Dynamic circulating biomarkers for predicting adverse events in PRaG therapy: a pooled analysis and model construction from PRaG series clinical trials

This study successfully delineated the real-world safety profile of PRaG therapy and identified a distinct set of dynamic circulating biomarkers strongly associated with moderate-to-severe AEs. The established non-invasive prediction model offers an effective tool for clinical early warning and proactive management in PRaG patients.

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Publication Details

Journal
Cancer Immunology Immunotherapy
Published
2026-01-27
DOI
https://doi.org/10.1007/s00262-025-04292-w
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Dynamic circulating biomarkers for predicting adverse events in PRaG therapy: a pooled analysis and model construction from PRaG series clinical trials

Wei-wu Chen, Xiang-rong Zhao, Mei-ling Xu, Yue-hong Kong et al.
Cancer Immunology Immunotherapy
Advanced Causal Inference Techniques
article

Dynamic circulating biomarkers for predicting adverse events in PRaG therapy: a pooled analysis and model construction from PRaG series clinical trials

Wei-wu Chen, Xiang-rong Zhao, Mei-ling Xu, Yue-hong Kong, Peng-fei Xing, Shi-cheng Li, Jun-jun Zhang, Li-yuan Zhang, Qian Yin
article en

Abstract

This study successfully delineated the real-world safety profile of PRaG therapy and identified a distinct set of dynamic circulating biomarkers strongly associated with moderate-to-severe AEs. The established non-invasive prediction model offers an effective tool for clinical early warning and proactive management in PRaG patients.

Cancer Immunology ImmunotherapyVol. 75(2)
Soochow University (CN), Second Affiliated Hospital of Soochow University (CN)
National Natural Science Foundation of China, Soochow University, State Key Laboratory of Radiation Medicine and Protection
Partnerships for the goals
Openalex Percentile: Top 79%
Advanced Causal Inference Techniques
DOIOpen Access PDFOpenAlex
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