THE PREDICTIVE VALUE OF ERICA IN BREAST-CANCER RECURRENCE - A UNIVARIATE AND MULTIVARIATE-ANALYSIS

In breast cancer, primary tumor size (T), the number of lymph node met astases (#N), the biochemical estrogen (ER), and progesterone (PGR) re ceptor status have all been important prognostic variables. We evaluat ed the significance of the immunocytochemical measurement of estrogen receptors suing the ERICA method. To determine the relative prognostic value of these variables T, #N, ER, PGR, ERICA and adjuvant treatment , (ADJ), univariate and multivariate analyses of disease-free survival (DFS) were performed for 154 primary breast cancer patients who were diagnosed in 1985 to 1986 at Women's College Hospital and followed pro spectively. We analyzed ERICA results using different classification s ystems, and assessed clinical cut points for the univariate and multiv ariate context. The variables consistently included in the best Cox st epwise regression are T, (p < 0.01), ADJ (p < 0.01), #N (p < 0.01), an d ERICA (p < 0.01). There was weaker evidence of an association betwee n DFS and the biochemically determined ER; ER was not included in the model with a cut point at 10 fmol mg of protein. This illustrates the value of the ERICA method in predicting outcome, and suggests the need to consider ERICA values for clinical decision making.