Indications of neoadjuvant chemotherapy for locally advanced Gastric Cancer patients based on pre-treatment clinicalpathological and laboratory parameters

Objective: There are controversial indications for neoadjuvant chemotherapy (NAT) in the treatment of locally advanced gastric cancer (LAGC). Here, we aimed to identify indications for NAT based on pre-treatment clinicopathological and laboratory parameters. Methods: This study included a retrospective cohort of 1083 LAGC patients who had underwent radical D2 gastrectomy in the Cancer Hospital of China Medical University between 2012 and 2016. After propensity score matching, 756 patients were recruited and were separated into NAT (n=378) or primary surgery (PS) (n=378) groups. Cox regression identified pre-treatment risk factors for overall survival (OS). A nomogram was established to predict OS and calculate scores for risk factors. Recursive partitioning analysis (RPA) determined cut off values, where the entire patient cohort was divided into low and high risk groups. Results: Seven risk factors that were significantly related to OS were incorporated in the nomogram. These risk factors included age, tumor size, tumor site, carbohydrate antigen 199 (CA199), carcino-embryonic antigen (CEA), clinical T stage (cT) and clinical N stage (cN). The model contained a C-index of 0.637. The calibration curve revealed anticipated values that were reflective of actual values. The decision curve revealed an achievement of optimal clinical impact when threshold possibility was 0-54%. Next, the cohort was split into low (≤ 252 points) or high (> 252 points) risk groups based on the 5-year OS projected by RPA. The PS group showed a worse OS compared to the NAT group for high-risk patients (P =0.004). There was no significant difference when comparing OS between the PS and NAT groups for low-risk patients (P =0.407). Conclusions: A feasible, quantifiable and practical prognostic tool was generated to screen for potential survival benefits for patients receiving NAT. Surgeons can use this model to identify optimal treatment regimens for individualized treatment strategies during the diagnosis of LAGC patients. For these patients, NAT is suggested for high-risk patients.