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Recursive Partitioning Analysis of Lymph Node Ratio in Breast Cancer Patients

Lymph node ratio (LNR) is a powerful prognostic factor for breast cancer. We conducted a recursive partitioning analysis (RPA) of the LNR to identify the prognostic risk groups in breast cancer patients. Records of newly diagnosed breast cancer patients between 2002 and 2006 were searched in the Tai...

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Autores principales: Chang, Yao-Jen, Chung, Kuo-Piao, Chen, Li-Ju, Chang, Yun-Jau
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4602854/
https://www.ncbi.nlm.nih.gov/pubmed/25569639
http://dx.doi.org/10.1097/MD.0000000000000208
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author Chang, Yao-Jen
Chung, Kuo-Piao
Chen, Li-Ju
Chang, Yun-Jau
author_facet Chang, Yao-Jen
Chung, Kuo-Piao
Chen, Li-Ju
Chang, Yun-Jau
author_sort Chang, Yao-Jen
collection PubMed
description Lymph node ratio (LNR) is a powerful prognostic factor for breast cancer. We conducted a recursive partitioning analysis (RPA) of the LNR to identify the prognostic risk groups in breast cancer patients. Records of newly diagnosed breast cancer patients between 2002 and 2006 were searched in the Taiwan Cancer Database. The end of follow-up was December 31, 2009. We excluded patients with distant metastases, inflammatory breast cancer, survival <1 month, no mastectomy, or missing lymph node status. Primary outcome was 5-year overall survival (OS). For univariate significant predictors, RPA were used to determine the risk groups. Among the 11,349 eligible patients, we identified 4 prognostic factors (including LNR) for survival, resulting in 8 terminal nodes. The LNR cutoffs were 0.038, 0.259, and 0.738, which divided LNR into 4 categories: very low (LNR ≤ 0.038), low (0.038 < LNR ≤ 0.259), moderate (0.259 < LNR ≤ 0.738), and high (0.738 < LNR). Then, 4 risk groups were determined as follows: Class 1 (very low risk, 8,265 patients), Class 2 (low risk, 1,901 patients), Class 3 (moderate risk, 274 patients), and Class 4 (high risk, 900 patients). The 5-year OS for Class 1, 2, 3, and 4 were 93.2%, 83.1%, 72.3%, and 56.9%, respectively (P< 0.001). The hazard ratio of death was 2.70, 4.52, and 8.59 (95% confidence interval 2.32–3.13, 3.49–5.86, and 7.48–9.88, respectively) times for Class 2, 3, and 4 compared with Class 1 (P < 0.001). In conclusion, we identified the optimal cutoff LNR values based on RPA and determined the related risk groups, which successfully predict 5-year OS in breast cancer patients.
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spelling pubmed-46028542015-10-27 Recursive Partitioning Analysis of Lymph Node Ratio in Breast Cancer Patients Chang, Yao-Jen Chung, Kuo-Piao Chen, Li-Ju Chang, Yun-Jau Medicine (Baltimore) 5700 Lymph node ratio (LNR) is a powerful prognostic factor for breast cancer. We conducted a recursive partitioning analysis (RPA) of the LNR to identify the prognostic risk groups in breast cancer patients. Records of newly diagnosed breast cancer patients between 2002 and 2006 were searched in the Taiwan Cancer Database. The end of follow-up was December 31, 2009. We excluded patients with distant metastases, inflammatory breast cancer, survival <1 month, no mastectomy, or missing lymph node status. Primary outcome was 5-year overall survival (OS). For univariate significant predictors, RPA were used to determine the risk groups. Among the 11,349 eligible patients, we identified 4 prognostic factors (including LNR) for survival, resulting in 8 terminal nodes. The LNR cutoffs were 0.038, 0.259, and 0.738, which divided LNR into 4 categories: very low (LNR ≤ 0.038), low (0.038 < LNR ≤ 0.259), moderate (0.259 < LNR ≤ 0.738), and high (0.738 < LNR). Then, 4 risk groups were determined as follows: Class 1 (very low risk, 8,265 patients), Class 2 (low risk, 1,901 patients), Class 3 (moderate risk, 274 patients), and Class 4 (high risk, 900 patients). The 5-year OS for Class 1, 2, 3, and 4 were 93.2%, 83.1%, 72.3%, and 56.9%, respectively (P< 0.001). The hazard ratio of death was 2.70, 4.52, and 8.59 (95% confidence interval 2.32–3.13, 3.49–5.86, and 7.48–9.88, respectively) times for Class 2, 3, and 4 compared with Class 1 (P < 0.001). In conclusion, we identified the optimal cutoff LNR values based on RPA and determined the related risk groups, which successfully predict 5-year OS in breast cancer patients. Wolters Kluwer Health 2015-01-09 /pmc/articles/PMC4602854/ /pubmed/25569639 http://dx.doi.org/10.1097/MD.0000000000000208 Text en Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved. http://creativecommons.org/licenses/by/4.0 This is an open access article distributed under the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0
spellingShingle 5700
Chang, Yao-Jen
Chung, Kuo-Piao
Chen, Li-Ju
Chang, Yun-Jau
Recursive Partitioning Analysis of Lymph Node Ratio in Breast Cancer Patients
title Recursive Partitioning Analysis of Lymph Node Ratio in Breast Cancer Patients
title_full Recursive Partitioning Analysis of Lymph Node Ratio in Breast Cancer Patients
title_fullStr Recursive Partitioning Analysis of Lymph Node Ratio in Breast Cancer Patients
title_full_unstemmed Recursive Partitioning Analysis of Lymph Node Ratio in Breast Cancer Patients
title_short Recursive Partitioning Analysis of Lymph Node Ratio in Breast Cancer Patients
title_sort recursive partitioning analysis of lymph node ratio in breast cancer patients
topic 5700
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4602854/
https://www.ncbi.nlm.nih.gov/pubmed/25569639
http://dx.doi.org/10.1097/MD.0000000000000208
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