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In 271 breast cancer patients with adequate follow-up for at least 5.5 and maximally 12 years, the value of morphometry to classic prognosticators of breast cancer (tumor size and axillary lymph node status) was assessed. Previous studies had indicated the value of this quantitative microscopic technique. Apart from quantitative microscopic features, subjective qualitative features such as nuclear and histologic grade were assessed as well. Univariate life-table analysis showed the significance (p less than 0.001) of several features such as lymph node status, tumor size, nuclear and histologic grade, and several morphometric variables (mitotic activity index, mean and standard deviation of nuclear area). Cellularity index was also significant (p = 0.02). Survival analysis with Cox's regression model, using a stepwise selection as well as backwards elimination, pointed to three features: mitotic activity index, tumor size, and lymph node status. Mitotic activity was the most important prognostic feature, but the combination of these three features in a multivariate prognostic index had even more prognostic significance. Kaplan-Meier curves showed that the 5-year survival of lymph node-negative patients (n = 146) is 85%, versus 93% in patients with a "good prognosis index" (n = 150). For lymph node-positive patients (n = 125), 5-year survival was 55%, compared with 47% in the "high index" (poor prognosis) patients (n = 121). Logistic discriminant analysis with 5.5-year follow-up as a fixed endpoint (191 survivors and 80 nonsurvivors) essentially gave the same results. Application of two instead of one decision threshold (e.g., numerical classification probability 0.60 and 0.40) decrease the number of false-negative and false-positive outcomes, however, with a number of patients falling in the class "uncertain." Thus, in agreement with other studies, morphometry significantly adds to the prognosis prediction of lymph node status and tumor size. Mitotic activity index is the best single predictor of the prognosis. An additional index advantage is that the multivariate model results in a continuous index variable that can be subdivided in many classes with an increasing risk of recurrence, so that more refined clinical therapeutic decision making is possible in individual patient care. The morphometric techniques are inexpensive and fairly simple and therefore can be applied in most pathology laboratories.

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Morphometric methods were applied to predict the clinical course of individual patients with breast cancer. Measurement of tumour diameter, assessment of mitotic and cellular indices, and quantitative microscopy of nuclear features were assessed together with nuclear features and histological grades. Of the tumours from 78 patients investigated, 42 had died from metastases within 6.5 years ('non-survivors'), while the other 36 were alive and well without evidence of metastases at the end of the follow-up period (minimum 6.5 years) ('survivors'). If the tumours of the 42 non-survivors are compared with those of 36 survivors, there are many reproducible significant differences, the most important being cellularity index and mitotic activity index, followed by quantitative microscopical nuclear parameters and nuclear and histological grade. Discriminant analysis, of the quantitative microscopical data alone showed 82% of all patients to be correctly classified as survivor or non-survivor. By contrast with the axillary lymph node invasion status alone, or the tumour diameter and axillary lymph node status together, 59% and 64% of the patients were predicted correctly as survivor or non-survivor. With a more realistic statistical approach of discriminant analysis, 78% of the patients were classified correctly with quantitative microscopy, in place of 54% with the axillary lymph node status, 56% with the TNM-system and 64% with a combination of TNM system and nuclear and histological grade. Morphometry thus seems possible to predict the outcome of individual patients more accurately than with the usual staging/grading methods. This technique might therefore prove to be useful in the selection of patients for adjuvant chemotherapy.

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