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Breast cancer is a major health problem, and disease control depends on an effective healthcare system. A registry-based tool to monitor the quality of breast cancer care could be useful. The aim of this study was to develop a population survival model for breast cancer based on the Nottingham Prognostic Model (NPM). To this end, 1452 cases of breast cancer diagnosed in the Umbria Region, Italy, during the period 1994-1996 were studied. An extensive search for routinely available variants in prognosis and treatment was performed. In about 80% of cases complete information on factors included in the NPM was available. The Cox model was used to assess the prognostic value of study factors. Nodal stage was the most important prognostic factor. In women who did not undergo axillary dissection (17%) the risk of death was twice that in women with no affected nodes, but they received chemotherapy with the same frequency. Radiotherapy was also less frequently used in this group. Grading was a significant prognostic factor only when women over 80 were excluded. Population survival models based on data from cancer registries may provide a tool that can be used to evaluate healthcare systems and the effectiveness of interventions. The inclusion of older women in our models decreased the significance of many established prognostic factors because of the frequency of incomplete evaluation and less aggressive treatment in these patients. Not undergoing surgical axillary dissection was associated with a worse prognosis and with less aggressive treatment.

The search for single independent prognostic factors in breast cancer has often produced conflicting results. Therefore, prognostic indexes have been compiled by combining several parameters. In this study we compare the Nottingham Prognostic Index (NPI), which is based on traditional prognostic factors (diameter of the neoplasm, lymph node status and histological grade) with the Adelaide Prognostic Index (API), which is based on the tumour diameter and two biological parameters: oestrogen receptors and cell kinetics. We considered 82 cases of breast cancer observed over the period 1987-1990 with a minimum follow-up of 60 months. The NPI gives a better definition of the prognostic profile for each patient. Our results indicate three prognostic groups (good, moderate, unfavourable), which differ with respect to disease-free survival (DFS; P=0.0024) and overall survival (OS; P=0.0033). In contrast, the API scores showed no significant correlation with OS or DFS. The use of prognostic indexes, especially when compiled using traditional parameters, is a useful aid to the clinician, since they can provide a reliable indication of how individual tumours will evolve.

Literature data suggest that breast cancers occurring in young patients may be different from those arising in older women. In this study the clinicopathologic characteristics of 50 patients under 40 years of age were compared with those of patients aged over 60. Patients under 40 years old more frequently had a family history of breast cancer than did older patients (24% vs 17%) and had more often used oral contraceptives (29% vs 13%); on average they had experienced menarche 1 year earlier. For early onset breast carcinomas there was a higher frequency of grade 3 tumours (38% vs 17%) and oestrogen receptor negativity (46% vs 20%). In addition, in younger patients the carcinomas were mostly DNA aneuploid (78% vs 58%), with a higher proliferation rate (48% vs 26%) and more frequent c-erbB-2 overexpression (48% vs 26%) and p53 alteration (30% vs 8%). Our data demonstrate that breast cancers arising in young women have a significantly different biopathological profile from those in older patients, with a predominance of unfavourable prognostic parameters.

Previously we have demonstrated that determination of oestrogen (ER) and progesterone (PR) receptors by immunocytochemical assay (ICA) on frozen sections (FS) and cytological smears with image analysis is effective for evaluating steroid receptors. The aim of this study was to determine concordance between ER and PR assessed by ICA on FS and paraffin sections (PS) both evaluated by image analysis. There were 115 breast carcinomas selected. For all cases, ER and PR determination was performed on FS and PS. Computer-assisted image analysis was performed using CAS 200. Results were expressed as percent positive area of neoplastic nuclei compared with total nuclear area of the examined neoplastic cells. Good correlation was demonstrated for both ER (r=0.759; concordance=83.4%) and PR (r=0.800; concordance=87.8%). The unexpected relatively low concordance for ER led to further investigations. We divided the 115 cases in two groups. The first group included specimens from our hospital; the second group specimens from suburban hospitals. In the first group there was better correlation for both ER (r=0.897) and PR (r=0.915) with a concordance of 91.5% and 93.6%, respectively. In the second group, correlation was worse for both ER (r=0.724) and PR (r=0.708), with a concordance of 77.9% and 83.9% respectively. From analysis of discordant cases we conclude that reduction in correlation and concordance with increased false negative cases in group 2 are probably due to delayed fixation. Our data suggest that ICA with automated image analysis is efficient in evaluating ER and PR on paraffin section only when the tumour samples are correctly fixed.

We describe a case of leiomyoma in the breast in a 48-year-old woman. The main clinical-pathologic features together with the differential diagnosis, and the pertinent literature reviewed.