Theresa Relation1, Yaming Li2, James L Fisher3, Allan Tsung2, Bridget Oppong2, Mariam F Eskander2, Samilia Obeng-Gyasi4. 1. Division of Surgical Oncology, Department of Surgery, The Ohio State University, Columbus, OH; Department of Surgery, MetroHealth System and Case Western Reserve University, Cleveland OH. 2. Division of Surgical Oncology, Department of Surgery, The Ohio State University, Columbus, OH. 3. The Ohio State University College of Medicine, Columbus, OH; James Cancer Hospital and Solove Research Institute, Columbus, OH. 4. Division of Surgical Oncology, Department of Surgery, The Ohio State University, Columbus, OH. Electronic address: samilia.obeng-gyasi@osumc.edu.
Abstract
BACKGROUND: The objective of this study is to examine the associations among neighborhood socioeconomic status, trimodal treatment, and disease-specific mortality among inflammatory breast cancer patients using data from the Surveillance, Epidemiology, and End Results program. METHODS: Patients diagnosed with inflammatory breast cancer (T4d) from 2010 to 2016 were identified in the Surveillance, Epidemiology, and End Results program. The cohort was stratified into neighborhood socioeconomic status groups (low, middle, high) based on National Cancer Institute census tract-level index. Trimodal treatment was defined as receipt of modified radical mastectomy, chemotherapy, and radiation therapy. Bivariable analysis, log-rank test, and a Cox proportional hazards model (hazard ratio, 95% confidence interval) were conducted to evaluate the relationship between neighborhood socioeconomic status, trimodal treatment, and disease-specific mortality. RESULTS: In total, 4,374 patients met study criteria. There was no difference between the neighborhood socioeconomic status groups in receipt of trimodal treatment (P = .19). On multivariable analysis, there was no association between low neighborhood socioeconomic status (hazard ratio 1.13, 0.98-1.30; ref high neighborhood socioeconomic status) or middle neighborhood socioeconomic status (hazard ratio 1.01, 0.88-1.64; ref high neighborhood socioeconomic status) and disease-specific mortality. Notably, triple negative subtype (hazard ratio 2.66, 2.21-3.20; ref luminal A) and Black race (hazard ratio 1.41, 1.16-1.72; ref White) were associated with a higher disease-specific mortality. CONCLUSION: For inflammatory breast cancer patients in the Surveillance, Epidemiology, and End Results program, disease-specific mortality appears to be driven by tumor biology and patient characteristics instead of treatment disparities or neighborhood socioeconomic status.
BACKGROUND: The objective of this study is to examine the associations among neighborhood socioeconomic status, trimodal treatment, and disease-specific mortality among inflammatory breast cancer patients using data from the Surveillance, Epidemiology, and End Results program. METHODS: Patients diagnosed with inflammatory breast cancer (T4d) from 2010 to 2016 were identified in the Surveillance, Epidemiology, and End Results program. The cohort was stratified into neighborhood socioeconomic status groups (low, middle, high) based on National Cancer Institute census tract-level index. Trimodal treatment was defined as receipt of modified radical mastectomy, chemotherapy, and radiation therapy. Bivariable analysis, log-rank test, and a Cox proportional hazards model (hazard ratio, 95% confidence interval) were conducted to evaluate the relationship between neighborhood socioeconomic status, trimodal treatment, and disease-specific mortality. RESULTS: In total, 4,374 patients met study criteria. There was no difference between the neighborhood socioeconomic status groups in receipt of trimodal treatment (P = .19). On multivariable analysis, there was no association between low neighborhood socioeconomic status (hazard ratio 1.13, 0.98-1.30; ref high neighborhood socioeconomic status) or middle neighborhood socioeconomic status (hazard ratio 1.01, 0.88-1.64; ref high neighborhood socioeconomic status) and disease-specific mortality. Notably, triple negative subtype (hazard ratio 2.66, 2.21-3.20; ref luminal A) and Black race (hazard ratio 1.41, 1.16-1.72; ref White) were associated with a higher disease-specific mortality. CONCLUSION: For inflammatory breast cancer patients in the Surveillance, Epidemiology, and End Results program, disease-specific mortality appears to be driven by tumor biology and patient characteristics instead of treatment disparities or neighborhood socioeconomic status.
Authors: Jennifer A Schlichting; Amr S Soliman; Catherine Schairer; David Schottenfeld; Sofia D Merajver Journal: Breast Cancer Res Treat Date: 2012-06-26 Impact factor: 4.872
Authors: Samilia Obeng-Gyasi; Lava Timsina; Kathy D Miller; Kandice K Ludwig; Carla S Fisher; David A Haggstrom Journal: Surgery Date: 2018-08-28 Impact factor: 3.982
Authors: Dennis Slamon; Wolfgang Eiermann; Nicholas Robert; Tadeusz Pienkowski; Miguel Martin; Michael Press; John Mackey; John Glaspy; Arlene Chan; Marek Pawlicki; Tamas Pinter; Vicente Valero; Mei-Ching Liu; Guido Sauter; Gunter von Minckwitz; Frances Visco; Valerie Bee; Marc Buyse; Belguendouz Bendahmane; Isabelle Tabah-Fisch; Mary-Ann Lindsay; Alessandro Riva; John Crown Journal: N Engl J Med Date: 2011-10-06 Impact factor: 91.245
Authors: Arjun Menta; Tamer M Fouad; Anthony Lucci; Huong Le-Petross; Michael C Stauder; Wendy A Woodward; Naoto T Ueno; Bora Lim Journal: Surg Clin North Am Date: 2018-05-24 Impact factor: 2.741
Authors: Relin Yang; Michael C Cheung; Judith Hurley; Margaret M Byrne; Youjie Huang; Teresa A Zimmers; Leonidas G Koniaris Journal: Breast Cancer Res Treat Date: 2009-01-24 Impact factor: 4.872
Authors: Naoto T Ueno; Jose Rodrigo Espinosa Fernandez; Massimo Cristofanilli; Beth Overmoyer; Dan Rea; Fedor Berdichevski; Mohamad El-Shinawi; Jennifer Bellon; Huong T Le-Petross; Anthony Lucci; Gildy Babiera; Sarah M DeSnyder; Mediget Teshome; Edward Chang; Bora Lim; Savitri Krishnamurthy; Michael C Stauder; Simrit Parmar; Mona M Mohamed; Angela Alexander; Vicente Valero; Wendy A Woodward Journal: J Cancer Date: 2018-04-06 Impact factor: 4.207