Clinical and Body Composition Parameters as Predictors of Response to Chemotherapy plus PD-1 Inhibitor in Gastric Cancer

Jun Zhang^1*Chenfei Zhou¹Yan Sun²Tao Liu³David P. J. van Dijk²Wenqi Xi¹Jinling Jiang¹Liting Guo¹Feng Qi¹Xuekun Zhang¹Mengfan Jia³Jun Ji¹Zhenggang Zhu¹Sander Rensen²Steven Olde Damink²

• ¹Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
• ²Universiteit Maastricht School of Nutrition and Translational Research in Metabolism, Maastricht, Netherlands
• ³The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China

Background Predicting treatment efficacy of programmed cell death protein 1 (PD-1) inhibitors is crucial for guiding optimal treatment plans and prevents unnecessary complications for cancer patients. We aimed to develop a prediction model using clinical and body composition parameters to identify gastric cancer (GC) patients who would respond to chemotherapy plus PD-1 antibody. Methods Clinical data of GC patients treated with chemotherapy plus PD-1 antibody (immunotherapy cohort, n=120) or chemotherapy alone (chemotherapy cohort, n=82) following surgical resection was reviewed as the training set. Patients treated with chemotherapy plus PD-1 antibody at an external center were collected as the validation set (n=43). Tumor regression grade (TRG) was recorded and was classified as TRG0/1 or TRG2/3 during analysis. Body composition parameters were assessed on computed tomography images at the third lumbar vertebral level using SliceOmatic software. Univariate and multivariate analyses were performed to identify parameters associated with TRG0/1, then a logistic regression model was developed to stratify patients into good and poor response groups. Results In the training set, clinical and body composition parameters between the immunotherapy cohort and chemotherapy cohort were similar. Skeletal muscle radiation attenuation (SMRA), neutrophil to lymphocyte ratio (NLR), and weight loss ≥5% were associated with TRG0/1 in the immunotherapy cohort. Subcutaneous adipose tissue index (SATI) and metastasis were identified in the chemotherapy cohort. A logistic regression model was developed to stratified immunotherapy cohort patients into two response groups with an area under receiver operating characteristics curve (AUC) value at 0.728. In the immunotherapy cohort, patients stratified as good response showed higher TRG0/1 rate (37/55, 67.3%) than poor response patients (18/65, 27.7%, P<0.001), and had better overall survival (P=0.001). In the external validation set, patients stratified by the clinical model as good response also showed higher TRG0/1 rate (14/18, 77.8%) than poor response patients (9/25, 36.0%, P=0.012). Conclusion The prediction model consisting of SMRA, NLR and weight loss could help identify GC patients who respond well to chemotherapy plus PD-1 antibody.