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DOI 10.2147/cmar.s559532

Медицинская библиотека · 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.

Li Long, Cai Weiwen, Han Haobo, Chen Shigong, Long Bo, Zhang Gengyuan, Jiang Xiangyan, Zhou Huinian, Qin Long, Yu Zeyuan, Jiao Zuoyi

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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.

Для цитирования: Li Long, Cai Weiwen, Han Haobo, Chen Shigong, Long Bo, Zhang Gengyuan, Jiang Xiangyan, Zhou Huinian, Qin Long, Yu Zeyuan, Jiao Zuoyi. A Real-Time Online Nomogram Integrating Systemic Inflammatory Response Index and Lactate Dehydrogenase to Predict Pathological Response in Gastric Cancer Patients Receiving Neoadjuvant Chemoimmunotherapy.. Cancer management and research. 2026. DOI: 10.2147/cmar.s559532.
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