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A prediction model for early systemic recurrence in breast cancer using a molecular diagnostic analysis of sentinel lymph nodes: A large‐scale, multicenter cohort study
BACKGROUND: The one‐step nucleic acid amplification (OSNA) assay can quantify the cytokeratin 19 messenger RNA copy number as a proxy for sentinel lymph node (SN) metastasis in breast cancer. A large‐scale, multicenter cohort study was performed to determine the prognostic value of the SN tumor burd...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9311203/ https://www.ncbi.nlm.nih.gov/pubmed/35226357 http://dx.doi.org/10.1002/cncr.34144 |
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author | Osako, Tomo Matsuura, Masaaki Yotsumoto, Daisuke Takayama, Shin Kaneko, Koji Takahashi, Mina Shimazu, Kenzo Yoshidome, Katsuhide Kuraoka, Kazuya Itakura, Masayuki Tani, Mayumi Ishikawa, Takashi Ohi, Yasuyo Kinoshita, Takayuki Sato, Nobuaki Tsujimoto, Masahiko Nakamura, Seigo Tsuda, Hitoshi Noguchi, Shinzaburo Akiyama, Futoshi |
author_facet | Osako, Tomo Matsuura, Masaaki Yotsumoto, Daisuke Takayama, Shin Kaneko, Koji Takahashi, Mina Shimazu, Kenzo Yoshidome, Katsuhide Kuraoka, Kazuya Itakura, Masayuki Tani, Mayumi Ishikawa, Takashi Ohi, Yasuyo Kinoshita, Takayuki Sato, Nobuaki Tsujimoto, Masahiko Nakamura, Seigo Tsuda, Hitoshi Noguchi, Shinzaburo Akiyama, Futoshi |
author_sort | Osako, Tomo |
collection | PubMed |
description | BACKGROUND: The one‐step nucleic acid amplification (OSNA) assay can quantify the cytokeratin 19 messenger RNA copy number as a proxy for sentinel lymph node (SN) metastasis in breast cancer. A large‐scale, multicenter cohort study was performed to determine the prognostic value of the SN tumor burden based on a molecular readout and to establish a model for the prediction of early systemic recurrence in patients using the OSNA assay. METHODS: SN biopsies from 4757 patients with breast cancer were analyzed with the OSNA assay. The patients were randomly assigned to the training or validation cohort at a ratio of 2:1. On the basis of the training cohort, the threshold SN tumor burden value for stratifying distant recurrence was determined with Youden's index; predictors of distant recurrence were investigated via multivariable analyses. Based on the selected predictors, a model for estimating 5‐year distant recurrence–free survival was constructed, and predictive performance was measured with the validation cohort. RESULTS: The prognostic cutoff value for the SN tumor burden was 1100 copies/μL. The following variables were significantly associated with distant recurrence and were used to construct the prediction model: SN tumor burden, age, pT classification, grade, progesterone receptor, adjuvant cytotoxic chemotherapy, and adjuvant anti–human epidermal growth factor receptor 2 therapy. The values for the area under the curve, sensitivity, specificity, and accuracy of the prediction model were 0.83, 63.4%, 81.7%, and 81.1%, respectively. CONCLUSIONS: Using the OSNA assay, the molecular readout–based SN tumor burden is an independent prognostic factor for early breast cancer. This model accurately predicts early systemic recurrence and may facilitate decision‐making related to treatment. |
format | Online Article Text |
id | pubmed-9311203 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93112032022-07-29 A prediction model for early systemic recurrence in breast cancer using a molecular diagnostic analysis of sentinel lymph nodes: A large‐scale, multicenter cohort study Osako, Tomo Matsuura, Masaaki Yotsumoto, Daisuke Takayama, Shin Kaneko, Koji Takahashi, Mina Shimazu, Kenzo Yoshidome, Katsuhide Kuraoka, Kazuya Itakura, Masayuki Tani, Mayumi Ishikawa, Takashi Ohi, Yasuyo Kinoshita, Takayuki Sato, Nobuaki Tsujimoto, Masahiko Nakamura, Seigo Tsuda, Hitoshi Noguchi, Shinzaburo Akiyama, Futoshi Cancer Original Articles BACKGROUND: The one‐step nucleic acid amplification (OSNA) assay can quantify the cytokeratin 19 messenger RNA copy number as a proxy for sentinel lymph node (SN) metastasis in breast cancer. A large‐scale, multicenter cohort study was performed to determine the prognostic value of the SN tumor burden based on a molecular readout and to establish a model for the prediction of early systemic recurrence in patients using the OSNA assay. METHODS: SN biopsies from 4757 patients with breast cancer were analyzed with the OSNA assay. The patients were randomly assigned to the training or validation cohort at a ratio of 2:1. On the basis of the training cohort, the threshold SN tumor burden value for stratifying distant recurrence was determined with Youden's index; predictors of distant recurrence were investigated via multivariable analyses. Based on the selected predictors, a model for estimating 5‐year distant recurrence–free survival was constructed, and predictive performance was measured with the validation cohort. RESULTS: The prognostic cutoff value for the SN tumor burden was 1100 copies/μL. The following variables were significantly associated with distant recurrence and were used to construct the prediction model: SN tumor burden, age, pT classification, grade, progesterone receptor, adjuvant cytotoxic chemotherapy, and adjuvant anti–human epidermal growth factor receptor 2 therapy. The values for the area under the curve, sensitivity, specificity, and accuracy of the prediction model were 0.83, 63.4%, 81.7%, and 81.1%, respectively. CONCLUSIONS: Using the OSNA assay, the molecular readout–based SN tumor burden is an independent prognostic factor for early breast cancer. This model accurately predicts early systemic recurrence and may facilitate decision‐making related to treatment. John Wiley and Sons Inc. 2022-02-28 2022-05-15 /pmc/articles/PMC9311203/ /pubmed/35226357 http://dx.doi.org/10.1002/cncr.34144 Text en © 2022 The Authors. Cancer published by Wiley Periodicals LLC on behalf of American Cancer Society https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Original Articles Osako, Tomo Matsuura, Masaaki Yotsumoto, Daisuke Takayama, Shin Kaneko, Koji Takahashi, Mina Shimazu, Kenzo Yoshidome, Katsuhide Kuraoka, Kazuya Itakura, Masayuki Tani, Mayumi Ishikawa, Takashi Ohi, Yasuyo Kinoshita, Takayuki Sato, Nobuaki Tsujimoto, Masahiko Nakamura, Seigo Tsuda, Hitoshi Noguchi, Shinzaburo Akiyama, Futoshi A prediction model for early systemic recurrence in breast cancer using a molecular diagnostic analysis of sentinel lymph nodes: A large‐scale, multicenter cohort study |
title | A prediction model for early systemic recurrence in breast cancer using a molecular diagnostic analysis of sentinel lymph nodes: A large‐scale, multicenter cohort study |
title_full | A prediction model for early systemic recurrence in breast cancer using a molecular diagnostic analysis of sentinel lymph nodes: A large‐scale, multicenter cohort study |
title_fullStr | A prediction model for early systemic recurrence in breast cancer using a molecular diagnostic analysis of sentinel lymph nodes: A large‐scale, multicenter cohort study |
title_full_unstemmed | A prediction model for early systemic recurrence in breast cancer using a molecular diagnostic analysis of sentinel lymph nodes: A large‐scale, multicenter cohort study |
title_short | A prediction model for early systemic recurrence in breast cancer using a molecular diagnostic analysis of sentinel lymph nodes: A large‐scale, multicenter cohort study |
title_sort | prediction model for early systemic recurrence in breast cancer using a molecular diagnostic analysis of sentinel lymph nodes: a large‐scale, multicenter cohort study |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9311203/ https://www.ncbi.nlm.nih.gov/pubmed/35226357 http://dx.doi.org/10.1002/cncr.34144 |
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