LAUSR

Anastomotic leakage (AL) is the most serious postoperative complication for patients with gastric cancer. We aim to develop clinically tools to detect AL in the early phase by analysis of the inflammatory factors (IFs) in abdominal drainage. We prospectively included 326 patients to establish two independent cohorts, and the concentration of IFs within abdominal drainage was detected. In the primary cohort, an IF-based AL prediction model was constructed using the least absolute shrinkage and selection operator (LASSO) regression. The predictive value of the model was later validated via the validation cohort. Analyzing the IFs with LASSO regression, we developed an Anastomotic Score system on postoperative Day 3 (AScore-POD3), which yielded high diagnostic efficacy in the primary cohort (the area under the curve (AUC) = 0.87). The predictive value of AScore-POD3 was validated in the validation cohort, and its AUC was 0.83. We further built an AScore-POD3 based nomogram by combining the AScore-POD3 system with other clinical risk factors of AL. The C-index of the nomogram was 0.93 in the primary cohort and 0.82 in the validation cohort. Our study suggests that AL can be early diagnosed after gastric cancer surgery by measuring drainage IFs.