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Background <p>PREDICT is a prognostic tool developed in the United Kingdom to estimate postoperative overall survival (OS) and the additional benefits of adjuvant therapies in patients with breast cancer. It has been validated in various international cohorts and continuously updated with the inclusion of new variables and model retraining. However, their efficacy in the Japanese population remains unclear. We aimed to evaluate the generalizability of PREDICT versions 2.2 (v2.2) and 3.0 (v3.0) using data from the National Cancer Center Hospital in Japan, a high-volume cancer center.</p> Methods <p>We analyzed a retrospective cohort (2006–2016) including 2,980 cases of postoperative breast cancer. We calculated survival predictions using both v2.2 and v3.0, and compared them with the Kaplan–Meier-estimated survival probabilities using a calibration plot. Additionally, we performed a time-dependent receiver operating characteristic (ROC) curve analysis for v2.2 and v3.0.</p> Results <p>Both models tended to underestimate survival in our cohort, whereas v3.0 showed improved calibration compared to v2.2, for 5- and 10-year OS. Both v2.2 and v3.0 maintained good discriminative performance throughout 10 years, with values under the ROC curve generally above 0.80.</p> Conclusions <p>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.</p>

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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

  • 期刊论文

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  • 发表日期：

    2026年1月19日

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

摘要

Background

PREDICT is a prognostic tool developed in the United Kingdom to estimate postoperative overall survival (OS) and the additional benefits of adjuvant therapies in patients with breast cancer. It has been validated in various international cohorts and continuously updated with the inclusion of new variables and model retraining. However, their efficacy in the Japanese population remains unclear. We aimed to evaluate the generalizability of PREDICT versions 2.2 (v2.2) and 3.0 (v3.0) using data from the National Cancer Center Hospital in Japan, a high-volume cancer center.

Methods

We analyzed a retrospective cohort (2006–2016) including 2,980 cases of postoperative breast cancer. We calculated survival predictions using both v2.2 and v3.0, and compared them with the Kaplan–Meier-estimated survival probabilities using a calibration plot. Additionally, we performed a time-dependent receiver operating characteristic (ROC) curve analysis for v2.2 and v3.0.

Results

Both models tended to underestimate survival in our cohort, whereas v3.0 showed improved calibration compared to v2.2, for 5- and 10-year OS. Both v2.2 and v3.0 maintained good discriminative performance throughout 10 years, with values under the ROC curve generally above 0.80.

Conclusions

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.