PROGNOSTICATION OF BREAST CANCER BY MULTIVARIATE METHODS.

Three multivariate prognostic models based on Cox's regression were tested in terms of how they predicted prognosis in a material of 134 patients with breast cancer. The multivariate models all incorporated tumor size, mitotic activity index (MAI), and axillary lymph node status in their formulas, and were originally produced through studies on different patient materials. The predictive behavior of MAI was also tested separately in the same material. The multivariate models gave roughly parallel predicted percentages of survival at two years (CV=5.2%), but showed clearly greater variation later (12.3% and 24.4% at 5 and 9 years, respectively). The results were more uniform between the multivariate models, than between the prediction by MAI and the multivariate models. The variation between repeated estimates was smaller within multivariate models than within the estimation of one of their components (MAI). We found the use of the multivariate models easy. However, traditional hospital practice does not necessarily favor the use of multivariate models, although they seem to group patients more reliably than single prognostic features.