Extending the Gail model for Breast Cancer Risk Prediction to Account for Modifiable Factors in the Italian Population.

Calza S, Ferraroni M, Decarli A

University of Brescia and University of Milan, Italy

The wide international variation in breast cancer (BC) rates suggests that there are potentially modifiable environmental and lifestyle determinants of BC.

Two relevant components need to be considered, when the individual estimated probability of cancer is of main concern:

- the first is related to the risk factors which are “irreversible”“irreversible” (i.e. genetic factors, age at menarche, age at first birth, number of full-time pregnancies, etc.)

-the second is the set of risk factors which are “modifiable”“modifiable”, at least in principle, such as those related to life-style, (i.e. diet, body mass index, alcohol consumption, etc.).

Background

Gail et al. (1989) proposed a statistical method (GM) to estimate the individual probability of BC developing, as a function of age and a set of irreversible factors.

This model, widely used to optimise intervention studies on BC in USA, is one of the more promising in this field of research.

Different authors have evaluated the model in terms of reliability in predicting the number of BC cases expected and validity of assumptions.

The probability of developing BC between the ages a and , for a women who is in risk group i is written as:

where the subscript 1 refers to the incidence of BC and

2 to all other causes of death.

The model

where :is the baseline incidencebaseline incidence of developing BC at age t

in the reference group. is the relative riskrelative risk of developing BC at age t

compared to the baseline group.

is the mortality ratemortality rate, at age t, from all causes of death, except BC, in the population.

is the probability of survivingprobability of surviving to all other causes of other causes of death death to age t.

where:

The major difficultymajor difficulty is in the estimation of the baselinebaseline breast cancer age-specific hazardhazard , for a subject withoutwithout known risk factors. It is given by

is the overalloverall age-specific invasive BC incidence incidence raterate irrespective of risk group

is the proportion of casesproportion of cases in the i-th risk group as estimated by the case-control studies

is the attributable riskattributable risk of the specified factors which, in turn, define the different risk groups.

This model calculates a woman’s absolute riskabsolute risk of developing BC over various time intervals.

It includes information on:

ageage

age at menarcheage at menarche ( 14 years, 12-13 years, < 12 years)

n. of first-degree relatives with BCn. of first-degree relatives with BC (none, 1 , > 1)

breast biopsiesbreast biopsies (none or unknown, yes)

age at first live birthage at first live birth (< 20 years, 20-24 years, 25-29 years or nulliparous,

30 years)

The routine use of screening mammography in women 50 years old or older reduces BC mortality by approximately one third.

This reduction comes without substantial risks and at an acceptable economic cost.

However the use of screening is more controversial in women under the age of 50, for several reasons.

Decision about the use of Mammography

TargetingTargeting mammography to women at higher risk of higher risk of BCBC can improve the balance of risks and benefits.

This approach has the potential to define guidelines with relevant implications for cancer prevention and public health. In particular, it allows to stratify women with high risk of BC in subgroups which would benefitbenefit from different policies of preventionpolicies of prevention.

The inclusion in the Gail model of other variables, related to modifiable risk factors for BC would allow to disentangle the relative contribution of the two components “irreversible”“irreversible” or “modifiable”“modifiable”, in the individualised probability of developing BC.

The data-sets

EPIC-Florence cohortEPIC-Florence cohort

Recruitment was carried out in the period January 1993-March 1998 and 10,083 women volunteers, residing in the Provinces of Florence and Prato covered by Cancer Registry, were enrolled in the age interval 35-64 years, in the Florence section of EPIC prospective study on diet and cancer.

Detailed information was collected about dietary and life-style habits, reproductive history and family history for BC , for each woman included in the study.

10,083 women volunteers residing in the provinces of Florence and Prato in the age interval 35-64 years

10 subjects lost to follow-up

30 subjects prevalent BC cases

10,031 subjects included in the analysis

12 subjects incident BC cases but diagnosed whitin 6 months from

the date of recruitment

A total of 142 incident invasive BC cases occurred during the period of follow-up

Multicentre case-control Multicentre case-control studystudy

The case-control study was conducted between June 1991 and February 1994 in six Italian areas.

CasesCases were 2569 women, aged 23-74 years ( median age 55 years) admitted to the major teaching and general hospitals of the study areas with histologically confirmed BC diagnosed within the year before interview, and no previous history of cancer.

ControlsControls were 2588 women, aged 20-74 years ( median age 56 years) and admitted to hospitals in the same catchment areas of cases for acute conditions.

Both data-sets include information on sociodemographic charateristics, such as age, education, occupation end socio-economic indicators, lifelong smoking habits, physical activity, anthropometric measures, alcohol consumption, dietary habits, personal medical history and selected questions regarding family history of cancer.

A validated food frequency questionnaire was used to assess the usual diet in order to estimate the mean daily intake of calories and selected nutrients.

Individualized absolute risksabsolute risks for BC in the EPIC-Florence cohort were estimated according different modelsdifferent models, that differ in the following aspects:

age-specific invasive BC rates, ri(t) and AR(t) are those derived from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute;

US-Gail modelUS-Gail model

It-Gail modelIt-Gail model

ri(t) are derived by the multicentre case-control study on diet and BC conducted in Italy, and h1(t), h2(t) are obtained from the Florence Cancer Registry. The estimated ri(t) were obtained by means of a logistic regression model including the same variables as in the US-Gail model.

Different It-Gail models were fitted including dietary variables. In particular we investigated the role of alcohol consumptionalcohol consumption and monounsaturated fats monounsaturated fats intakeintake.

Gail model extension Gail model extension

The aim is to quantify the proportionalproportional relevance of the different risk factorsdifferent risk factors in defining BC risk.

Validation of the model

Gail model extension

Conclusions

Gail model is reasonably valid in Italy: our projected probabilities of developing BC have been validated on women included in a screening programme.

Gail model can be improved for use in populations other than American one, by using BC incidence and RR estimates for risk factors of interest which are more appropriate to the target population.

Gail model structure including potentially modifiable factors can be an important tool in BC risk counselling. The counsellor has the opportunity to look at the lifestyle of the women and possibly suggest that this be modified as an alternative or in conjunction with chemioprevention.

Acknowledgements

This work was conducted with the contributions of the Associazione Italiana per la Ricerca sul Cancro and the Italian Ministry of Education (PRIN 2003)

Estimates of probabilities (% and 95% bootstrap confidence intervals) of developing breast cancer for selected group of subjects

- Breast density is generally higher in younger women and screening mammography is less likely to detect early BC at a curable stage.

- More false positive tests.

- Women under 50 are less likely to have BC. Fewer women in this age group will benefit from screening.

- Cost of mammography per year of life saved is approximately 80.000 Euro.