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Developing a predictive model and uncovering immune influences on prognosis for brain metastasis from lung carcinomas

  • 0Department of Gastroenterology, West China Hospital, Sichuan University, Chengdu, China.
Frontiers in Oncology +

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March 18, 2025

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March 18, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

Brain metastasis from lung cancer significantly reduces survival. A new nomogram model predicts survival and aids clinical decisions for lung cancer patients with brain metastasis.

Area Of Science

  • Oncology
  • Medical Statistics
  • Immunology

Background

  • Primary lung carcinomas (LCs) frequently metastasize to the brain, leading to poor patient outcomes.
  • Understanding survival and immune status in LCs with brain metastasis (BM) is crucial for improved management.

Purpose Of The Study

  • To investigate survival periods and immune status in patients with LCs and BM.
  • To develop and validate a predictive model for survival in LCs with BM.

Main Methods

  • Analysis of 86,763 primary LCs from the SEER database, including 15,180 with BM.
  • Construction of a nomogram prediction model using Cox regression and validation with machine learning.
  • Exploration of immune status using flow cytometry and ELISA.

Main Results

  • Prevalence of BM from LCs was 17.49%.
  • Median survival for LCs with BM was 8 months versus 16 months without BM (p <0.001).
  • A validated nomogram demonstrated strong predictive performance (AUCs 0.857-0.786) and correlated with immune status.

Conclusions

  • Brain metastasis significantly worsens the prognosis for lung cancer patients.
  • The developed nomogram is a valuable tool for clinical decision-making and patient management.
  • The model's association with immune status warrants further investigation.

Keywords: