STRATIFIED MULTIVARIATE-ANALYSIS OF PROGNOSTIC MARKERS IN BREAST-CANCER - A PRELIMINARY-REPORT

Published results using prognostic markers in breast cancer have been very confusing to oncologists, surgeons, and pathologists alike As a r esult, there is a wide variation in opinion among oncologists about th e utility of these markers in clinical practice. This study was undert aken to determine the utility of stratified multivariate survival anal ysis in integrating the commonly used prognostic factors into a user-f riendly prognostic scheme, and its implication for treatment decision making. 300 women with invasive ductal carcinoma of the breast who wer e followed-up for 28-112 months (median 72 months) were entered in the study. Patients with distant metastases, those with bilateral or mult ifocal tumors, and special types of carcinoma were excluded. Variables included in the stratified multivariate survival analysis were estrog en receptor (ER) status, tumor size, nodal status, histological grade, number of mitotic figures per ten high power fields (MF/10HPF), and t ype of initial therapy. Data was subjected to Kaplan-Meier survival an alysis and the log rank test for statistical significance at different steps of the analysis Cut-off values for ER that produced a significa nt difference in survival varied from 9 fmol/mg protein to as high as 76 fmol/mg protein in different patient groups and MF/10HPF varied fro m 6 to 21. Patients were stratified into different groups that enabled better evaluation of treatment outcome. Patients could also be combin ed into three groups with significantly different survival rates (p<0. 0001). Stratified multivariate survival analysis show that prognostic markers a) are interdependent and their cut-off values vary depending on other tumor characteristics, and b) if used in a systematic way, th ey can be used to guide treatment decisions.