Validation and update of a lymph node metastasis prediction model for breast cancer

Autor: Pieter Ott, Susanne H. Estourgie, Arkajyoti Bhattacharya, Huan Cheng Zeng, Hendrik Koffijberg, Jeroen Veltman, Si-Qi Qiu, Caroline A H Klazen, Sabine Siesling, Monique D. Dorrius, Marissa C. van Maaren, Merel Aarnink, W. Kelder, Gooitzen M. van Dam, Guo-Jun Zhang, Jan H. Korte
Přispěvatelé: Health Technology & Services Research, Guided Treatment in Optimal Selected Cancer Patients (GUTS), Microbes in Health and Disease (MHD), ​Basic and Translational Research and Imaging Methodology Development in Groningen (BRIDGE)
Rok vydání: 2018
Předmět:
Axillary surgery omission
ARM LYMPHEDEMA
Receptor
ErbB-2
Lymph node metastasis
HER2 STATUS
030218 nuclear medicine & medical imaging
Metastasis
PROGNOSTIC-FACTORS
Breast cancer
0302 clinical medicine
Lymph node
Mastectomy
Netherlands
Ultrasonography
HISTOLOGICAL GRADE
education.field_of_study
General Medicine
Middle Aged
Sentinel node
Tumor Burden
medicine.anatomical_structure
Receptors
Estrogen
Oncology
Area Under Curve
Lymphatic Metastasis
030220 oncology & carcinogenesis
Female
Radiology
Receptors
Progesterone
SENTINEL-NODE
Adult
Generalized linear model
China
medicine.medical_specialty
Population
Breast Neoplasms
Decision Support Techniques
03 medical and health sciences
Prediction model
medicine
Humans
education
PROGESTERONE-RECEPTOR
Aged
Neoplasm Staging
Receiver operating characteristic
Sentinel Lymph Node Biopsy
business.industry
Carcinoma
Reproducibility of Results
medicine.disease
Axillary lymph node metastasis
ESTROGEN-RECEPTOR
AXILLARY DISSECTION
CORE NEEDLE-BIOPSY
Axilla
Linear Models
Lymph Node Excision
Surgery
Lymph Nodes
Neoplasm Grading
FOLLOW-UP
business
Model
Zdroj: European journal of surgical oncology, 44(5), 700-707. Elsevier
EJSO, 44(5), 700-707. ELSEVIER SCI LTD
ISSN: 0748-7983
DOI: 10.1016/j.ejso.2017.12.008
Popis: Purpose: This study aimed to validate and update a model for predicting the risk of axillary lymph node (ALN) metastasis for assisting clinical decision-making.Methods: We included breast cancer patients diagnosed at six Dutch hospitals between 2011 and 2015 to validate the original model which includes six variables: clinical tumor size, tumor grade, estrogen receptor status, lymph node longest axis, cortical thickness and hilum status as detected by ultrasonography. Subsequently, we updated the original model using generalized linear model (GLM) tree analysis and by adjusting its intercept and slope. The area under the receiver operator characteristic curve (AUC) and calibration curve were used to assess the original and updated models. Clinical usefulness of the model was evaluated by false-negative rates (FNRs) at different cut-off points for the predictive probability.Results: Data from 1416 patients were analyzed. The AUC for the original model was 0.774. Patients were classified into four risk groups by GLM analysis, for which four updated models were created. The AUC for the updated models was 0.812. The calibration curves showed that the updated model predictions were better in agreement with actual observations than the original model predictions. FNRs of the updated models were lower than the preset 10% at all cut-off points when the predictive probability was less than 12.0%. ER Conclusions: The original model showed good performance in the Dutch validation population. The updated models resulted in more accurate ALN metastasis prediction and could be useful preoperative tools in selecting low-risk patients for omission of axillary surgery. (C) 2018 Elsevier Ltd, BASO - The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.
Databáze: OpenAIRE
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