Factors affecting distant disease-free survival for primary invasive breast cancer: use of a log-normal survival model.

Abstract

Invasive breast cancer is a frequently diagnosed disease that now comes with an ever expanding array of therapeutic management options. We assessed the effects of 20 prognostic factors in a multivariate context. We accrued clinical data for 156 consecutive patients with stage 1-3 primary invasive breast cancer who were diagnosed in 1989-1990 at the Henrietta Banting Breast Center, and followed to 1995. There is complete follow-up for 91% of patients (median follow-up of 4.9 years). The event of interest was distant recurrence (for distant disease-free survival, DFS). We used Cox and log-normal step-wise regression to assess the multivariate effects of the following factors on DFS: age, tumor size, nodal status, histology, tumor and nuclear grade, lymphovascular and perineural invasion (LVPI), ductal carcinoma-in-situ (DCIS) type, DCIS extent, DCIS at edge of tumor, ER and PgR, ERICA, adjuvant systemic therapy, ki67, S-phase, DNA index, neu oncogene, and pRb. There was strong evidence against the Cox assumption of proportional hazards for nodal status, and nodal status was not in the Cox step-wise model. With step-wise log-normal regression, a large tumor size (P < .001), positive nodes (P = .002), high nuclear grade (P = .01), presence of LVPI (P = .03), and infiltrating duct carcinoma not otherwise specified (P = .05) were associated with a reduction in DFS. For nodal status, there was strong evidence against the Cox assumption of proportional hazards, and it was not included in the Cox model although it was in the log-normal model. Only traditional factors were included in the step-wise models. Thus, this statistical management of prognostic markers in breast cancer appears to be very important.