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. 2011 Jul 6;103(13):1037-48.
doi: 10.1093/jnci/djr172. Epub 2011 Jun 24.

Risk factor modification and projections of absolute breast cancer risk

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Risk factor modification and projections of absolute breast cancer risk

Elisabetta Petracci et al. J Natl Cancer Inst. .

Abstract

Background: Although modifiable risk factors have been included in previous models that estimate or project breast cancer risk, there remains a need to estimate the effects of changes in modifiable risk factors on the absolute risk of breast cancer.

Methods: Using data from a case-control study of women in Italy (2569 case patients and 2588 control subjects studied from June 1, 1991, to April 1, 1994) and incidence and mortality data from the Florence Registries, we developed a model to predict the absolute risk of breast cancer that included five non-modifiable risk factors (reproductive characteristics, education, occupational activity, family history, and biopsy history) and three modifiable risk factors (alcohol consumption, leisure physical activity, and body mass index). The model was validated using independent data, and the percent risk reduction was calculated in high-risk subgroups identified by use of the Lorenz curve.

Results: The model was reasonably well calibrated (ratio of expected to observed cancers = 1.10, 95% confidence interval [CI] = 0.96 to 1.26), but the discriminatory accuracy was modest. The absolute risk reduction from exposure modifications was nearly proportional to the risk before modifying the risk factors and increased with age and risk projection time span. Mean 20-year reductions in absolute risk among women aged 65 years were 1.6% (95% CI = 0.9% to 2.3%) in the entire population, 3.2% (95% CI = 1.8% to 4.8%) among women with a positive family history of breast cancer, and 4.1% (95% CI = 2.5% to 6.8%) among women who accounted for the highest 10% of the total population risk, as determined from the Lorenz curve.

Conclusions: These data give perspective on the potential reductions in absolute breast cancer risk from preventative strategies based on lifestyle changes. Our methods are also useful for calculating sample sizes required for trials to test lifestyle interventions.

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Figures

Figure 1
Figure 1
Estimated 5-, 10-, 20-, 30-year projections of the mean risk reduction vs the non-modified mean risk in the whole population of 45-year-old women and women in two high-risk subsets of the population. Women with a positive family history for breast cancer and women who account for the highest 10% of risk in the population make up the two high-risk subsets. The numbers next to the symbols denote the risk projection interval in years.
Figure 2
Figure 2
Estimated 10-year mean risk reductions in 45- and 55-year-old women in subsets that contain varying proportions of the total population risk. Top 10% risk subset = the subset of women that contains the highest 10% of population risk. Other subsets are defined similarly. Vertical lines represent 95% confidence intervals for the estimated risk reductions.

Comment in

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