Is There a Bias Against Obese Patients in the Treatment of Breast Cancer?

2020 ◽  
pp. 000313482098487
Author(s):  
Melinda Wang ◽  
Julian Huang ◽  
Anees B. Chagpar
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Prophylactic Mastectomy ◽  
Implicit Bias ◽  
Treatment Decision ◽  
Obese Patients ◽  
Breast Cancers ◽  
Breast Cancer Patients ◽  
Immediate Reconstruction

Background Patient and tumor characteristics often coincide with obesity, potentially affecting treatment decision-making in obese breast cancer patients. Independent of all of these factors, however, it is unclear whether obesity itself impacts the decision to offer patients undergoing mastectomy breast reconstruction, postmastectomy radiation therapy (PMRT), or neoadjuvant chemotherapy. We sought to determine whether implicit bias against obese breast cancer patients undergoing mastectomy plays a role in their treatment. Methods Medical records of breast cancer patients undergoing mastectomy from January 2010 to April 2018 from a single institution were retrospectively reviewed, separated into obese (BMI ≥30) and nonobese (BMI <30) categories, and compared using nonparametric statistical analyses. Results Of 972 patients, 291 (31.2%) were obese. Obese patients were more likely to have node-positive, triple-negative breast cancers ( P = .026) and were also more likely to have other comorbidities such as a history of smoking ( P = .026), hypertension ( P < .001), and diabetes ( P < .001). Receipt of immediate reconstruction and contralateral prophylactic mastectomy did not vary between obese and nonobese patients. While obese patients were more likely to undergo neoadjuvant chemotherapy (26.5% vs. 18.1%, P = .004) and PMRT (33.0% vs. 23.4%, P = .003), this did not remain significant when controlling for comorbidities and clinicopathologic confounders. Conclusion Obese patients present with more aggressive tumors and often have concomitant comorbidities. Independent of these factors, however, differences in the treatment of patients undergoing mastectomy do not seem to be affected by an implicit bias against obese patients.

scholarly journals Relationship Between Obesity and Pathologic Response to Neoadjuvant Chemotherapy Among Women With Operable Breast Cancer

2008 ◽  
Vol 26 (25) ◽  
pp. 4072-4077 ◽  
Author(s):  
Jennifer K. Litton ◽  
Ana M. Gonzalez-Angulo ◽  
Carla L. Warneke ◽  
Aman U. Buzdar ◽  
Shu-Wan Kau ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Pathologic Complete Response ◽  
Operable Breast Cancer ◽  
Obese Patients ◽  
Breast Cancer Patients ◽  
Significant Difference ◽  
Response To Neoadjuvant Chemotherapy

Purpose To understand the mechanism through which obesity in breast cancer patients is associated with poorer outcome, we evaluated body mass index (BMI) and response to neoadjuvant chemotherapy (NC) in women with operable breast cancer. Patients and Methods From May 1990 to July 2004, 1,169 patients were diagnosed with invasive breast cancer at M. D. Anderson Cancer Center and received NC before surgery. Patients were categorized as obese (BMI ≥ 30 kg/m2), overweight (BMI of 25 to < 30 kg/m2), or normal/underweight (BMI < 25 kg/m2). Logistic regression was used to examine associations between BMI and pathologic complete response (pCR). Breast cancer–specific, progression-free, and overall survival times were examined using the Kaplan-Meier method and Cox proportional hazards regression analysis. All statistical tests were two-sided. Results Median age was 50 years; 30% of patients were obese, 32% were overweight, and 38% were normal or underweight. In multivariate analysis, there was no significant difference in pCR for obese compared with normal weight patients (odds ratio [OR] = 0.78; 95% CI, 0.49 to 1.26). Overweight and the combination of overweight and obese patients were significantly less likely to have a pCR (OR = 0.59; 95% CI, 0.37 to 0.95; and OR = 0.67; 95% CI, 0.45 to 0.99, respectively). Obese patients were more likely to have hormone-negative tumors (P < .01), stage III tumors (P < .01), and worse overall survival (P = .006) at a median follow-up time of 4.1 years. Conclusion Higher BMI was associated with worse pCR to NC. In addition, its association with worse overall survival suggests that greater attention should be focused on this risk factor to optimize the care of breast cancer patients.

The predictive potential of the spatial signature of lymphocytes in breast cancer patients.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 530-530
Author(s):  
Nora Balint-Lahat ◽  
Chen Mayer ◽  
Noa Ben-Baruch ◽  
Ady Yosepovich ◽  
Kira Sacks ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Early Stage ◽  
Principal Component ◽  
Treatment Decision ◽  
High Ratio ◽  
Luminal Breast Cancer ◽  
Breast Cancers ◽  
Breast Cancer Patients ◽  
Validation Set

530 Background: Tumor-infiltrating lymphocytes in breast cancer have emerged as both a prognostic and a potentially predictive immunotherapy biomarker. Advancements in artificial intelligence can extract pathology-based spatial immune fingerprints for use as treatment decision support tools. Methods: We examined 908 primary breast cancer patients with whole slide images (WSI) available from TCGA database. Digital structuring of WSIs included automated detection of lymphocytes, tumor and tumor adjacent stroma, using deep learning-based semantic segmentation. Prognosis was defined as progression free interval (PFI). A Cox Survival analysis was used to detect prognostic spatial features. We used principal component analysis (PCA) to reduce and decorrelate significant features. The resulting PCA features were used to fit the final model. The model was then validated on an independent database of WSI of breast lumpectomies, from two tertiary hospitals in Israel. Results: The analysis included 908 WSI. The average age was 58.4 years old, with a majority of early stage breast cancer (76.7%, stage I and II). The detection performance for tumor area and lymphocytes reached F1 scores of 99% and 97% respectively, in comparison to human annotation. In the Kaplan Meier (KM) analysis of 414 early stage luminal breast cancers, a high number of lymphocyte clusters (LC) and a high ratio between stromal lymphocyte density and tumor lymphocyte density (LD-S/LD-T) were significantly associated with longer PFI (p = 0.005 and p = 0.038, respectively). Based on these features, two continuous PCA features were added to the multivariate model, and remained significantly associated with PFI after adjusting for age (HR = 1.19, 95% CI 1.05-1.35; HR = 1.26 95% CI 1.03-1.55). The validation set was underpowered (n = 79) and data is still being collected. In a preliminary KM analysis of 37 early stage luminal breast cancer cases from the validation set, LD-S/LD-T was significantly associated with longer PFI (p = 0.046). Conclusions: In our study, LC and LD-S/LD-T, presumably surrogate measures of peritumoral lymphocytes, were found significantly associated with longer PFI.

Adding carbon nanoparticles to dual-tracers for the sentinel node evaluation after neoadjuvant chemotherapy in patients with pretreatment node-positive breast cancers: The TT-SLNB trial.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 566-566
Author(s):  
Jie Chen ◽  
Jiqiao Yang ◽  
Tao He ◽  
Yunhao Wu ◽  
Xian Jiang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Neoadjuvant Chemotherapy ◽  
Lymph Nodes ◽  
Cancer Patients ◽  
Carbon Nanoparticles ◽  
Axillary Lymph Nodes ◽  
Axillary Lymph ◽  
Breast Cancers ◽  
Breast Cancer Patients

566 Background: This study measures the feasibility and accuracy of sentinel lymph node biopsy (SLNB) with triple-tracers (TT-SLNB) which combines carbon nanoparticles (CNS) with dual tracers of radioisotope and blue dye, hoping to achieve an optimized method of SLNB after neoadjuvant chemotherapy (NAC) in ycN0 breast cancer patients with pretreatment positive axillary lymph nodes. Methods: Clinically node-negative invasive breast cancer patients with pre-NAC positive axillary lymph nodes who received surgeries from November 2020 to January 2021 were included. CNS was injected at the peritumoral site the day before surgery. Standard dual-tracer (SD)-SLNs were defined as blue-colored and/or hot nodes, and TT-SLNs were defined as lymph nodes detected by any of hot, blue-stained, black-stained, and/or palpated SLNs. All patients received subsequent axillary lymph node dissection. Detection rate (DR), false-negative rate (FNR), negative predictive value (NPV) and accuracy of SLNB were calculated. Results: Seventy-six of 121 (62.8%) breast cancer patients converted to cN0 after NAC and received TT-SLNB. After NAC, 28.95% (22/76) achieved overall (breast and axilla) pCR. The DR was 94.74% (72/76), 88.16% (67/76) and 96.05% (73/76) for SLNB with single-tracer of CNS (CNS-SLNB), SD-SLNB, and TT-SLNB, respectively. The FNR was 22.86% (8/35) for CNS-SLNB and 10% (3/30) for SD-SLNB. The FNR of TT-SLNB was 5.71% (2/35), which was significantly lower than those of CNS-SLNB and SD-SLNB. The NPV and accuracy was 95.0% and 97.3% for TT-SLNB, respectively. Moreover, a significant relation was seen between the pretreatment clinical T classification and the DR of TT-SLNB (Fisher’s exact test, p= 0.010). Conclusions: TT-SLNB revealed ideal performance in post-NAC ycN0 patients with pretreatment node-positive breast cancers. The application of TT-SLNB reached a better balance between more accurate axillary evaluation and less intervention. Clinical trial information: ChiCTR2000039814. [Table: see text]

scholarly journals Tumor Microenvironment Characterization in Breast Cancer Identifies Prognostic and Neoadjuvant Chemotherapy Relevant Signatures

2021 ◽  
Vol 8 ◽  
Author(s):  
Fei Ji ◽  
Jiao-Mei Yuan ◽  
Hong-Fei Gao ◽  
Ai-Qi Xu ◽  
Zheng Yang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
T Cells ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Immune Cells ◽  
Predictive Accuracy ◽  
Complete Response ◽  
Favourable Outcome ◽  
Breast Cancers ◽  
Breast Cancer Patients

Immune response which involves distinct immune cells is associated with prognosis of breast cancer. Nonetheless, less study have determined the associations of different types of immune cells with patient survival and treatment response. In this study, A total of 1,502 estrogen receptor(ER)-negative breast cancers from public databases were used to infer the proportions of 22 subsets of immune cells. Another 320 ER-negative breast cancer patients from Guangdong Provincial People’s Hospital were also included and divided into the testing and validation cohorts. CD8+ T cells, CD4+ T cells, B cells, and M1 macrophages were associated with favourable outcome (all p &lt;0.01), whereas Treg cells were strongly associated with poor outcome (p = 0.005). Using the LASSO model, we classified patients into the stromal immunotype A and B subgroups according to immunoscores. The 10 years OS and DFS rates were significantly higher in the immunotype A subgroup than immunotype B subgroup. Stromal immunotype was identified as an independent prognostic indicator in multivariate analysis in all cohorts and was also related to pathological complete response(pCR) after neoadjuvant chemotherapy. The nomogram that integrated the immunotype and clinicopathologic features showed good predictive accuracy for pCR and discriminatory power. The stromal immunotype A subgroup had higher expression levels of immune checkpoint molecules (PD-L1, PD-1, and CTLA-4) and cytokines (IL-2, INF-γ, and TGF-β). In addition, patients with immunotype A and B diseases had distinct mutation signatures. Therefore, The stromal immunotypes could predict survival and responses of ER-negative breast cancer patients to neoadjuvant chemotherapy.

Body mass index and response to neoadjuvant chemotherapy in breast cancer patients

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 531-531
Author(s):  
J. K. Litton ◽  
A. M. Gonzalez ◽  
C. L. Warneke ◽  
S. Kau ◽  
A. U. Buzdar ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Tumor Response ◽  
Normal Weight ◽  
Pathologic Response ◽  
Obese Patients ◽  
Tumor Characteristics ◽  
Breast Cancer Patients ◽  
Response To Neoadjuvant Chemotherapy

531 Background: Obesity in breast cancer patients is associated with increased risk of poor outcome. One possible mechanism is that obesity may affect metabolism of chemotherapeutic agents, influencing tumor response to chemotherapy. To test this hypothesis, we evaluated the relationship between body mass index (BMI, weight kg/height m2) and response to neoadjuvant chemotherapy in women diagnosed with operable breast cancer. Methods: From May 1990 - July 2004, 1169 patients diagnosed with invasive breast cancer at our institution, received neoadjuvant chemotherapy (anthracycline and/or taxane) followed by definitive surgery. Based on BMI, patients were categorized as obese (BMI ≥30), overweight (BMI 25 to <30), normal weight (18.5 to <25) and underweight (BMI <18.5). We used logistic regression to examine associations between BMI and pathologic response to therapy (complete= no invasive carcinoma, and partial) as well as tumor characteristics. Kaplan-Meier survival curves for BMI groups were compared using the log-rank test. Results: Median patient age was 50 (range 23 - 84) years; 30% were obese, 32% overweight, 36% normal weight and 1% underweight. BMI was not significantly associated with pathologic response to neoadjuvant chemotherapy even after adjusting for relevant clinical factors (OR 1.00; 95% CI 0.96–1.03, p = 0.8). Compared to patients not overweight, obese patients had higher odds of having ER negative tumors (OR 1.5; 95% CI 1.1–2.0; p = 0.01) and T3 or T4 lesions (OR 1.7; 95% CI 1.3–2.4, p < 0.001) adjusting for age, race and menopausal status. At a median follow up of 4.1 (range 0.2–14.3) years, obesity was significantly associated with poorer overall survival (p = 0.006) but not progression-free survival. Conclusions: Obese patients presented with more aggressive tumor characteristics and had worse overall survival compared to patients not overweight. However, BMI was not related to lower tumor response to anthracycline and/or taxane based neoadjuvant chemotherapy suggesting a role for other co-morbidities in influencing outcome. Understanding specific components through which overweight and obesity contribute to breast cancer outcome is essential to individualize and improve care of overweight/obese breast cancer patients. No significant financial relationships to disclose.

Axillary ultrasonographic criteria to predict chemotherapy response in breast cancer patients receiving neoadjuvant chemotherapy.

2014 ◽  
Vol 32 (26_suppl) ◽  
pp. 48-48 ◽  
Author(s):  
Koun Joy Yoo ◽  
Sun Mi Kim ◽  
Sung-Won Kim ◽  
So Yeon Park ◽  
Seung-Hee Choi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Roc Curve ◽  
Chemotherapy Response ◽  
Short Axis ◽  
Breast Cancers ◽  
Breast Cancer Patients ◽  
Cortical Thickening ◽  
Axis Ratio

48 Background: The purpose of the study is to evaluate ultrasonographic criteria to predict response of axillary LNs in patients with breast cancer receiving neoadjuvant chemotherapy. Methods: We retrospectively reviewed data of 402 patients who underwent neoadjuvant chemotherapy from August 2003 to December 2012. Of these, 202 breast cancers in 199 patients (bilateral in 2 patients) in whom axillary LN metastasis was confirmed using axillary ultrasonography (US) and US-guided fine-needle aspiration biopsy (FNAB) were included in the study. US evaluation was done for the long and short axes, and cortical thickening before and after chemotherapy. The ratio of decreased long and short axes and cortical thickening on prechemotherapy US was also calculated. Statistical analysis with receiver operating characteristic (ROC) curve was used to determine the valuable ultrasonographic criteria for predicting pathologic complete remission (CR) using Medicalc program. Results: Final pathologic diagnoses of LNs were yNo in 57, yN1 in 76, yN2 in 50 and yN3 in 19 cases. The mean size of LNs were 1.8cm in long axis, 1.0cm in short axis and 0.9cm in cortical thickening on prechemotherapy US and 1.1cm in long axis, 0.6 cm in short axis and 0.4 cm in cortical thickening on postchemotherapy US. The area under the ROC curve (AUC) was 0.578 for cortex thickening, 0.523 for the long axis, and 0.523 for the short axis of LN on postchemotherapy US. The AUC was 0.643 for the decreased cortex thickening ratio, 0.585 for the long axis ratio, and 0.585 for the short axis ratio. The most significant criteria was decreased cortex thickening ratio to the long and short axes (p < 0.05). The sensitivity and specificity of the decreased cortex thickening ratio for predicting CR were 43.7% and 80.7%, respectively, with a 0.5 cut off value. Conclusions: The most significant criteria for predicting CR was decreased cortex thickening ratio to the long and short axes. It is applicable for selecting sentinel LN biopsy candidates from among breast cancer patients who have undergone neoadjuvant therapy.

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