Background: The rate of pathologic complete response (pCR) to neoadjuvant systemic treatment (NST) of patients with a body mass index (BMI) of ≥25 has been reported to be significantly lower than that of patients with a BMI <25. However, only patients with a BMI of ≥30 have been found to have worse overall survival (OS) than patients with a BMI <25. Several studies have shown that an increasing body weight after surgery is a poor prognostic factor for OS. Whether a higher BMI after NST and before surgery truly predicts response to chemotherapy or outcomes remains unclear. We hypothesized that higher BMI will be associated with lower rates of pCR and long-term clinical outcomes. The purpose of this study was to determine whether a change in BMI from baseline to after NST and definitive surgery affects pCR and OS in patients with inflammatory breast cancer (IBC) or locally advanced non-IBC. Material and Methods: We retrospectively reviewed the medical records of 263 patients with primary IBC and 865 patients with stage III non-IBC who underwent standard NST consisting of anthracyclines and/or taxanes with or without concurrent trastuzumab followed by definitive surgery at our institution between November 1, 2006, and December 31, 2012. Results: The median follow-up time for survivors was 19.8 months (0.1-69.9 months). One hundred forty-five (55.1%) IBC and 566 (65.7%) non-IBC were hormone receptor-positive and 91 (34.6%) IBC and 198 (22.9%) non-IBC were human epidermal growth factor receptors (HER2)-positive. One hundred forty-four (54.8%) IBC and 446 (51.9%) non-IBC were postmenopausal. Of the 1128 patients included in the study, 223 (19.8%) achieved pCR, including 42 (16.0%) IBC and 181 (20.9%) non-IBC. The median change in BMI during NST of the patients who achieved pCR (0.1) was significantly higher than that of the patients who did not achieve pCR (-0.1; p = 0.04). The pCR rate of the patients whose BMIs had positive change post NST (23.2%) was higher than that of the patients whose BMIs were lower after NST (18.2%), but this difference was not significant (p = 0.054). Multivariate analysis did not reveal positive change in BMI post NST to be a significant predictor of pCR. Univariate analysis with the log-rank test revealed that higher BMI change from pre NST as a categorical variable (BMI change >0 vs. ≤0) predicted increased OS in all patients (p = 0.005) and in IBC patients (p<0.001). After adjust for other clinical variables, none of the BMI-related measures (i.e., baseline BMI, BMI at surgery, and BMI change during NST) predicted OS. Although univariate analysis revealed that BMI change as a continuous variable predicted OS in IBC patients (p = 0.031), after adjust for other clinical variables BMI change no longer predicted OS. None of the BMI measures as continuous or categorical variables predicted recurrence-free survival. Conclusion: In patients with stage III breast cancer, a higher BMI after NST than at baseline does not predict lower pCR rate or decreased survival after adjust for other clinical variables. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr PD2-4.
Background: The 5-year survival rates for inflammatory breast cancer (IBC) are significantly lower than non-IBC, highlighting the importance of cancer prevention in IBC. We investigated the risk factors for IBC subtypes based on estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor 2 (HER2neu) status to determine distinct etiological pathways. The Morgan Welch Inflammatory Breast Cancer Research Program and Clinic at University of Texas MD Anderson Cancer Center (UTMDACC) treats the largest number of IBC patients in a single center. The center maintains a prospective, comprehensive epidemiology registry, through which we were able to conduct the largest single center case-control study on IBC. Methods: We identified 246 patients diagnosed with IBC using strict consensus criteria and 397 cancer free patients seen at the UTMDACC Dan L. Duncan Cancer prevention clinic. We used logistic regression to estimate the odds ratios (OR) and 95% confidence intervals (CI) for the associations between breast cancer reproductive and lifestyle risk factors and IBC tumor subtypes. The tumor subtypes of IBC patients were classified as ER-positive (ER+/PR+/Her2neu-), Her2neu-positive (Her2neu+) and triple negative (ER-/PR-/Her2neu-). Results: In age-adjusted univariate analysis, body mass index (BMI), history of smoking, number of children, age at first pregnancy, breastfeeding, menopausal status, and first degree family history of breast cancer were statistically significant associated with risk of IBC (p<0.05). In multivariable analysis of IBC tumor subtypes, compared to cancer free controls, patients with triple negative (OR = 3.73, 95% CI = 1.52 – 9.13) and Her2neu-positive (OR = 19.27, CI = 4.14 – 89.62) tumors were significantly more likely to have ≥ 2 vs 0-1 children. Patients with triple negative (OR = 0.19, 95% CI = 0.09 – 0.45) and ER-positive (OR = 0.42, CI = 0.19 – 0.88) tumors were significantly less likely to have a history of breastfeeding. Patients with ER-positive (OR = 5.02, CI = 2.29 – 10.99) tumors were also significantly more likely to have a history of smoking. Patients with triple negative (OR = 6.07, CI = 2.62 – 17.07), ER-positive (OR = 7.22, CI = 2.94 – 17.78) and Her2neu-positive (OR = 12.81, CI = 4.59 – 35.78) were more likely to be overweight or obese (BMI ≥ 25kg/m2). Conclusion: The associations identified suggest that overweight or obese status is an important modifiable risk factor for all IBC subtypes. Triple negative IBC share similar risk factors as non-IBC triple negative tumors with increasing number of children and lack of breastfeeding associated with increased risk. Interestingly lack of breastfeeding was also associated with ER-positive IBC tumors, and Her2neu-positive IBC tumors were associated with increasing number of children; two associations that have not been previously reported. Impact: These results highlight the importance of evaluating epidemiologic risk factors of IBC, which could lead to the identification of subtype specific prevention strategies. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P6-12-04.
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