Antonio Piñero-Madrona1, Francisco Ripoll-Orts2, José Ignacio Sánchez-Méndez3, Asunción Chaves-Benito4, Maximiliano Rodrigo Gómez-de la Bárcena5, Ana Calatrava-Fons6, Salomón Menjón-Beltrán7, Vicente Peg-Cámara8. 1. Breast Cancer Unit, Department of Surgery, Virgen de La Arrixaca University Hospital, Ctra. Madrid-Cartagena, s/n, El Palmar, 30120, Murcia, Spain. pineromadrona@gmail.com. 2. Breast Cancer Unit, La Fe University and Polytechnic Hospital, Valencia, Spain. 3. Breast Unit, La Paz University Hospital, Madrid, Spain. 4. Pathology Department, J.M. Morales Meseguer Hospital, Murcia, Spain. 5. Pathology Department, Burgos University Hospital, Burgos, Spain. 6. Pathology Department, Fundation Institute of Oncology, Valencia, Spain. 7. Oncologic Gynaecology Unit, Virgen de Las Nieves Hospital, Granada, Spain. 8. Pathology Department, Vall D'Hebron University Hospital, Barcelona, Spain.
Abstract
BACKGROUND: A prognostic model based on the results of molecular analysis of sentinel lymph nodes (SLN) is needed to replace the information that staging the entire axilla provided. The aim of the study is to conduct an external validation of a previously developed model for the prediction of 5-year DFS in a group of breast cancer patients that had undergone SLN biopsy assessed by the One Step Nucleic Acid Amplification (OSNA) method. METHODS: We collected retrospective data of 889 patients with breast cancer, who had not received systemic treatment before surgery, and who underwent SLN biopsy and evaluation of all SLN by OSNA. The discrimination ability of the model was assessed by the area under the ROC curve (AUC ROC), and its calibration by comparing 5-years DFS Kaplan-Meier estimates in quartile groups of model predicted probabilities (MPP). RESULTS: The AUC ROC ranged from 0.78 (at 2 years) to 0.73 (at 5 years) in the training set, and from 0.78 to 0.71, respectively, in the validation set. The MPP allowed to distinguish four groups of patients with heterogeneous DFS (log-rank test p < 0.0001). In the highest risk group, the HR were 6.04 [95% CI 2.70, 13.48] in the training set and 4.79 [2.310, 9.93] in the validation set. CONCLUSIONS: The model for the prediction of 5-year DFS was successfully validated using the most stringent form of validation, in centers different from those involved in the development of the model. The external validation of the model confirms its utility for the prediction of 5-year DFS and the usefulness of the TTL value as a prognostic variable.
BACKGROUND: A prognostic model based on the results of molecular analysis of sentinel lymph nodes (SLN) is needed to replace the information that staging the entire axilla provided. The aim of the study is to conduct an external validation of a previously developed model for the prediction of 5-year DFS in a group of breast cancerpatients that had undergone SLN biopsy assessed by the One Step Nucleic Acid Amplification (OSNA) method. METHODS: We collected retrospective data of 889 patients with breast cancer, who had not received systemic treatment before surgery, and who underwent SLN biopsy and evaluation of all SLN by OSNA. The discrimination ability of the model was assessed by the area under the ROC curve (AUC ROC), and its calibration by comparing 5-years DFS Kaplan-Meier estimates in quartile groups of model predicted probabilities (MPP). RESULTS: The AUC ROC ranged from 0.78 (at 2 years) to 0.73 (at 5 years) in the training set, and from 0.78 to 0.71, respectively, in the validation set. The MPP allowed to distinguish four groups of patients with heterogeneous DFS (log-rank test p < 0.0001). In the highest risk group, the HR were 6.04 [95% CI 2.70, 13.48] in the training set and 4.79 [2.310, 9.93] in the validation set. CONCLUSIONS: The model for the prediction of 5-year DFS was successfully validated using the most stringent form of validation, in centers different from those involved in the development of the model. The external validation of the model confirms its utility for the prediction of 5-year DFS and the usefulness of the TTL value as a prognostic variable.
Entities:
Keywords:
Breast cancer; Model validation; Prognosis; Sentinel lymph node; Total tumor load
Authors: B Vieites; M Á López-García; M D Martín-Salvago; C L Ramirez-Tortosa; R Rezola; M Sancho; L López-Vilaró; F Villardell; O Burgués; B Fernández-Rodriguez; L Alfaro; V Peg Journal: Clin Transl Oncol Date: 2021-01-31 Impact factor: 3.405