PREDICTING AXILLARY LYMPH-NODE METASTASES IN BREAST-CARCINOMA PATIENTS

Routine axillary dissection is primarily used as a means of assessing prognosis to establish appropriate treatment plans for patients with p rimary breast carcinoma. However, axillary dissection offers no therap eutic benefit to node negative patients and patients may incur unneces sary morbidity, including mild to severe impairment of arm motion and lymphedema, as a result. This paper outlines a method of evaluating th e probability of harbouring lymph node metastases at the time of initi al surgery by assessment of tumour based parameters, in order to provi de an objective basis for further selection of patients for treatment or investigation. The novel aspect of this study is the use of Maximum Entropy Estimation (MEE) to construct probabilistic models of the rel ationship between the risk factors and the outcome. Two hundred and se venteen patients with invasive breast carcinoma were studied. Surgical treatment included axillary clearance in all cases, so that the patho logic status of the nodes was known. Tumour size was found to be signi ficantly correlated (P < 0.001) to the axillary lymph node status in t he multivariate analysis with age (P = 0.089) and vascular invasion (P = 0.08) marginally correlated. Using the multivariate model construct ed, 38 patients were predicted to have risk of nodal metastases lower than 20%, of these only 4 (10%) patients had lymph node metastases. A comparison with the Multivariate Logistic Regression (MLR) was carried out. It was found that the predictive quality of the MEE model was be tter than that of the MLR model. In view of the small sample size, fur ther verification of this model is required in assessing its practical application to a larger population.