A Real-Time Online Nomogram Integrating Systemic Inflammatory Response Index and Lactate Dehydrogenase to Predict
Long Li1,2, Weiwen Cai1,2, Haobo Han1,2
1Department of General Surgery, The Second Hospital of Lanzhou University, Lanzhou, People's Republic of China.
Background:
Globally, gastric cancer is a significant health burden. Neoadjuvant chemoimmunotherapy (NACI) has emerged as a promising strategy for locally advanced gastric cancer, but responses vary substantially among patients. Predicting major pathological response (MPR) is crucial for treatment personalization.
Objective:
To develop and validate a web-based nomogram that integrates readily available clinical and serological markers to predict MPR in gastric cancer patients receiving NACI.
Methods:
This retrospective study analyzed 325 gastric cancer patients who underwent NACI and radical resection. A nomogram was constructed using R software and validated with metrics including receiver operating characteristic curve (ROC), area under curve (AUC), calibration curves, and decision curve analysis (DCA), compared to the use of a single biomarker.
Results:
The MPR was 53.5%. Multivariate analysis identified lower stomach location (odds ratio (OR) = 2.90; 95% confidence interval (CI): 1.35-6.22; P = 0.006), histological differentiation grade (OR = 3.43; 95% CI: 1.77-6.63; P < 0.001), systemic inflammatory response index (SIRI) (OR = 2.02; 95% CI: 1.02-3.97; P = 0.043) and lactate dehydrogenase (LDH) (OR = 1.02; 95% CI: 1.01-1.03; P < 0.001) as independent predictors of MPR. The nomogram demonstrated robust discriminative ability, with AUC values of 0.807 (95% CI: 0.751-0.863) and 0.799 (95% CI: 0.711-0.888) in the training and testing sets, respectively. Furthermore, DCA further confirmed its significant clinical utility.
Conclusion:
We developed and internally validated a nomogram that accurately predicts MPR after NACI. Implemented as a user-friendly web-based calculator, this model enables real-time, individualized estimation of MPR probability and may assist clinicians in tailoring treatment strategies for patients with gastric cancer. Further external and prospective validation is warranted.
