ArticlePeerJ2026
Serum markers for prognostic value of EGFR-TKI in lung adenocarcinoma with bone metastases: a retrospective study.
Article in PeerJ, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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9 authors.
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Abstract
Background: Lung adenocarcinoma is a prevalent malignancy. Mutations in the epidermal growth factor receptor (EGFR) have introduced novel prospects for targeted therapies. However, the status of EGFR mutations alone may be insufficient to fully predict treatment outcomes. To this end, the present research was performed to evaluate the serum markers associated with epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) treatment in patients with lung adenocarcinoma and bone metastases, specifically focusing on the prognostic value of EGFR-TKI therapy. Methods: A retrospective analysis was conducted on 164 patients diagnosed with lung adenocarcinoma and bone metastases at Yunnan Cancer Hospital between January 2019 and December 2020. Clinical and follow-up data were collected, and a Cox regression model was employed to evaluate the combined predictive value of serum markers for survival outcomes. Results: The findings revealed that variables identified through Cox regression analysis included age, the neutrophil-to-lymphocyte ratio (NLR), carcinoembryonic antigen (CEA), and Cytokeratin 19 fragment (Cyfra21-1), all exhibiting significance levels of Conclusion: This research successfully developed a nomogram based on the Cox regression model to predict prognosis and treatment outcomes in patients with lung adenocarcinoma and bone metastases undergoing EGFR-TKI therapy. This facilitates the avoidance of poor treatment outcomes by enabling individualized therapeutic approaches, thereby simplifying the development of the most appropriate treatment plans and ultimately improving patient prognosis.
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