Comprehensive Analysis of Receptor Status, Histopathological Classifications (B1-B5), and Cumulative Histological Dimensions in Breast Cancer: Predictors of Malignancy and Diagnostic Implications.

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 ( < 0.001), non-vulnerability ( = 0.04), no daily physical activity ( = 0.002), no re-biopsy ( < 0.001), immunohistochemistry use ( < 0.001), use of larger gauge needles ( < 0.001), ultrasound-guided biopsy ( < 0.001), and vacuum biopsy ( < 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.