Development of a dynamic prediction model with the inclusion of time-dependent inflammatory biomarker enhances recurrence prediction after curative surgery for stage II or III gastric cancer
Prediction models incorporating postoperative information could serve as a decision-making tool in clinical practice to more precisely distinguish between patients with high and low risk of recurrence.
Authors
- Yasuhiro Okumura (ORCID: https://orcid.org/0000-0001-6452-0724)
- Koji Oba (ORCID: https://orcid.org/0000-0001-5468-8988)
- Yasuyuki Seto (ORCID: https://orcid.org/0000-0002-6953-8752)
- Takeo Fukagawa (ORCID: https://orcid.org/0000-0002-9425-3767)
- Hideaki Shimada
- Koichi Yagi (ORCID: https://orcid.org/0000-0001-8319-8005)
- Yoko Oshima
- Yutaka Matsuyama (ORCID: https://orcid.org/0000-0003-2009-6831)
- Akihiro Kuroda
- Larbi Aluariachy
Institutions
- Toho University (JP)
- National Cancer Center (US)
- Toho University Omori Medical Center (JP)
- The University of Tokyo (JP)
- International University of Health and Welfare (JP)
- Teikyo University (JP)
Publication Details
- Journal
- Japanese Journal of Clinical Oncology
- Published
- 2025-05-23
- DOI
- https://doi.org/10.1093/jjco/hyaf075
- Primary Topic
- Gastric Cancer Management and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Japan Agency for Medical Research and Development
- Japan Society for the Promotion of Science