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Relationship between Clinicopathologic Variables in Breast Cancer Overall Survival Using Biogeography-Based Optimization Algorithm
المؤلفون المشاركون
Chuang, Li-Yeh
Ou-Yang, Fu
Moi, Sin-Hua
Chen, Guang-Yu
Hou, Ming-Feng
Yang, Cheng-Hong
المصدر
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-04-01
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
Breast cancer is the most common cancer among women and is considered a major public health concern worldwide.
Biogeography-based optimization (BBO) is a novel metaheuristic algorithm.
This study analyzed the relationship between the clinicopathologic variables of breast cancer using Cox proportional hazard (PH) regression on the basis of the BBO algorithm.
The dataset is prospectively maintained by the Division of Breast Surgery at Kaohsiung Medical University Hospital.
A total of 1896 patients with breast cancer were included and tracked from 2005 to 2017.
Fifteen general breast cancer clinicopathologic variables were collected.
We used the BBO algorithm to select the clinicopathologic variables that could potentially contribute to predicting breast cancer prognosis.
Subsequently, Cox PH regression analysis was used to demonstrate the association between overall survival and the selected clinicopathologic variables.
C-statistics were used to test predictive accuracy and the concordance of various survival models.
The BBO-selected clinicopathologic variables model obtained the highest C-statistic value (80%) for predicting the overall survival of patients with breast cancer.
The selected clinicopathologic variables included tumor size (hazard ratio [HR] 2.372, p = 0.006), lymph node metastasis (HR 1.301, p = 0.038), lymphovascular invasion (HR 1.606, p = 0.096), perineural invasion (HR 1.546, p = 0.168), dermal invasion (HR 1.548, p = 0.028), total mastectomy (HR 1.633, p = 0.092), without hormone therapy (HR 2.178, p = 0.003), and without chemotherapy (HR 1.234, p = 0.491).
This number was the minimum number of discriminators required for optimal discrimination in the breast cancer overall survival model with acceptable prediction ability.
Therefore, on the basis of the clinicopathologic variables, the survival prediction model in this study could contribute to breast cancer follow-up and management.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Chuang, Li-Yeh& Chen, Guang-Yu& Moi, Sin-Hua& Ou-Yang, Fu& Hou, Ming-Feng& Yang, Cheng-Hong. 2019. Relationship between Clinicopathologic Variables in Breast Cancer Overall Survival Using Biogeography-Based Optimization Algorithm. BioMed Research International،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1123766
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Chuang, Li-Yeh…[et al.]. Relationship between Clinicopathologic Variables in Breast Cancer Overall Survival Using Biogeography-Based Optimization Algorithm. BioMed Research International No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1123766
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Chuang, Li-Yeh& Chen, Guang-Yu& Moi, Sin-Hua& Ou-Yang, Fu& Hou, Ming-Feng& Yang, Cheng-Hong. Relationship between Clinicopathologic Variables in Breast Cancer Overall Survival Using Biogeography-Based Optimization Algorithm. BioMed Research International. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1123766
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1123766
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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