CORRELATION OF CLINICOPATHOLOGICAL FEATURES AND DISEASE PROGRESSION IN BREAST CARCINOMA PATIENTS-A MULTINOMIAL LOGISTIC REGRESSION ANALYSIS

Abstract

Objective: To determine the correlation between breast carcinoma progression pattern with age, tumor cell receptor status, histopathological diagnoses, and stage of disease in patients. 

Materials and Methods: The study was conducted in the surgery unit of Khyber Teaching Hospital, from January 2023 to December 2023. Patients diagnosed with breast cancer who did not receive treatment were included while those already on chemotherapy were excluded. Patients received neoadjuvant chemotherapy in the oncology department from a consultant Oncologist. A cohort of 54 patients were followed up until completion of chemotherapy. Pre- and post-chemotherapy CT scans were done to re-stage and determine disease progression. The normality of data was recognized by Kolmogorov-Smirnov and Shapiro-Wilks test. The association between categorical variables was determined by the chi-square test of association. The Kruskall-Wallis test was used to determine the correlation between nominal and continuous variables. Multinomial logistic regression was applied between nominal variables where correlation was significant. A p-value < 0.05 was considered statistically significant.

Results: Mean age of 54 patients was 44.11±10.87 (range: 17-70) years. Early-stage disease was seen in 20(37%) cases, while 25(46.3%) had locally advanced breast carcinoma and 9 (16.7%) had metastatic disease.  Disease progression was seen in 19 (35.2%), while 24(44.4%) showed regression and 11 (20.4%) showed no change in disease progression (p-value<0.05). A statistically significant strong association was seen between disease progression and stage (?²=14.7, p=0.004). Multinomial logistic regression analysis showed that patients with early disease at diagnosis were more likely to observe disease regression (OR=24.5, p= 0.008, CI 95%=2.28-262.5).