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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
Author(s) -
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
Publication year - 2022
Publication title -
cancer
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.052
H-Index - 304
eISSN - 1097-0142
pISSN - 0008-543X
DOI - 10.1002/cncr.34144
Subject(s) - medicine , oncology , breast cancer , cohort , youden's j statistic , sentinel node , adjuvant therapy , receiver operating characteristic , sentinel lymph node , cohort study , metastasis , lymph node , stage (stratigraphy) , cancer , paleontology , biology
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.