AIMS: The purpose was to identify the independent predictive factors of axillary lymph-node metastases (ALNM) in infiltrating ductal carcinoma (IFDC) and to create a prospective, validated statistical model to predict the likelihood of ALNM in patients in the present era of sentinel lymph-node (SLN) biopsy and enhanced histopathology. METHODS: Univariate and multivariate analyses of 13 clinicopathological variables (including tumour location) were performed to determine predictors of ALNM in 1659 eligible SLN biopsy procedures. A logistic regression model was developed and then prospectively validated on a second population of 187 subsequent consecutive procedures. RESULTS: Age, pathological tumour size, palpability, lymphovascular invasion (LVI), histological grade, nuclear grade, ductal histological subtype, tumour location (quadrant) and multifocality were associated with ALNM in univariate analyses (P < 0.001). Of these, only palpability and histological grade were not statistically associated with ALNM in the multivariate analysis (P> 0.05). The frequency of ALNM in upper-inner-quadrant (UIQ) tumours was 20.6%, compared with 33.2% for all other quadrants (P<0.0005). There was no statistical difference between UIQ and other-quadrant tumours in any clinicopathological variables analysed. The logistic regression model, developed based on the population of 1659, had the same accuracy, sensitivity, specificity, positive predictive value and negative predictive value when applied prospectively to the second population. CONCLUSION: Tumour size, LVI, age, nuclear grade, histological subtype, multifocality and location in the breast were independent predictive factors for ALNM in IFDC. ALNM is less frequent in UIQ tumours than in other-quadrant tumours. Our prospectively validated predictive model could be valuable in pre-operative patient discussions, although staging of the axilla in the individual patient remains necessary.
AIMS: The purpose was to identify the independent predictive factors of axillary lymph-node metastases (ALNM) in infiltrating ductal carcinoma (IFDC) and to create a prospective, validated statistical model to predict the likelihood of ALNM in patients in the present era of sentinel lymph-node (SLN) biopsy and enhanced histopathology. METHODS: Univariate and multivariate analyses of 13 clinicopathological variables (including tumour location) were performed to determine predictors of ALNM in 1659 eligible SLN biopsy procedures. A logistic regression model was developed and then prospectively validated on a second population of 187 subsequent consecutive procedures. RESULTS: Age, pathological tumour size, palpability, lymphovascular invasion (LVI), histological grade, nuclear grade, ductal histological subtype, tumour location (quadrant) and multifocality were associated with ALNM in univariate analyses (P < 0.001). Of these, only palpability and histological grade were not statistically associated with ALNM in the multivariate analysis (P> 0.05). The frequency of ALNM in upper-inner-quadrant (UIQ) tumours was 20.6%, compared with 33.2% for all other quadrants (P<0.0005). There was no statistical difference between UIQ and other-quadrant tumours in any clinicopathological variables analysed. The logistic regression model, developed based on the population of 1659, had the same accuracy, sensitivity, specificity, positive predictive value and negative predictive value when applied prospectively to the second population. CONCLUSION:Tumour size, LVI, age, nuclear grade, histological subtype, multifocality and location in the breast were independent predictive factors for ALNM in IFDC. ALNM is less frequent in UIQ tumours than in other-quadrant tumours. Our prospectively validated predictive model could be valuable in pre-operative patient discussions, although staging of the axilla in the individual patient remains necessary.
Authors: M Barry; R A Cahill; G Roche-Nagle; R Landers; D Walsh; D J Bouchier-Hayes; R G K Watson Journal: Ir J Med Sci Date: 2007-05-03 Impact factor: 1.568
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Authors: Ann Smeets; Emi Yoshihara; Annouschka Laenen; Anneleen Reynders; Julie Soens; Hans Wildiers; Robert Paridaens; Chantal Van Ongeval; Giuseppe Floris; Patrick Neven; Marie-Rose Christiaens Journal: Springerplus Date: 2013-06-23
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