Cancer management and research · 2026
A Real-Time Online Nomogram Integrating Systemic Inflammatory Response Index and Lactate Dehydrogenase to Predict Pathological Response in Gastric Cancer Patients Receiving Neoadjuvant Chemoimmunotherapy.
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Li Long, Cai Weiwen, Han Haobo, Chen Shigong, Long Bo, Zhang Gengyuan, Jiang Xiangyan, Zhou Huinian, Qin Long, Yu Zeyuan, Jiao Zuoyi
Аннотация
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.
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.