Diabetes risk-reduction diet may improve survival outcomes after breast cancer diagnosis
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Greater adherence to a diabetes risk-reduction diet appeared associated with increased OS among a cohort of breast cancer survivors, according to study results presented at the virtual San Antonio Breast Cancer Symposium.
The data suggest that dietary modifications consistent with type 2 diabetes prevention after a breast cancer diagnosis may be beneficial, according to Tengteng Wang, PhD, MSPH, MBBS, postdoctoral research fellow in the Channing Division of Network Medicine at Brigham and Women’s Hospital.
“There are more than 3.5 million breast cancer survivors in the United States and the number is expected to continually increase, with 4.5 million expected by 2026,” Wang said during her presentation. “When looking at the age distribution of these patients, we see that more than 2.6 million women are aged 60 years and older, which means that breast cancer survivorship must be managed in consideration with aging-related comorbidities, such as diabetes.”
Type 2 diabetes is a risk factor for breast cancer and may be a prognostic factor for breast cancer mortality, she added.
“Having breast cancer also increases the likelihood for developing type 2 diabetes. Therefore, identifying modifiable strategies to prevent type 2 diabetes among breast cancer survivors may be important to improve their survival outcomes,” Wang said.
Investigators examined the association of survival outcomes after breast cancer diagnosis and adherence to a diabetes risk-reduction diet (DRRD), which emphasizes nine dietary components — higher intake of cereal fiber, coffee, nuts, whole fruits and polyunsaturated vs. saturated fat; and lower intakes of trans fat, red meat, and sugar-sweetened beverages and fruit juices.
The analysis included 8,320 women with stage I to stage III breast cancer who participated in the Nurses’ Health Study between 1980 and 2014 and the Nurses’ Health Study II between 1991 and 2015.
Researchers validated information on diet and other covariates through follow-up questionnaires once every 2 to 4 years. They used Cox proportional hazards models to assess breast cancer-specific and all-cause mortality.
Compared with women in the lowest quintile of DRRD score, women in the highest quintile had higher median individual income ($50,046 vs. $47,627), were more likely to use postmenopausal hormone therapy (53% vs. 46%) and were more likely to be physically active and lean (mean BMI, 24.8 kg/m² vs. 26.9 kg/m²). Women in the highest and lowest quintiles were similar with regard to mean age at diagnosis (57 years vs. 56 years) and race (white, 97% vs. 96%).
At a median follow-up of 13 years, 2,146 women had died, including 948 due to breast cancer.
Results of multivariable-adjusted models showed that women with higher post-diagnosis DRRD scores had a 13% lower risk for breast cancer-specific mortality (HR = 0.87) and a 31% lower risk for all-cause mortality (HR = 0.69; P < .0001 for trend).
When researchers looked at changes in mortality before and after breast cancer diagnosis, they found that women who improved their DRRD scores from lower to higher quintiles had a 20% lower risk for breast cancer-specific mortality (HR = 0.8) and a 14% lower risk for all-cause mortality (HR = 0.86) compared with women who consistently had lower scores. In addition, women who maintained a high DRRD score had an 18% lower risk for all-cause mortality (HR = 0.82).
Mortality did not differ based upon breast tumor ER status or stage, according to Wang.
“Our study had multiple strengths, including the fact that we prospectively evaluated the DRRD scores every 4 years before and after diagnosis, we had a large cohort of breast cancer survivors with a long duration of follow-up, and we adjusted for comprehensive time-varying predictors of breast cancer survival during both the pre- and post-diagnostic period,” Wang said. “However, our study also had several limitations, including the predominantly white and educated population, and the dietary measurement error and residual confounding were not avoidable. We also admit that we had limited statistical power for ER-negative tumor analysis.”