Development and validation of a preoperative radiomics-based nomogram to identify patients who can benefit from splenic hilar lymphadenectomy: a pooled analysis of three prospective trials

Author:

Xu Bin-bin1234,Zheng Hua-Long1234,Chen Chun-sen5,Xu Liang-liang6,Xue Zhen1234,Wei Ling-hua1234,Zheng Hong-hong1234,Shen Li-li1234,Zheng Chao-Hui1234,Li Ping1234,Xie Jian-Wei1234,Lin Jian-xian1234,Zheng Yu-hui7,Huang Chang-Ming1234

Affiliation:

1. Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou, China

2. Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China

3. Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China

4. Fujian Province Minimally Invasive Medical Center, Fuzhou, China

5. Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China

6. Department of Radiology, Fuzhou Pulmonary Hospital of Fujian, Educational Hospital of Fujian Medical University, Fuzhou, China

7. Department of Pathology, Fujian Medical University Union Hospital, Fuzhou, China

Abstract

Background: We aimed to use preoperative computed tomography images to develop a radiomic nomogram to select patients who would benefit from spleen-preserving splenic hilar (No.10) lymphadenectomy (SPSHL). Methods: A pooled analysis of three distinct prospective studies was performed. The splenic hilar lymph node (SHLN) ratio (sLNR) was established as the quotient of the number of metastatic SHLN to the total number of SHLN. Radiomic features reflecting the phenotypes of the primary tumor (RS1) and SHLN region (RS2) were extracted and used as predictive factors for sLNR. Results: This study included 733 patients: 301 in the D2 group and 432 in the D2+No.10 group. The optimal sLNR cutoff value was set at 0.4, and the D2+No.10 group was divided into three groups: sLNR=0, sLNR≤0.4, and sLNR>0.4. Patients in the D2+No. 10 group were randomly divided into the training (n=302) and validation (n=130) cohorts. The AUCs value of the nomogram, including RS1 and RS2, were 0.952 in the training cohort and 0.888 in the validation cohort. The entire cohort was divided into three groups based on the nomogram scores: low, moderate and high SHLN metastasis burden groups (LMB, MMB and HMB, respectively). A similar 5-year OS rate was found between the D2 and D2+No. 10 groups in the LMB and HMB groups. In the MMB group, the 5-year OS of the D2+No. 10 group (73.4%) was significantly higher than that of the D2 group (37.6%) (P<0.001). Conclusions: The nomogram showed good predictive ability for distinguishing patients with various SHLN metastasis burdens. It can accurately identify patients who would benefit from SPSHL.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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