RT Journal Article
T1 Intraoperative predictive model for the detection of metastasis in non-sentinel axillary lymph nodes
A1 Antonio Garcia-Mejido, Jose
A1 Sanchez-Sevilla, Miguel
A1 Garcia-Jimenez, Rocio
A1 Fernandez-Palacin, Ana
A1 Antonio-Sainz, Jose
K1 Breast cancer
K1 One-step nucleic acid amplification
K1 Sentinel lymph-node
K1 Non-sentinel lymph-node metastasis
K1 Axillary lymph-node dissection
K1 Total tumor load
K1 Nucleic-acid amplification
K1 Breast-cancer patients
K1 Tumor load
K1 Dissection
K1 Nomogram
K1 Biopsy
K1 Assay
K1 Osna
K1 Women
AB Background: To design a software-applied predictive model relating patients clinical and pathological traits associated with sentinel lymph-node total tumor load to individually establish the need to perform an axillary lymph-node dissection. Methods: Retrospective observational study including 127 patients with breast cancer in which a sentinel lymph-node biopsy was performed with the one step nucleic acid amplification method and a subsequent axillary lymph-node dissection. We created various binary multivariate logistic regression models using non-automated methods to predict the presence of metastasis in non-sentinel lymph-nodes, including Log total tumor load, immunohistochemistry, multicentricity and progesterone receptors. These parameters were progressively added according to the simplicity of their evaluation and their predictive value to detect metastasis in non-sentinel lymph-nodes. Results: The final model was selected for having maximum discriminatory capability, good calibration, along with parsimony and interpretability. The binary logistic regression model chosen was the one which identified the variables Log total tumor load, immunohistochemistry, multicentricity and progesterone receptors as predictors of metastasis in non-sentinel lymph-nodes. liarrell's C-index obtained from the area under the curve of the predicted probabilities by Model 4 was 0.77 (95% CI, (1.689-0.85; p
PB Imr press
SN 0390-6663
YR 2022
FD 2022-04-01
LK http://hdl.handle.net/10668/21805
UL http://hdl.handle.net/10668/21805
LA en
DS RISalud
RD Apr 7, 2025