Prognostic value of progesterone receptor after long-term follow-up in primary breast cancer

Molecular pathology of breast cancer: the journey from traditional practice toward embracing the complexity of a molecular classification

CONTEXT

Adenocarcinoma of the breast is the most frequent cancer affecting women in both developed and developing regions of the world. From the moment of clinical presentation until the time of pathologic diagnosis, patients affected by this disease will face daunting questions related to prognosis and treatment options. While improvements in targeted therapies have led to increased patient survival, these same advances have created the imperative to accurately stratify patients to achieve maximum therapeutic efficacy while minimizing side effects. In this evolving era of personalized medicine, there is an ever-increasing need to overcome the limitations of traditional diagnostic practice.

OBJECTIVE

To summarize the molecular diagnostics traditionally used to guide prognostication and treatment of breast carcinomas, to highlight published data on the molecular classification of these tumors, and to showcase molecular assays that will supplement traditional methods of categorizing the disease.

DATA SOURCES

A review of the literature covering the molecular diagnostics of breast carcinomas with a focus on the gene expression and array studies used to characterize the molecular signatures of the disease. Special emphasis is placed on summarizing evolving technologies useful in the diagnosis and characterization of breast carcinoma.

CONCLUSIONS

Available and emerging molecular resources will allow pathologists to provide superior diagnostic, prognostic, and predictive information about individual breast carcinomas. These advances should translate into earlier identification and tailored therapy and should ultimately improve outcome for patients affected by this disease.

Predictive and prognostic markers for invasive breast cancer

Breast cancer is one of the most serious carcinomas among women worldwide, yet there are now encouraging signs that improvements in the mortality rate may be possible. The use of hormone therapy and chemotherapy has been widely accepted as treatment for breast cancer. Predictive factors can be used to predict response or lack of response to a particular therapy, and prognostic factors can be useful in making decisions about which patients should receive adjuvant therapy. Histopathology remains the universal basis of diagnosis, with the identification of new surrogate markers for potential new treatments. These are aimed at blocking tumor cell proliferation, neutralizing growth factors, stimulating apoptosis and blocking metastasis, and represent an integral part of new approaches for improving clinical management of patients with breast cancer. We review the standard predictive and prognostic factors that are routinely available today, and also describe some of the new, potential markers that are currently under investigation.

[Temporary dependency of steroid-receptor prognostic value in breast cancer]

BACKGROUND

The influence of prognostic factors in breast cancer may change during follow-up. Our aim was therefore to look for time-related changes in hazard ratios for steroid receptor status and the risk of relapse.

PATIENTS AND METHOD

We studied 455 patients with operable primary breast cancer during a mean follow-up period of 72 months (range, 42-130 months). Clinical and histological characteristics were assessed and estrogen receptor (ER) and progesterone receptor (PgR) status were determined and compared to disease-free survival (DFS) and overall survival (OS). Analysis of DFS included fitting a multivariate Cox proportional hazards model, testing for non-proportionality, and examining diagnostic plots.

RESULTS

A total of 66.8% of the tumors were ER positive and 54.7% PgR positive. Receptor status is highly associated with menopausal status, histological grade, peritumoral lymphatic or blood vessel invasion and mitotic index. No correlation was found between steroid receptor status and tumor size, node status or tumor stage. In univariate analysis, ER/PR vs ER+/PR+ display a hazard ratio of 2.15 (IC del 95%, 1.59-2.99) for DFS (p = 0.001) and 1.95 (IC del 95%, 1.38-2.59) for OS (p = 0.0043). In multivariate analysis, steroid receptor status, node status and mitotic index were independent prognostic factors for DFS and OS. By using Cox regression time-dependent covariates model, we show that the steroid receptor status hazard ratio is 5.6 at diagnosis, decreases after 4 years, and loses its significance after 10 years of follow-up.

CONCLUSION

In patients with breast cancer the status steroid receptor have a relatively limited prognostic value and is lost within the first years.

Prognostic role of oestrogen and progesterone receptors in patients with breast cancer: relation to age and lymph node status

AIMS

To consider the prognostic role of oestrogen receptor and progesterone receptor status in relation to the age at surgery, length of follow up and lymph node status.

METHODS

The study population comprised 977 patients with histologically confirmed breast carcinoma, with a median follow up of nine years. The actuarial life table method was used to test for survival differences. The Cox proportional hazard model was used to test for interaction effects between each hormone receptor and age, lymph node status and length of follow up. As the analysis involved multiple subgroups, significance was set at the 1% level (p < 0.01).

RESULTS

When the patients were subdivided into groups according to lymph node status and age, progesterone and oestrogen receptor status predicted prognosis in middle aged (46-60 years) patients with lymph node positive breast cancer. Their prognostic effect in this subgroup, however, was restricted to the first five years after surgery. Progesterone receptor status was the strongest predictor of outcome.

CONCLUSION

The prognostic power of oestrogen and progesterone receptor status varies depending on age, lymph node status and length of follow up after surgery.