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Morphologic complexity of epithelial architecture for predicting invasive breast cancer survival

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 thera...

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Autores principales: Tambasco, Mauro, Eliasziw, Misha, Magliocco, Anthony M
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3024250/
https://www.ncbi.nlm.nih.gov/pubmed/21194459
http://dx.doi.org/10.1186/1479-5876-8-140
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author Tambasco, Mauro
Eliasziw, Misha
Magliocco, Anthony M
author_facet Tambasco, Mauro
Eliasziw, Misha
Magliocco, Anthony M
author_sort Tambasco, Mauro
collection PubMed
description 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 (<1.56, N = 141), intermediate (1.56-1.75, N = 148), and high (>1.75, 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 (25.0%, 56.4%, and 69.4% for high, intermediate, and low fractal dimension, respectively, p < 0.001). Overall 10-year survival showed a similar association. Fractal dimension, nodal status, and grade were the only significant (P < 0.05) independent predictors for both disease-specific and overall survival. Among all of the prognosticators, the fractal dimension hazard ratio for disease-specific survival, 2.6 (95% confidence interval (CI) = 1.4,4.8; P = 0.002), was second only to the slightly higher hazard ratio of 3.1 (95% CI = 1.9,5.1; P < 0.001) for nodal status. As for overall survival, fractal dimension had the highest hazard ratio, 2.7 (95% CI = 1.6,4.7); P < 0.001). Split-sample cross-validation analysis suggests these results are generalizable. CONCLUSION: Except for nodal status, morphologic complexity of breast epithelium as measured quantitatively by fractal dimension was more strongly and significantly associated with disease-specific and overall survival than standard prognosticators.
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spelling pubmed-30242502011-01-21 Morphologic complexity of epithelial architecture for predicting invasive breast cancer survival Tambasco, Mauro Eliasziw, Misha Magliocco, Anthony M J Transl Med Research 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 (<1.56, N = 141), intermediate (1.56-1.75, N = 148), and high (>1.75, 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 (25.0%, 56.4%, and 69.4% for high, intermediate, and low fractal dimension, respectively, p < 0.001). Overall 10-year survival showed a similar association. Fractal dimension, nodal status, and grade were the only significant (P < 0.05) independent predictors for both disease-specific and overall survival. Among all of the prognosticators, the fractal dimension hazard ratio for disease-specific survival, 2.6 (95% confidence interval (CI) = 1.4,4.8; P = 0.002), was second only to the slightly higher hazard ratio of 3.1 (95% CI = 1.9,5.1; P < 0.001) for nodal status. As for overall survival, fractal dimension had the highest hazard ratio, 2.7 (95% CI = 1.6,4.7); P < 0.001). Split-sample cross-validation analysis suggests these results are generalizable. CONCLUSION: Except for nodal status, morphologic complexity of breast epithelium as measured quantitatively by fractal dimension was more strongly and significantly associated with disease-specific and overall survival than standard prognosticators. BioMed Central 2010-12-31 /pmc/articles/PMC3024250/ /pubmed/21194459 http://dx.doi.org/10.1186/1479-5876-8-140 Text en Copyright ©2010 Tambasco et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<url>http://creativecommons.org/licenses/by/2.0</url>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Tambasco, Mauro
Eliasziw, Misha
Magliocco, Anthony M
Morphologic complexity of epithelial architecture for predicting invasive breast cancer survival
title Morphologic complexity of epithelial architecture for predicting invasive breast cancer survival
title_full Morphologic complexity of epithelial architecture for predicting invasive breast cancer survival
title_fullStr Morphologic complexity of epithelial architecture for predicting invasive breast cancer survival
title_full_unstemmed Morphologic complexity of epithelial architecture for predicting invasive breast cancer survival
title_short Morphologic complexity of epithelial architecture for predicting invasive breast cancer survival
title_sort morphologic complexity of epithelial architecture for predicting invasive breast cancer survival
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3024250/
https://www.ncbi.nlm.nih.gov/pubmed/21194459
http://dx.doi.org/10.1186/1479-5876-8-140
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