Introduction: Breast cancer has become one of the most serious and widespread public health concerns globally, affecting an increasing number of women—and, in rare cases, men—across the world. It is the most common cancer among women across all countries. In this study, we aimed to evaluate the influence of demographic factors, medical and reproductive history, diagnostic techniques, and hormone receptor status on the development and progression of breast cancer. Materials and Methods: A total of 687 female patients from Romania underwent standard breast examination techniques, including clinical breast examination, mammography, ultrasonography, and, ultimately, breast biopsy. Statistical analysis was performed using the R programming language and RStudio software. The study included a comparative analysis and a prediction analysis for malignancy and tumor size (cumulative histological dimension) through logistic and linear regression models. Results: The comparative analysis identified several variables associated with malignancy: older age (p< 0.001), non-vulnerability (p= 0.04), no daily physical activity (p= 0.002), no re-biopsy (p< 0.001), immunohistochemistry use (p< 0.001), use of larger gauge needles (p< 0.001), ultrasound-guided biopsy (p< 0.001), and vacuum biopsy (p< 0.001). The hormone receptor statuses—estrogen receptor (ER), progesterone receptor (PR), and androgen receptor (AR)—showed statistically significant differences in distribution across breast cancer B classifications. Logistic regression analysis identified ER, PR, and age as significant predictors of malignancy. Linear regression analysis revealed histopathological results, living environment, geographical region, vulnerability, prior breast examination, and the number of histological fragments as significant predictors of cumulative histological dimension. Conclusions: Our predictive models demonstrate the impact of demographic factors, medical history, diagnostic techniques, and hormone receptor status on breast cancer development and progression, accounting for a significant portion of the variance in malignancy and cumulative histological dimension.
引言：乳腺癌已成为全球范围内最严重且最普遍的公共卫生问题之一，影响全球越来越多的女性，极少数情况下也影响男性。在所有国家中，乳腺癌是女性最常见的癌症。本研究旨在评估人口统计学因素、医疗与生育史、诊断技术以及激素受体状态对乳腺癌发生与进展的影响。材料与方法：研究纳入来自罗马尼亚的687名女性患者，所有患者均接受了标准乳腺检查技术，包括临床乳腺检查、乳腺X线摄影、超声检查，并最终进行乳腺活检。统计分析采用R编程语言及RStudio软件完成。研究通过逻辑回归和线性回归模型，对恶性肿瘤及肿瘤大小（累积组织学尺寸）进行了比较分析和预测分析。结果：比较分析发现多个与恶性肿瘤相关的变量：年龄较大（p<0.001）、非易感体质（p=0.04）、无日常体力活动（p=0.002）、未进行重复活检（p<0.001）、使用免疫组化技术（p<0.001）、使用较大规格穿刺针（p<0.001）、超声引导下活检（p<0.001）以及真空辅助活检（p<0.001）。激素受体状态——雌激素受体（ER）、孕激素受体（PR）和雄激素受体（AR）——在乳腺癌B分类中的分布显示出统计学显著差异。逻辑回归分析确定ER、PR和年龄是恶性肿瘤的显著预测因子。线性回归分析显示，组织病理学结果、生活环境、地理区域、易感性、既往乳腺检查史以及组织学切片数量是累积组织学尺寸的显著预测因子。结论：我们的预测模型证明了人口统计学因素、医疗史、诊断技术和激素受体状态对乳腺癌发生与进展的影响，这些因素对恶性肿瘤及累积组织学尺寸的变异具有显著解释力。
肿瘤(癌症)患者之家