Preoperative Maximum Standardized Uptake Value Emphasized in Explainable Machine Learning Model for Predicting the Risk of Recurrence in Resected Non–Small Cell Lung Cancer
Preoperative SUV<sub>max</sub> showed significant predictive value for postoperative recurrence after NSCLC resection. The nonlinear relationship between SUV<sub>max</sub> and recurrence risk, with a sharp increase at relatively low SUV<sub>max</sub> values, suggests its potential as a sensitive biomarker for early identification of high-risk patients. This may contribute to more precise assessments of the risk of recurrence and personalized treatment strategies for NSCLC.
Authors
- Kyoichi Okishio (ORCID: https://orcid.org/0000-0002-6348-1302)
- Kensuke Kojima (ORCID: https://orcid.org/0000-0001-8136-4970)
- Hyungeun Yoon
- Daiki Hayashi
- Takafumi Iguchi (ORCID: https://orcid.org/0000-0002-2067-223X)
- Toshiteru Tokunaga
Institutions
- NHO Kinki Chuo Chest Medical Center (JP)
Publication Details
- Journal
- JCO Clinical Cancer Informatics
- Published
- 2025-03-01
- DOI
- https://doi.org/10.1200/cci-24-00194
- Citations
- 3
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 4.56