Predicting the extent of nodal involvement for node positive breast cancer patients: Development and validation of a novel tool.
area under curve
breast neoplasms
nomograms
sentinel lymph node
Journal
Journal of surgical oncology
ISSN: 1096-9098
Titre abrégé: J Surg Oncol
Pays: United States
ID NLM: 0222643
Informations de publication
Date de publication:
Sep 2019
Sep 2019
Historique:
received:
05
02
2019
accepted:
10
07
2019
pubmed:
25
7
2019
medline:
7
9
2019
entrez:
25
7
2019
Statut:
ppublish
Résumé
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. 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. 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. 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.
Sections du résumé
BACKGROUND
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
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
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
CONCLUSIONS
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.
Identifiants
pubmed: 31338839
doi: 10.1002/jso.25644
pmc: PMC6771524
doi:
Types de publication
Journal Article
Validation Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
578-586Subventions
Organisme : Netherlands Organization for Scientific Research
ID : 917.11.383
Informations de copyright
© 2019 The Authors. Journal of Surgical Oncology Published by Wiley Periodicals, Inc.
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