Radiomics signature for prediction of long-term survival and recurrence patterns in patients with gastric cancer after radical gastrectomy: A multicenter study Huang JM, Zhuang LP, Wang HG, Zhong LY, Xue SJ, Tian FX, Lin HY, - J Indian Prosthodont Soc

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ORIGINAL ARTICLE

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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 Correspondence Address: 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 China Source of Support: None, Conflict of Interest: None DOI: 10.4103/sjg.sjg_253_22

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.

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    -  Huang JM
    -  Zhuang LP
    -  Wang HG
    -  Zhong LY
    -  Xue SJ
    -  Tian FX
    -  Lin HY

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