Molecular subtypes of breast cancer: prognostic implications and clinical and immunohistochemical characteristics

Fundamento. Los carcinomas de mama representan un grupo heterogéneo de tumores, tanto en su comportamiento clínico como pronóstico. El objetivo del presente trabajo es clasificar los carcinomas de mama en subtipos moleculares mediante marcadores inmunohistoquímicos y analizar las características clinicopatológicas e inmunohistoquímicas y los patrones de supervivencia y recaída de los distintos subtipos. Material y métodos. Se han clasificado 272 pacientes con diagnóstico de carcinoma de mama en cinco subtipos: carcinomas de mama de tipo basal, de tipo HER2, de tipo luminal A, de tipo luminal B y normal. Resultados. Los carcinomas de mama más frecuentes fueron los de tipo luminal A (62,5%), carcinomas de tipo luminal B (18%), carcinomas de tipo HER2 (9,9%), carcinomas de tipo basal (8,4%) y los de fenotipo normal (1,4%). Los carcinomas de mama de tipo luminal mostraron ser, con mayor frecuencia, de forma significativa, tumores bien diferenciados, de pequeño tamaño tumoral, con ganglios axilares negativos, estadio precoz en el momento del diagnóstico, niveles altos de BCL-2 y bajo índice de proliferación con Ki-67. En cambio, los carcinomas de mama de tipo basal y HER2 presentaban tumores de mayor tamaño, pobremente diferenciados, mayor compromiso ganglionar y estadios más avanzados en el momento del diagnóstico. Expresaban con mayor frecuencia índices de proliferación altos con Ki 67 y fueron los subtipos que en curvas de supervivencia global y de supervivencia libre de progresión mostraron un peor pronóstico. Conclusión. La clasificación del cáncer de mama basada en parámetros inmunohistoquímicos (IHQ) permite una mejor definición pronóstica. Tanto los carcinomas de mama de tipo basal como HER2 presentan características histopatológicas e IHQ más desfavorables así como peor supervivencia y menor tiempo de recaída mientras que los carcinomas de mama de tipo luminal manifiestan características más benignas y mejor pronóstico.Background. Breast carcinomas are a heterogeneous group of tumours, in both their clinical behavior and their prognosis. The aim of this article is to classify breast carcinomas according to molecular subtypes by means of immunohistochemical markers and to analyse the clinicopathological and immunohistochemical characteristics and the patterns of survival and relapse of the different subtypes. Methods. Two hundred and seventy-two patients diagnosed with breast cancer were classified into five subtypes: breast carcinomas of the basal type, HER2 type, luminal A type, luminal B type and normal. Results. The most frequent breast carcinomas were: luminal A type carcinomas (62.5%), luminal B type carcinomas (18%), HER2 type carcinomas (9.9%), basal type carcinomas (8.4%) and normal phenotype carcinomas (1.4%). Significantly and with greater frequency, the luminal type breast carcinomas proved to be well differentiated tumours, of small tumoral size, with negative axillary lymph nodes, at an early stage at the time of diagnosis, with high levels of BCL- 2 and a low Ki-67 proliferation index. On the contrary, the basal type and HER2 carcinomas presented larger tumours, poorly differentiated, greater ganglionar involvement and more advanced stages at the time of diagnosis. They expressed high Ki-67 proliferation indexes with greater frequency and were the subtypes that showed a worse prognosis on global survival and progression-free survival curves. Conclusion. Breast cancer classification based on immunohistochemical (IHC) parameters makes a better prognostic definition possible. Both the basal type and the HER2 type breast carcinomas present more unfavourable histopathological and IHC characteristics, as well as a worse survival and less relapse time, while the luminal type breast carcinomas show more benign characteristics and a better prognosis

Shared component modelling as an alternative to assess geographical variations in medical practice: gender inequalities in hospital admissions for chronic diseases

<p>Abstract</p> <p>Background</p> <p>Small area analysis is the most prevalent methodological approach in the study of unwarranted and systematic variation in medical practice at geographical level. Several of its limitations drive researchers to use disease mapping methods -deemed as a valuable alternative. This work aims at exploring these techniques using - as a case of study- the gender differences in rates of hospitalization in elderly patients with chronic diseases.</p> <p>Methods</p> <p>Design and study setting: An empirical study of 538,358 hospitalizations affecting individuals aged over 75, who were admitted due to a chronic condition in 2006, were used to compare Small Area Analysis (SAVA), the Besag-York-Mollie (BYM) modelling and the Shared Component Modelling (SCM). Main endpoint: Gender spatial variation was measured, as follows: SAVA estimated gender-specific utilization ratio; BYM estimated the fraction of variance attributable to spatial correlation in each gender; and, SCM estimated the fraction of variance shared by the two genders, and those specific for each one.</p> <p>Results</p> <p>Hospitalization rates due to chronic diseases in the elderly were higher in men (median per area 21.4 per 100 inhabitants, interquartile range: 17.6 to 25.0) than in women (median per area 13.7 per 100, interquartile range: 10.8 to 16.6). Whereas Utilization Ratios showed a similar geographical pattern of variation in both genders, BYM found a high fraction of variation attributable to spatial correlation in both men (71%, CI95%: 50 to 94) and women (62%, CI95%: 45 to 77). In turn, SCM showed that the geographical admission pattern was mainly shared, with just 6% (CI95%: 4 to 8) of variation specific to the women component.</p> <p>Conclusions</p> <p>Whereas SAVA and BYM focused on the magnitude of variation and on allocating where variability cannot be due to chance, SCM signalled discrepant areas where latent factors would differently affect men and women.</p