Development and validation of a relatively accurate gastric cancer high-risk group screening scoring system in urban residents.

Abstract

Our study aimed to develop a relatively accurate gastric cancer (GC) screening score system for urban residents and to validate the screening efficacy. The present study included a derivation cohort (n = 3406) and a validation cohort (n = 868) of urban residents. Applying the full-stack engineering intelligent system platform of Hualian Health Big Data of Shandong University, the clinical physical examination data of subjects were collected. Univariate and multivariate analyses were used to identify risk factors for GC, and subsequently, an optimal prediction rule was established to create three distinct scoring systems. In the GC-risk scoring system I, age, plateletocrit (PCT), carcinoembryonic antigen (CEA), glucose, albumin, creatinine were independent risk factors of GC, with scores ranging from 0 to 28 and optimal cut-off was 15.5. The second scoring system consisted of age, PCT, RDW-CV, CEA, glucose, albumin, and creatinine, with scores ranging from 0 to 31. The optimal cut-off point was determined to be 15.5. The scoring system III comprise of age, sex, PCT, RDW CV, CEA, glucose, with scores ranging from 0 to 21 and optimal cut-off was 10.5. All three scoring systems demonstrated excellent discrimination for GC, achieving an AUC of 0.884, 0.89, and 0.876, respectively. In external validation, the AUC values were 0.654, 0.658, and 0.714. Notably, the GC-risk scoring system III exhibited the highest screening efficiency. Urban residents benefited from the effective and verified GC-risk scoring systems, which demonstrated excellent performance in identifying individuals with an elevated risk of GC.