Validation of the postoperative prognostication tool PREDICT version 2.2 and 3.0 using data from the National cancer center hospital in Japan

Despite these differences, both versions demonstrated satisfactory performance, suggesting that they can be generalized for Japanese patients with postoperative breast cancer. Notably, v3.0, given its improved calibration, might be more suitable for supporting shared decision making. The model's performance in predicting 5-year OS supports its generalizability, whereas 10-year projections warrant caution due to limited follow-up. Overall, this study demonstrates that PREDICT is a valuable prognostic tool for Japanese patients with breast cancer.

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Publication Details

Journal
Breast Cancer
Published
2026-01-19
DOI
https://doi.org/10.1007/s12282-026-01823-w
Primary Topic
Breast Cancer Treatment Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Validation of the postoperative prognostication tool PREDICT version 2.2 and 3.0 using data from the National cancer center hospital in Japan

Yi-Wen Hsiao, Hiromi Hashiguchi, Sho Shiino, Naoto Takehara et al.
Breast Cancer
Breast Cancer Treatment Studies
article

Validation of the postoperative prognostication tool PREDICT version 2.2 and 3.0 using data from the National cancer center hospital in Japan

Yi-Wen Hsiao, Hiromi Hashiguchi, Sho Shiino, Naoto Takehara, Shin Takayama, Paul D. P. Pharoah, Katsuji Takeda, T. Murata, Ryuji Hamamoto, Nobuji Kouno, Satoshi Takahashi, Kazutaka Obama
article en

Abstract

Despite these differences, both versions demonstrated satisfactory performance, suggesting that they can be generalized for Japanese patients with postoperative breast cancer. Notably, v3.0, given its improved calibration, might be more suitable for supporting shared decision making. The model's performance in predicting 5-year OS supports its generalizability, whereas 10-year projections warrant caution due to limited follow-up. Overall, this study demonstrates that PREDICT is a valuable prognostic tool for Japanese patients with breast cancer.

Breast CancerVol. 33(2)
Cedars-Sinai Medical Center (US), Kyoto University (JP), RIKEN Center for Advanced Intelligence Project (JP), Shinmatsudo Central General Hospital (JP), Tokyo National Hospital (JP), National Cancer Research Institute (GB)
Ministry of Education, Culture, Sports, Science and Technology
Reduced inequalities
Openalex Percentile: Top 85%
Breast Cancer Treatment Studies
DOIOpen Access PDFOpenAlex
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Validation of the postoperative prognostication tool PREDICT version 2.2 and 3.0 using data from the National cancer center hospital in Japan — Yi-Wen Hsiao, Hiromi Hashiguchi, et al. · Breast Cancer (2026) | TGRS Research Map | TGRS