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Gene Regulation and Targeted Therapy in Gastric Cancer Peritoneal Metastasis: Radiological Findings from Dual Energy CT and PET/CT
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Nomogram based on CT imaging and clinical data to predict the efficacy of PD-1 inhibitors combined with chemotherapy

Yinchao Ma1,2, Zhipeng Wang1,2, Chenyang Qiu1

  • 1Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China.

Frontiers in Immunology
|April 15, 2025
PubMed
Summary

A new nomogram combining clinical and CT imaging features can predict treatment response in advanced gastric cancer patients receiving PD-1 inhibitors and chemotherapy. This tool aids in optimizing immunotherapy strategies for better patient outcomes.

Keywords:
chemo-immunotherapycomputed tomographygastric cancernomogramprogrammed cell death 1 inhibitors

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Area of Science:

  • Oncology
  • Medical Imaging
  • Immunotherapy

Background:

  • PD-1 inhibitors combined with chemotherapy are a first-line treatment for advanced metastatic gastric cancer.
  • Predictive markers are needed as not all patients benefit from this immunotherapy.

Purpose of the Study:

  • To develop a simple and reliable tool to predict immunotherapy efficacy in advanced gastric cancer.
  • To identify clinical and CT imaging features associated with treatment response.

Main Methods:

  • Retrospective analysis of clinical and CT imaging features from 272 gastric cancer patients (Center 1) and validation in 76 patients (Center 2).
  • Development of clinical, imaging, and combined nomogram models.
  • Evaluation using Area Under the Curve (AUC), accuracy, sensitivity, and specificity.

Main Results:

  • A nomogram integrating clinical and CT imaging features showed superior predictive performance.
  • The nomogram achieved an AUC of 0.904 in the training set and 0.801 in the validation set.
  • High accuracy (0.829) and sensitivity (0.889) were observed in predicting treatment response.

Conclusions:

  • A nomogram combining pre-treatment clinical and CT imaging features effectively predicts response to PD-1 inhibitor plus chemotherapy in advanced gastric cancer.
  • This predictive tool can assist in optimizing treatment strategies for individual patients.