Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Morphologic complexity of epithelial architecture for predicting invasive breast cancer survival | Tambasco et al. Journal of Translational Medicine 2010 8 140 http content 8 1 140 TRANSLATIONAL MEDICINE RESEARCH Open Access Morphologic complexity of epithelial architecture for predicting invasive breast cancer survival Mauro Tambasco1 2 3 Misha Eliasziw1 4 Anthony M Magliocco1 2 5 Abstract Background Precise criteria for optimal patient selection for adjuvant chemotherapy remain controversial and include subjective components such as tumour morphometry pathological grade . There is a need to replace subjective criteria with objective measurements to improve risk assessment and therapeutic decisions. We assessed the prognostic value of fractal dimension an objective measure of morphologic complexity for invasive ductal carcinoma of the breast. Methods We applied fractal analysis to pan-cytokeratin stained tissue microarray TMA cores derived from 379 patients. Patients were categorized according to low N 141 intermediate N 148 and high N 90 fractal dimension. Cox proportional-hazards regression was used to assess the relationship between disease-specific and overall survival and fractal dimension tumour size grade nodal status estrogen receptor status and HER-2 neu status. Results Patients with higher fractal score had significantly lower disease-specific 10-year survival and for high intermediate and low fractal dimension respectively p . Overall 10-year survival showed a similar association. Fractal dimension nodal status and grade were the only significant P independent predictors for both disease-specific and overall survival. Among all of the prognosticators the fractal dimension hazard ratio for disease-specific survival 95 confidence interval CI P was second only to the slightly higher hazard ratio of 95 CI P for nodal status. As for overall survival fractal dimension had the highest hazard ratio 95 CI P . Split-sample .
