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Predicting the extent of nodal involvement for node positive breast cancer patients: Development and validation of a novel tool

BACKGROUND: This study aimed to develop an easy to use prediction model to predict the risk of having a total of 1 to 2, ≥3, or ≥4 positive axillary lymph nodes (LNs), for patients with sentinel lymph node (SLN) positive breast cancer. METHODS: Data of 911 SLN positive breast cancer patients were us...

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Autores principales: van den Hoven, Ingrid, van Klaveren, David, Verheuvel, Nicole C., van la Parra, Raquel F. D., Voogd, Adri C., de Roos, Wilfred K., Bosscha, Koop, Heuts, Esther M., Tjan‐Heijnen, Vivianne C. G., Roumen, Rudi M. H., Steyerberg, Ewout W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6771524/
https://www.ncbi.nlm.nih.gov/pubmed/31338839
http://dx.doi.org/10.1002/jso.25644
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author van den Hoven, Ingrid
van Klaveren, David
Verheuvel, Nicole C.
van la Parra, Raquel F. D.
Voogd, Adri C.
de Roos, Wilfred K.
Bosscha, Koop
Heuts, Esther M.
Tjan‐Heijnen, Vivianne C. G.
Roumen, Rudi M. H.
Steyerberg, Ewout W.
author_facet van den Hoven, Ingrid
van Klaveren, David
Verheuvel, Nicole C.
van la Parra, Raquel F. D.
Voogd, Adri C.
de Roos, Wilfred K.
Bosscha, Koop
Heuts, Esther M.
Tjan‐Heijnen, Vivianne C. G.
Roumen, Rudi M. H.
Steyerberg, Ewout W.
author_sort van den Hoven, Ingrid
collection PubMed
description BACKGROUND: This study aimed to develop an easy to use prediction model to predict the risk of having a total of 1 to 2, ≥3, or ≥4 positive axillary lymph nodes (LNs), for patients with sentinel lymph node (SLN) positive breast cancer. METHODS: Data of 911 SLN positive breast cancer patients were used for model development. The model was validated externally in an independent population of 180 patients with SLN positive breast cancer. RESULTS: Final pathology after ALND showed additional positive LN for 259 (28%) of the patients. A total of 726 (81%) out of 911 patients had a total of 1 to 2 positive nodes, whereas 175 (19%) had ≥3 positive LNs. The model included three predictors: the tumor size (in mm), the presence of a negative SLN, and the size of the SLN metastases (in mm). At external validation, the model showed a good discriminative ability (area under the curve = 0.82; 95% confidence interval = 0.74‐0.90) and good calibration over the full range of predicted probabilities. CONCLUSION: This new and validated model predicts the extent of nodal involvement in node‐positive breast cancer and will be useful for counseling patients regarding their personalized axillary treatment.
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spelling pubmed-67715242019-10-03 Predicting the extent of nodal involvement for node positive breast cancer patients: Development and validation of a novel tool van den Hoven, Ingrid van Klaveren, David Verheuvel, Nicole C. van la Parra, Raquel F. D. Voogd, Adri C. de Roos, Wilfred K. Bosscha, Koop Heuts, Esther M. Tjan‐Heijnen, Vivianne C. G. Roumen, Rudi M. H. Steyerberg, Ewout W. J Surg Oncol Research Articles BACKGROUND: This study aimed to develop an easy to use prediction model to predict the risk of having a total of 1 to 2, ≥3, or ≥4 positive axillary lymph nodes (LNs), for patients with sentinel lymph node (SLN) positive breast cancer. METHODS: Data of 911 SLN positive breast cancer patients were used for model development. The model was validated externally in an independent population of 180 patients with SLN positive breast cancer. RESULTS: Final pathology after ALND showed additional positive LN for 259 (28%) of the patients. A total of 726 (81%) out of 911 patients had a total of 1 to 2 positive nodes, whereas 175 (19%) had ≥3 positive LNs. The model included three predictors: the tumor size (in mm), the presence of a negative SLN, and the size of the SLN metastases (in mm). At external validation, the model showed a good discriminative ability (area under the curve = 0.82; 95% confidence interval = 0.74‐0.90) and good calibration over the full range of predicted probabilities. CONCLUSION: This new and validated model predicts the extent of nodal involvement in node‐positive breast cancer and will be useful for counseling patients regarding their personalized axillary treatment. John Wiley and Sons Inc. 2019-07-23 2019-09-15 /pmc/articles/PMC6771524/ /pubmed/31338839 http://dx.doi.org/10.1002/jso.25644 Text en © 2019 The Authors. Journal of Surgical Oncology Published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Articles
van den Hoven, Ingrid
van Klaveren, David
Verheuvel, Nicole C.
van la Parra, Raquel F. D.
Voogd, Adri C.
de Roos, Wilfred K.
Bosscha, Koop
Heuts, Esther M.
Tjan‐Heijnen, Vivianne C. G.
Roumen, Rudi M. H.
Steyerberg, Ewout W.
Predicting the extent of nodal involvement for node positive breast cancer patients: Development and validation of a novel tool
title Predicting the extent of nodal involvement for node positive breast cancer patients: Development and validation of a novel tool
title_full Predicting the extent of nodal involvement for node positive breast cancer patients: Development and validation of a novel tool
title_fullStr Predicting the extent of nodal involvement for node positive breast cancer patients: Development and validation of a novel tool
title_full_unstemmed Predicting the extent of nodal involvement for node positive breast cancer patients: Development and validation of a novel tool
title_short Predicting the extent of nodal involvement for node positive breast cancer patients: Development and validation of a novel tool
title_sort predicting the extent of nodal involvement for node positive breast cancer patients: development and validation of a novel tool
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6771524/
https://www.ncbi.nlm.nih.gov/pubmed/31338839
http://dx.doi.org/10.1002/jso.25644
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