Radiomics signature for prediction of long-term survival and recurrence patterns in patients with gastric cancer after radical gastrectomy: A multicenter study
Jing-Min Huang1, Lv-Ping Zhuang2, Hua-Gen Wang3, Li-Ying Zhong4, Sheng-Jin Xue5, Fang-Xi Tian6, Hua-Yang Lin7
1 The Graduate School of Qinghai University, Qinghai University; Department of General Surgery, Qinghai Provincial People's Hospital, Xining, China
2 Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, China
3 The Graduate School of Fujian Medical University, Fujian Medical University, Fuzhou, China
4 Department of Clinical Medicine, Xiamen Medical College, Xiamen, China
5 Department of Stomatology, Fujian Medical University Union Hospital, Fuzhou, China
6 Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China
7 Department of Anesthesiology, The Third Affiliated People's Hospital of Fujian University of Traditional Chinese Medicine, Fuzhou, China
Prof. Hua-Yang Lin
Department of Anesthesiology, The Third Affiliated People's Hospital of Fujian University of Traditional Chinese Medicine, No. 363 Guobin Avenue, Fuzhou 350100, Fujian Province
Source of Support: None, Conflict of Interest: None
Background: This study aimed to develop and validate a radiomics score to predict the long-term survival and patterns of recurrence of gastric cancer (GC).
Methods: A total of 513 patients who underwent radical gastrectomy for GC after curative resection between 2008 and 2016 at two institutions were analyzed. A radiomics score was generated using the least absolute shrinkage and selection operator Cox regression model on 327 patients and was validated in 186 patients. A nomogram consisting of the radiomics score and clinicopathological factors was created and compared with the tumor-lymph node-metastasis (TNM) staging system. Model performance was assessed using calibration, discrimination, and clinical usefulness.
Results: The radiomics score was established based on five selected features. A higher score was significantly associated with poorer recurrence-free survival (RFS) and overall survival (OS) rates, both in the training and validation cohorts (P < 0.05). Multivariate analysis demonstrated that the radiomics score was an independent prognostic factor for both RFS and OS (P < 0.05). A nomogram incorporating the radiomics score had a significantly better prognostic value than the TNM system alone. Moreover, a high score was significantly associated with an increased risk of distant recurrence, a medium score was significantly associated with an increased risk of peritoneal recurrence, and a low score was significantly associated with an increased risk of locoregional recurrence, in the entire cohort (P < 0.05).
Conclusions: The newly proposed radiomics score may be a powerful predictor of long-term outcomes and recurrence patterns of GC. Further studies are warranted to confirm these findings.