Development and validation of multivariate models integrating preoperative clinicopathological and radiographic findings to predict HER2 status in gastric cancer

Abstract

Abstract The combination of trastuzumab and chemotherapy is recommended as first-line therapy for patients with human epidermal growth factor receptor 2 (HER2) positive advanced gastric cancers (GCs). Successful trastuzumab-induced targeted therapy should be based on the assessment of HER2 overexpression. This study aimed to evaluate the feasibility of multivariate models based on hematological parameters, endoscopic biopsy, and computed tomography (CT) findings for assessing HER2 overexpression in GC. This retrospective study included 183 patients with GC, and they were divided into primary (n = 137) and validation (n = 46) cohorts at a ratio of 3:1. Hematological parameters, endoscopic biopsy, CT morphological characteristics, and CT value-related and texture parameters of all patients were collected and analyzed. The mean corpuscular hemoglobin concentration value, morphological type, 3 CT value-related parameters, and 22 texture parameters in three contrast-enhanced phases differed significantly between the two groups (all p < 0.05). Multivariate models based on the regression analysis and support vector machine algorithm achieved areas under the curve of 0.818 and 0.879 in the primary cohort, respectively. The combination of hematological parameters, CT morphological characteristics, CT value-related and texture parameters could predict HER2 overexpression in GCs with satisfactory diagnostic efficiency. The decision curve analysis confirmed the clinical utility.