"Radiation & Risk", 2003, special issue

2. PREDICTION OF RADIATION-INDUCED THYROID CANCERS AMONG RESIDENTS
OF THE ORYOL OBLAST BASED ON THE ICRP MODELS

2.1. Model of radiation risks for thyroid cancer

Let us first define the terminology used here before describing the model for the radiation risk. A risk of disease (death) is understood as a probability m of developing disease by an individual during a given time interval. The risk or probability of developing disease depends on age, sex, profession, lifestyle, place of residence, time and other factors. By way of an example, let us consider a group of N persons not exposed to radiation, followed up for a year with a view to determine how many cases occurred in this group. If during a year E of persons (expected number of cases) developed a disease in this group, then the risk over a year will be estimated as

m = E/N (the risk m is called spontaneous or background). Given N = 100 thousand people, then m is to the spontaneous incidence rate per 100 thousand persons. If the group was exposed to radiation, then the number of cases will change and be equal to O (observed number of cases). In absolute terms, the effect of exposure is characterized by the excess absolute risk EAR=O-E. The relative significance of exposure is described by EER - excess relative risk.

ERR = EAR/E = (O-E) /E. (2.1)

One of the key characteristics of the level of radiation-induced diseases is the attributive risk ATR (sometimes called the probability of causation POC or simply PC ) defined as:

. (2.2)

The attributive risk is the ratio of radiation-induced diseases to the number of all diseases. The attributive risk is often expressed in percent. The excess absolute risk EAR is calculated as:

, (2.3)

where m is the background incidence rate.

In this work the model of excess absolute risk BEIR-V [1] recommended by the ICRP is used for calculating thyroid cancer:

, (2.4)

where F is the efficiency factor (for isotopes 125I, 131I F = 1/3, for other iodine isotopes F = 1); the sex factor

S = 2/3 for males and S = 4/3 for females; the age factor G = 1 at g £ 18 and G = 0.5 at g > 18. The latent period is taken to be TL = 5 years.

The calculation of radiation-induced risks requires a knowledge of the background incidence rates. We use the average Russian incidence rates for 1996 [2] given in Table 2.1 for the background rates. For comparison the table contains general cancer incidence rates. As can be seen, thyroid cancer is a fairly rare disease. Thyroid cancer makes, on average, only a few percent of all cancers. This section describes a model of radiation risks of thyroid cancer. This disease occurs 2-3 times more frequently in females than in males. In the subsequent chapter there is a projection of radiation risks of this disease for residents of the Oryol oblast.

Table 2.1. Background incidence and death rates in 1996.

Age interval / Incidence rate per 100 thousand persons / Death rate per 1 thousand from all causes
All Cancer / Thyroid Caner
males / females / males / females / males / females
0 - 4 / 12 / 11 / 0.00 / 0.00 / 4.45 / 3.33
5 - 9 / 11 / 8 / 0.04 / 0.09 / 0.61 / 0.37
10 - 14 / 10 / 8 / 0.13 / 0.40 / 0.58 / 0.33
15 - 19 / 16 / 14 / 0.25 / 0.91 / 2.14 / 0.80
20 - 24 / 20 / 24 / 0.30 / 2.0 / 4.12 / 0.98
25 - 29 / 23 / 37 / 0.59 / 2.8 / 4.96 / 1.22
30 - 34 / 36 / 67 / 0.74 / 4.5 / 6.57 / 1.57
35 - 39 / 64 / 114 / 0.89 / 5.9 / 8.56 / 2.24
40 - 44 / 136 / 194 / 1.2 / 8.7 / 12.0 / 3.32
45 - 49 / 289 / 314 / 2.3 / 11.6 / 16.8 / 5.09
50 - 54 / 543 / 421 / 3.4 / 13.0 / 23.3 / 7.46
55 - 59 / 804 / 480 / 2.8 / 10.8 / 30.5 / 10.5
60 - 64 / 1175 / 632 / 3.6 / 10.7 / 41.3 / 15.9
65 - 69 / 1539 / 755 / 3.8 / 10.1 / 55.6 / 24.5
70 - 74 / 1974 / 944 / 5.4 / 9.5 / 71.0 / 39.0
>74 / 1814 / 856 / 3.6 / 7.1 / 138.0 / 106.

2.2. Demographic data and doses for the population of the Oryol oblast

The depositions from the Chernobyl accident resulted in radioactive contamination of the territories of the Bryansk, Kaluga, Lipetsk, Oryol, Ryazan and Tula oblasts. Starting from the moment of contamination the population of these territories was exposed to internal and external irradiation from a mix of a variety of fission products and activation products. The main exposure source were radioisotopes of iodine, cesium, strontium and plutonium. So far, mean thyroid doses have been calculated for residents of the indicated oblasts. Table 2.2 includes data on accumulated doses and populations of the rayons of the Oryol oblast. As of 1986 the general population of the oblast was 887 thousand people (of them 190 thousand children and 697 thousand adults).

Table 2.2. Populations of rayons of the Oryol oblast and the accumulated doses averaged over each rayon.

Administrative name / Population / Accumulated thyroid dose (adults), mGy / Accumulated thyroid dose (children), mGy
children / adults / total
BOLKHOVSKY / 5339 / 19586 / 24925 / 17.1 / 71.4
VERKHOVSKY / 5479 / 20103 / 25582 / 8.59 / 28.4
GLAZUNOVSKY / 3728 / 13677 / 17405 / 14.3 / 49.5
DMITROVSKY / 4262 / 15636 / 19898 / 21 / 84.3
DOLZHANSKY / 3480 / 12768 / 16248 / 5.29 / 16.3
ZALEGOSHENSKY / 4156 / 15248 / 19404 / 9.03 / 31
ZNAMENSKY / 1438 / 5277 / 6715 / 8.97 / 27.3
KOLPNYANSKY / 5014 / 18395 / 23409 / 7.73 / 24.6
KORSAKOVSKY / 1129 / 4143 / 5272 / 10.5 / 36.7
KRASNOZORENSKY / 2101 / 7707 / 9808 / 12.4 / 35.4
KROMSKY / 5524 / 20266 / 25790 / 14.8 / 54.6
LIVENSKY / 18031 / 66153 / 84184 / 5.8 / 21
MALOARKHANGELSKY / 3476 / 12755 / 16231 / 22 / 66.1
MTSENSKY / 14778 / 54219 / 68997 / 8.05 / 32.2
NOVODEREVENKOVSKY / 3276 / 12021 / 15297 / 9.08 / 29.4
NOVOSILSKY / 2661 / 9764 / 12425 / 10.5 / 36.7
ORLOVSKY / 82741 / 303552 / 386293 / 9 / 40.6
POKROVSKY / 4443 / 16303 / 20746 / 10.3 / 31.3
SVERDLOVSKY / 4317 / 15841 / 20158 / 14.4 / 48
SOSKOVSKY / 2027 / 7437 / 9464 / 12.8 / 37
TROSNYANSKY / 3140 / 11521 / 14661 / 15.9 / 48.9
URITSKY / 4219 / 15481 / 19700 / 10.8 / 38.3
KHOTYNETSKY / 2896 / 10627 / 13523 / 6.73 / 21.6
SHABLYKINSKY / 2426 / 8903 / 11329 / 10.5 / 34
TOTAL OBLAST / 190095 / 697393 / 887488 / 13 / 38.7

As a result of the intense rainfall on 28-29 April 1986 the territory of the Oryol oblast was contaminated by radioactivity. The rayons worst affected were Bolkhovsky, Dmitrovsky, Kromsky and Maloarkhangelsky rayons. The accumulated doses in children of these rayons exceed 50 mGy and the doses in adults are up to 22 mGy. Figures 1.15 and 1.16 of chapter 1 present the maps of the Oryol oblast with mean accumulated doses (iodine) in mGy in children and adults of the studied rayons, respectively.

In adults the accumulated thyroid doses are about 3-4 times lower than those in children. As a consequence, the risk of radiation-induced thyroid cancers is estimated to be 6-8 times higher in children than in adults (for children the factor G=1 for adults G=0.5).

2.3. Mathematical model for predicting radiation-induced risks

In a general case, the dynamics of cancer incidence in the population with uniform doses is described by a system of differential equations with partial derivatives written as:

(2.5)

Here n is the number of healthy individuals, ni is the number of patients with the background i-th disease, dni is the number of patients with radiation-induced i-th disease, m is the background death rate, hi is the survival rate for the i-th disease, mi is the death rate from the i-th disease, Q accounts for birth rate and migration process. The background coefficients in equation (2.5) depend on time t and age u. The radiation-induced coefficients are a function of radiation dose and other parameters. If the number of diseases is k (1 £ I £ k), then the total number of equations equals to 2k + 1. Taking into account the dependence of the equation parameters on sex, the number of equations is doubled.

If the dose is not uniform over the population, for each dose interval a system of equations similar to system (2.5) is written. At the initial time moment the distribution of population by age n(u,o) is specified. Assuming the maximum age um, n(u,t)=0 at u > um (further in calculations um = 90 years).

Considering the uncertainty in the demographic and epidemiological data over the years since the accident and in projections, the prognostic model was based on the following assumptions. It is assumed that the accumulated radiation dose (iodine) was received only by the population living in the Oryol oblast in 1986. Thus, at a starting time moment the distribution n(u,s,0) of the population of each rayon by age u and sex s are considered to be known. As n(u,s,0) we take the age distribution of the population of the whole Oryol oblast normalized to the number of residents in a particular rayon. The changes in population as a result of background deaths from all causes at t>0 (with allowance for sex) is described by the equation:

, (2.6)

where m(u,s) is the death factor dependent only on age and sex. For brevity the sex parameter s is omitted. In the calculations the mean Russian death rates for 1996 shown in Table 2.1 are used.

To elucidate the influence of uncertainties in demographic data on prediction results we used “standardized” age distribution of population derived from the solution of the following equation:

(2.7)

at the initial condition n(0)=n0. This distribution (for each sex) was normalized to the number of residents of a given rayon. Figure 2.1 presents both age distributions of the population for the whole Oryol oblast.

Fig. 2.1. Age distribution of the population of the Oryol oblast.

The solid line is the standardized distribution calculated with equation (2.7).

The incidence rate for the i-th background disease (number of cases per year) for a given age at the time moment t>TL was calculated as follows:

, (2.8)

where mi(u) is the coefficient of the i-th incidence rate. The incidence rates are shown in Table 2.1.

The incidence rate dni of radiation-induced diseases at a given age at the time moment t was calculated by the equation:

. (2.9)

The cumulative number of background Ni and radiation-induced dNi diseases at the time moment t>TL is found as follows:

, (2.10)

. (2.11)

Corresponding lifetime risks are determined as Ni(um) and dNi(um) (i.e. the number of cases over the whole time of the cohort existence).

Equation (2.6) was solved by the numerical method with the step of time and age integration of 1 year. Accordingly, the number of background and radiation-induced cases were calculated for each year.

2.4. Information and reference software PUBRASS-2002

For calculating and predicting background and radiation-induced cancers in the residents of the Oryol oblast an information and reference software program PUBRASS-2002 (Public Risk ASSessment) has been developed. The size of this software is 1.8 Mb (execution module) and 0.5 Mb are the service files. The software is based on a mathematical model for predicting cancer risks described in the previous section. The software is written in the algorithmic language FORTRAN-90, the environment is Fortran Power Station 4.0. Figure 2.2 shows a part of the main window of the PUBRASS software with the main menu of 4 items (RISKS, CALCULATION RESULTS, INPUT DATA AND REFERENCES).

Fig. 2.2. Fragment of the display window of software PUBRASS-2002
with the main menu.

Each item of the main menu contains a pull-down menu, as shown in Fig. 2.3. When the first item of the menu is activated, a dialogue window shows up and a user can select a rayon of the Oryol oblast or the whole oblast, type of cancer, age distribution, sex and age interval at the time of exposure. Among other things, a button “REFERENCES” is available in the dialogue window for obtaining explanatory information. The dialogue window is shown in Fig. 2.4.

Fig. 2.3. Fragment of the main window of software PUBRASS-2002
with pull-down menus.

Fig. 2.4. Dialogue window for input of source data for calculating risks
for residents of the Oryol oblast.

Results of the calculation and the prediction of cancer risks are presented as time functions of risks and maps of the Oryol oblast with indication of cumulative risks (lifetime and current year values). Figure 2.5 presents a fragment of the screen display with the results of predicted incidence (number of persons) plotted. The plot is accompanied by brief information about the time dependence of risk. The second item of the menu “RESULTS OF CALCULATION” provides an opportunity to look at risks of interest. Activating the submenu “MAPPED RISKS” the user can select a map with risks of interest (background and radiation-induced). This window is shown in Fig. 2.6.