COMPUTER-DERIVED NUCLEAR FEATURES COMPARED WITH AXILLARY LYMPH-NODE STATUS FOR BREAST-CARCINOMA PROGNOSIS

BACKGROUND. Both axillary lymph node involvement and tumor anaplasia, as expressed by visually assessed grade, have been shown to be prognos tically important in breast carcinoma outcome. In this study, axillary lymph node involvement was used as the standard against which prognos tic estimations based on computer-derived nuclear features were gauged , METHODS, The prognostic significance of nuclear morphometric feature s determined by computer-based image analysis were analyzed in 198 con secutive preop preoperative samples obtained by fine-needle aspiration (FNA) from patients with invasive breast carcinoma. A novel multivari ate prediction method was used to model the time of distant recurrence as a function of the nuclear features. Prognostic predictions based o n the nuclear feature data were cross-validated to avoid overly optimi stic conclusions. The estimated accuracy of these prognostic determina tions was compared with determinations based on the extent of axillary lymph node involvement. RESULTS. The predicted outcomes based on nucl ear features were divided into three groups representing best, interme diate, and worst prognosis, and compared with the traditional TNM lymp h node stratification. Nuclear feature stratification better separated the prognostically best from the intermediate group whereas lymph nod e stratification better separated the prognostically intermediate from the worst group. Prognostic accuracy was not increased by adding lymp h node status or tumor size to the nuclear features. CONCLUSIONS. Comp uter analysis of a preoperative FNA more accurately identified prognos tically favorable patients than did pathologic examination of axillary lymph nodes and may obviate the need for routine axillary lymph node dissection. (C) 1997 American Cancer Society.