A simple index to predict prognosis independent of axillary node information in breast cancer

Prognostic indexes in breast cancer: comparison of the Nottingham and Adelaide indexes

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.

Role of expression of cell cycle inhibitor p27 and MIB-1 in predicting lymph node metastasis in male breast carcinoma

Tumor expression of the proliferation marker (MIB-1) and the cell cycle-related protein (p27) may predict the biologic behavior of various human tumors. The purpose of this study was to evaluate the role of p27 and MIB-1 expression in predicting lymph node metastasis in male breast carcinomas (MBCs). We studied 67 patients with invasive MBC who had undergone modified radical mastectomy. Pathologic lymph node status was correlated with the p27 protein and the MIB-1 proliferation index. These factors were studied immunohistologically by standard methods. Men in this study ranged from 36 to 92 years of age (mean, 63 years); 43 (64%) were T1 lesions, and 24 (36%) were T2 lesions. Twenty-nine patients (43%) had positive nodes. p27 was expressed in 43 tumors (64%) and MIB-1 in 13 tumors (19.4%). Tumors with positive p27 showed positive lymph nodes in 10 cases (23%). In contrast, p27-negative tumors had positive lymph nodes in 18 cases (75%). Tumors positive for MIB-1 show positive lymph nodes in 11 cases (85%). However, when MIB-1 was negative, only 16 patients (30%) had positive lymph nodes. Multivariate logistic regression analysis confirmed the utility of MIB-1 overexpression in predicting lymph node metastasis ( p < 0.0006). Also, decreased p27 protein expression strongly correlates with lymph node metastasis ( p < or = 0.0001). Furthermore, when p27 was negative and MIB-1 was positive, 100% of the patients had positive lymph nodes. In contrast, when p27 was positive and MIB-1 was negative, only 12% of patients had positive lymph nodes. The reduced expression of the p27 protein and the overexpression of the MIB-1 proliferation index in this study show a significant correlation in predicting lymph nodes metastasis in MBCs.

Biologic markers in ductal carcinoma in situ and concurrent infiltrating carcinoma. A comparison of eight contemporary grading systems

The relevance of 8 contemporary classification and grading systems for ductal carcinoma in situ (DCIS) of the breast was examined in 100 tumors by comparing DCIS grade with grade of the concurrent infiltrating ductal carcinoma (IDC). Besides tumor size and nodal status, the immunohistochemical parameters in both lesions were compared, including estrogen receptor, progesterone receptor, c-erbB-2 protein, E-cadherin, vimentin, Ki-67 (MIB1), and p27. Nuclear grading of DCIS alone or in combination with architectural pattern and necrosis showed the best correlation with grade of the invasive component. There also was a positive correlation between every biologic marker expressed in DCIS and in the concurrent IDC, supporting a clonal relationship. Biologic markers varied between the different grades of DCIS. DCIS is heterogeneous, and the progression of DCIS to IDC may be from low-grade DCIS to low-grade IDC and high-grade DCIS to high-grade IDC. This concept is different from the conventional model held for intraepithelial neoplasia in the cervix, vulva, vagina, and skin, in which there is increasing severity of in situ atypia (dysplasia) before the development of stromal invasion.

A simple index using video image analysis to predict disease outcome in primary breast cancer

Image analysis was used to investigate the prognostic significance of immunostaining for oestrogen receptor (ER), p53 tumour-suppressor protein and tumour cell proliferation (MIB-1) in a random cohort of 200 primary breast cancer patients with between 4 and 7 years of clinical follow-up. Image measurements of the percentage of immunopositive cancer cell nuclei (% positive nuclear area) were recorded for the above tumour features for each patient. Assessment of relative risk using Cox's univariate analysis indicated that tumour size, number of cancer-involved nodes, MIB-1 and ER % positive nuclear area were significantly associated with breast cancer disease outcome, i.e., relapse-free survival and overall survival. In multivariate analysis, tumour size, number of involved nodes, ER and MIB-1 % positive nuclear area were retained as independent predictors of prognosis, depending on the image measurement cut-point used. A prognostic model, which can be used without reference to nodal involvement, was constructed for tumour size, ER cut-point of 30% positive nuclear area and MIB-1 cut-point of 10% positive nuclear area. Kaplan-Meier analysis of this image-based prognostic index identified 4 risk groups with predicted 5-year overall survival rates of 93%, 83%, 76.7% and 61.5%. We conclude that image measurements of ER and proliferative rate can be combined with tumour size to construct a prognostic index which reliably predicts disease outcome in primary breast cancer without knowledge of the nodal status of the patient.