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In recent years, immunotherapy has become one of the important treatments for malignant tumors. Among them, PD-1 inhibitors have been widely used in clinical practice, and have shown a significant survival benefits in many patients. However, the incidence of immune-related adverse reactions (irAEs) of PD-1 inhibitors is relatively high, and severe cases can even threaten patients's life. At present, irAEs have become a bottleneck and it is urgent to establish a prevention strategy for the prediction of irAEs. In this study, the investigators intends to use Sintilimab as the research drug. A prospective cohort study was carried out. Part of the sample which was used as a training set would be detected for producing a time-series multi-dimensional data such as differential genes, metabolites and immune factors. Then gene expression programming (GEP) was used to explore the irAEs recognition model. Then, based on this recognition model, internal verification ( part of samples from the center 1 ) and external verification ( part of samples from the center 2 and center 3 samples) are carried out to accurately predict the high-risk population of irAEs and realize the early-stage warning of Sintilimab induced- irAEs.
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100 participants in 3 patient groups
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Data sourced from clinicaltrials.gov
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