Analysis of Partially Incomplete Tables of Breast Cancer Characteristics with an Ordinal Variable

Which strategies reduce breast cancer mortality most? Collaborative modeling of optimal screening, treatment, and obesity prevention

BACKGROUND

US breast cancer mortality is declining, but thousands of women still die each year.

METHODS

Two established simulation models examine 6 strategies that include increased screening and/or treatment or elimination of obesity versus continuation of current patterns. The models use common national data on incidence and obesity prevalence, competing causes of death, mammography characteristics, treatment effects, and survival/cure. Parameters are modified based on obesity (defined as BMI  ≥  30 kg/m(2) ). Outcomes are presented for the year 2025 among women aged 25+ and include numbers of cases, deaths, mammograms and false-positives; age-adjusted incidence and mortality; breast cancer mortality reduction and deaths averted; and probability of dying of breast cancer.

RESULTS

If current patterns continue, the models project that there would be about 50,100-57,400 (range across models) annual breast cancer deaths in 2025. If 90% of women were screened annually from ages 40 to 54 and biennially from ages 55 to 99 (or death), then 5100-6100 fewer deaths would occur versus current patterns, but incidence, mammograms, and false-positives would increase. If all women received the indicated systemic treatment (with no screening change), then 11,400-14,500 more deaths would be averted versus current patterns, but increased toxicity could occur. If 100% received screening plus indicated therapy, there would be 18,100-20,400 fewer deaths. Eliminating obesity yields 3300-5700 fewer breast cancer deaths versus continuation of current obesity levels.

CONCLUSIONS

Maximal reductions in breast cancer deaths could be achieved through optimizing treatment use, followed by increasing screening use and obesity prevention.

Which strategies reduce breast cancer mortality most? Collaborative modeling of optimal screening, treatment, and obesity prevention

BACKGROUND

US breast cancer mortality is declining, but thousands of women still die each year.

METHODS

Two established simulation models examine 6 strategies that include increased screening and/or treatment or elimination of obesity versus continuation of current patterns. The models use common national data on incidence and obesity prevalence, competing causes of death, mammography characteristics, treatment effects, and survival/cure. Parameters are modified based on obesity (defined as BMI ≥ 30 kg/m²). Outcomes are presented for the year 2025 among women aged 25+ and include numbers of cases, deaths, mammograms and false-positives; age-adjusted incidence and mortality; breast cancer mortality reduction and deaths averted; and probability of dying of breast cancer.

RESULTS

If current patterns continue, the models project that there would be about 50,100-57,400 (range across models) annual breast cancer deaths in 2025. If 90% of women were screened annually from ages 40 to 54 and biennially from ages 55 to 99 (or death), then 5100-6100 fewer deaths would occur versus current patterns, but incidence, mammograms, and false-positives would increase. If all women received the indicated systemic treatment (with no screening change), then 11,400-14,500 more deaths would be averted versus current patterns, but increased toxicity could occur. If 100% received screening plus indicated therapy, there would be 18,100-20,400 fewer deaths. Eliminating obesity yields 3300-5700 fewer breast cancer deaths versus continuation of current obesity levels.

CONCLUSIONS

Maximal reductions in breast cancer deaths could be achieved through optimizing treatment use, followed by increasing screening use and obesity prevention. Cancer 2013;119:2541–2548. © 2013 American Cancer Society.

Collaborative modeling of the impact of obesity on race-specific breast cancer incidence and mortality

Obesity affects multiple points along the breast cancer control continuum from prevention to screening and treatment, often in opposing directions. Obesity is also more prevalent in Blacks than Whites at most ages so it might contribute to observed racial disparities in mortality. We use two established simulation models from the Cancer Intervention and Surveillance Modeling Network (CISNET) to evaluate the impact of obesity on race-specific breast cancer outcomes. The models use common national data to inform parameters for the multiple US birth cohorts of Black and White women, including age- and race-specific incidence, competing mortality, mammography characteristics, and treatment effectiveness. Parameters are modified by obesity (BMI of ≥ 30 kg/m(2)) in conjunction with its age-, race-, cohort- and time-period-specific prevalence. We measure age-standardized breast cancer incidence and mortality and cases and deaths attributable to obesity. Obesity is more prevalent among Blacks than Whites until age 74; after age 74 it is more prevalent in Whites. The models estimate that the fraction of the US breast cancer cases attributable to obesity is 3.9-4.5 % (range across models) for Whites and 2.5-3.6 % for Blacks. Given the protective effects of obesity on risk among women <50 years, elimination of obesity in this age group could increase cases for both the races, but decrease cases for women ≥ 50 years. Overall, obesity accounts for 4.4-9.2 % and 3.1-8.4 % of the total number of breast cancer deaths in Whites and Blacks, respectively, across models. However, variations in obesity prevalence have no net effect on race disparities in breast cancer mortality because of the opposing effects of age on risk and patterns of age- and race-specific prevalence. Despite its modest impact on breast cancer control and race disparities, obesity remains one of the few known modifiable risks for cancer and other diseases, underlining its relevance as a public health target.