

at exposure and all attained ages. (Table IV.D.3 on page 83 in Land et al., 2002)