Development and validation of a prediction model for gastric cancer: a single-center prospective study.

Abstract

Objective: This study aimed to develop and validate a novel nomogram for diagnosing gastric cancer (GC).

Methods: In this prospective analysis, 146 patients of Wenzhou Central Hospital were recruited for a GC group and a benign lesion group and were divided into a training set and an internal validation set in a ratio of 7:3. Clinical and analytical characteristics were collected and analyzed by logistic regression analysis. The performance of the predictive model was evaluated using the receiver operating characteristic curve, calibration curve, and decision curve analysis.

Results: There were 5 variables, namely albumin, carcinoembryonic antigen, carbohydrate antigen 125, creatinine, and small proline-rich protein 2A, that were identified as the final parameters for the developed model. In the training and internal validation sets, the area under the curve of the model was 0.968 and 0.979, respectively, showing good diagnostic performance.

Conclusion: This study developed and validated a new nomogram based on 5 parameters. This model shows good diagnostic performance in distinguishing GC from benign lesion groups and has certain significance in clinical application.