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To achieve precise individualized immunotherapy, this review systematically summarizes the multidimensional biomarker profiles that can predict the efficacy, resistance, and safety of immunotherapy. Beyond the single PD\u2010L1 expression, the efficacy prediction system has expanded to integrate multimodal information such as dynamic tumor microenvironment, tumor genomic characteristics, systemic inflammation\/immune status, and radiomics. At the same time, studies have revealed that immune\u2010suppressive microenvironments and specific genetic variations are key mechanisms mediating treatment resistance. Moreover, clinical characteristics, blood markers, and imaging findings provide a basis for predicting the risk of irAEs. Looking to the future, the core to overcoming current bottlenecks lies in constructing dynamic and integrated prediction models. By integrating multiomics data, longitudinal liquid biopsies, and artificial intelligence algorithms, an intelligent decision\u2010making system is expected to be developed to achieve real\u2010time monitoring of treatment response, early identification of resistance mechanisms, and proactive management of toxicity risks, ultimately optimizing the clinical practice of NSCLC immunotherapy and advancing it towards higher\u2010order precision medicine.<\/jats:p>","DOI":"10.1111\/1759-7714.70342","type":"journal-article","created":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T05:45:17Z","timestamp":1790228717000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Guiding the Application of Immunotherapy in Nonsmall Cell Lung Cancer: The Role of 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