RESUMEN
INTRODUCTION: Mammographic density is well-established as a risk factor for breast cancer, however, adjustment for age and body mass index (BMI) is vital to its clinical interpretation when assessing individual risk. In this paper we develop a model to adjust mammographic density for age and BMI and show how this adjusted mammographic density measure might be used with existing risk prediction models to identify high-risk women more precisely. METHODS: We explored the association between age, BMI, visually assessed percent dense area and breast cancer risk in a nested case-control study of women from the placebo arm of the International Breast Cancer Intervention Study I (72 cases, 486 controls). Linear regression was used to adjust mammographic density for age and BMI. This adjusted measure was evaluated in a multivariable logistic regression model that included the Tyrer-Cuzick (TC) risk score, which is based on classical breast cancer risk factors. RESULTS: Percent dense area adjusted for age and BMI (the density residual) was a stronger measure of breast cancer risk than unadjusted percent dense area (odds ratio per standard deviation 1.55 versus 1.38; area under the curve (AUC) 0.62 versus 0.59). Furthermore, in this population at increased risk of breast cancer, the density residual added information beyond that obtained from the TC model alone, with the AUC for the model containing both TC risk and density residual being 0.62 compared to 0.51 for the model containing TC risk alone (P =0.002). CONCLUSIONS: In women at high risk of breast cancer, adjusting percent mammographic density for age and BMI provides additional predictive information to the TC risk score, which already incorporates BMI, age, family history and other classic breast cancer risk factors. Furthermore, simple selection criteria can be developed using mammographic density, age and BMI to identify women at increased risk in a clinical setting. CLINICAL TRIAL REGISTRATION NUMBER: http://www.controlled-trials.com/ISRCTN91879928 (Registered: 1 June 2006).
Asunto(s)
Neoplasias de la Mama/patología , Glándulas Mamarias Humanas/anomalías , Antineoplásicos Hormonales/uso terapéutico , Densidad de la Mama , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/tratamiento farmacológico , Femenino , Humanos , Glándulas Mamarias Humanas/patología , Mamografía , Persona de Mediana Edad , Estudios Multicéntricos como Asunto , Placebos , Ensayos Clínicos Controlados Aleatorios como Asunto , Factores de Riesgo , Tamoxifeno/uso terapéuticoRESUMEN
Epithelial tissues have sparse stroma, in contrast to their corresponding tumours. The effect of cancer cells on stromal cells is well recognized. Increasingly, stromal components, such as endothelial and immune cells, are considered indispensable for cancer progression. The role of desmoplastic stroma, in contrast, is poorly understood. Targeting such cellular components within the tumour is attractive. Recent evidence strongly points towards a dynamic stromal cell participation in cancer progression that impacts patient prognosis. The role of specific desmoplastic stromal cells, such as stellate cells and myofibroblasts in pancreatic, oesophageal and skin cancers, was studied in bio-engineered, physiomimetic organotypic cultures and by regression analysis. For pancreatic cancer, the maximal effect on increasing cancer cell proliferation and invasion, as well as decreasing cancer cell apoptosis, occurs when stromal (pancreatic stellate cells) cells constitute the majority of the cellular population (maximal effect at a stromal cell proportion of 0.66-0.83), accompanied by change in expression of key molecules such as E-cadherin and ß-catenin. Gene-expression microarrays, across three tumour types, indicate that stromal cells consistently and significantly alter global cancer cell functions such as cell cycle, cell-cell signalling, cell movement, cell death and inflammatory response. However, these changes are mediated through cancer type-specific alteration of expression, with very few common targets across tumour types. As highlighted by these in vitro data, the reciprocal relationship of E-cadherin and polymeric immunoglobulin receptor (PIGR) expression in cancer cells could be shown, in vivo, to be dependent on the stromal content of human pancreatic cancer. These studies demonstrate that context-specific cancer-stroma crosstalk requires to be precisely defined for effective therapeutic targeting. These data may be relevant to non-malignant processes where epithelial cells interact with stromal cells, such as chronic inflammatory and fibrotic conditions.