Background: U.S. breast cancer survivors (BCSs) are expected to increase from 3 to 4 million in the next 5-10 years. Cancer recurrence risk is highest in obese survivors. Pro-inflammatory biomarkers including C-reactive protein (CRP), Interleukins -3, -6, and -8 (IL-3, IL-6, IL-8), and Tumor Necrosis Factor (TNF)α have been associated with cancer severity and recurrence. Nutritional interventions aimed at reducing inflammation (INF) may contribute to reduced recurrence risk and potentially increase survival rates. However, studies to date have been conducted predominantly in animal models. The primary goal of this one-year culinary-based pilot intervention is to improve BCS biomarker profiles -- decrease pro-inflammatory biomarkers and increase anti-inflammatory (AI) cytokines like IL-10 -- by promoting incorporation of AI foods into dietary routines. The secondary goal is to examine effects on potential cancer risk factors including body mass index (BMI), stress and depression levels.

Methods: A total of 153 BCSs was recruited. Overweight and obese women aged 18 or older, diagnosed with Stage 0-III breast cancer who were at least 2 months post-systemic therapy at time of enrollment were randomized into Intervention (IG; n=76) and Control (CG; n=77) groups. The CG received monthly nutritional brochures from the American Institute for Cancer Research. IG participants attended 6 monthly workshops consisting of brief lectures on AI topics and chef-prepared food demonstrations, and received monthly tailored newsletters and follow-up telephone calls incorporating Motivational Interviewing techniques. At baseline and 6- and 12-month follow-up assessments, fasting blood samples were collected from all participants and assayed for inflammatory marker levels. BMI and waist circumference were measured, and self-reported data on dietary habits, demographics, physical activity (PA), perceived stress (PSS) and depression levels were collected. Violin plots of baseline, 6- and 12-month BMI were generated in R version 3.1.3 (R Core Team, 2013) for participants who had completed all three assessments (n=46). Path Analysis and Structural Equation Modeling were conducted using both R and Stata version 13 (Stata Corp, College Station, TX, 2014) to test hypothesized relationships among latent and observed variables.

Results: Participants were characterized at baseline by mean age of 56.6 ± 9.4 years and mean BMI of 32.4 ± 4.9 kg/m2. Women self-identified as U.S. Latino or Anglo (41.2% and 43.1%, respectively), had college-level education or bachelor's degree (65.4%), were employed full-time (51.6%) and privately insured (80.9%). There were no significant differences between groups. All Interleukins were significant predictors of INF (standardized coefficient βs>0.83, p<0.001). Although not significant, INF had positive relationships with BMI (βs=0.06) and PSS (βs=0.10), and negative relationships with PA (βs=-0.01) and AI diet (βs=-0.03). AI diet was negatively correlated with depression (r=-0.47). The IG plots (n=20) showed a progressive decrease in median BMI from baseline to 12 months (32.3, 31.6, 30.6, respectively; Interquartile ranges [IQR] 7.3, 6.2, 7.7). In contrast, the CG (n=26) demonstrated minimal change (median BMI=30.0, 30.7, 30.5, respectively; IQR=4.3, 5.2, 5.3).

Conclusion: Ongoing analyses will determine relationship significance over the entire study period. Future studies are needed in larger populations with increased INF-related morbidity and mortality risks, to provide more robust estimation of parameters and fit statistics and facilitate generalizability of results.

Citation Format: Amelie G. Ramirez, Edgar Muñoz, Dorothy Long-Parma, Kristin D. Mendoza, Alan E.C. Holden, Michael J. Wargovich. An anti-inflammatory dietary intervention to reduce breast cancer recurrence risk: Preliminary data from a pilot study. [abstract]. In: Proceedings of the Eighth AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 13-16, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2016;25(3 Suppl):Abstract nr A66.