Scholarlink

Background <p>Lung cancer with the highest incidence and mortality rates of malignant tumors in the world, has become one of the greatest economic burden diseases in China. To construct a simple, efficient, and practical prognostic model for lung cancer can accurately guide the development of treatment plans for patients without additional expenses, which is beneficial for reducing medical costs and improving patients’ quality of life.</p> Methods <p>Clinical characteristics and blood inflammatory biomarkers (BIBs) of 501 patients diagnosed with NSCLC for the first time between June 2004 and December 2016 were collected. Group analyses were conducted on clinical characteristics and BIBs. Relevant factors for overall survival were selected using LASSO regression, and a prognostic model based on BIBs was established.</p> Results <p>Kaplan–Meier analysis indicated statistically significant differences in lung cancer survival among subgroups of gender, smoking, pathological type, TNM stage, surgical status, and Performance Status (PS) score (all <i>P</i> &lt; 0.05), whereas no significant differences were observed among age and Charlson Comorbidity Index (CCI) subgroups (all <i>P</i> &gt; 0.05). Statistically significant differences in lung cancer survival were also observed among subgroups of various BIBs (all <i>P</i> &lt; 0.05). The BIBs prognostic model demonstrated good predictive value with AUCs of 0.811, 0.891, 0.856, and 0.841 for 1-year, 3-year, 5-year, and 10-year survival, respectively, effectively predicting NSCLC prognosis.</p> Conclusion <p>The prognostic model based on clinical characteristics and BIBs exhibit simplicity, efficiency, and broad application prospects.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A long-term survival prediction model for non-small cell lung cancer based on blood inflammatory biomarkers

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月10日

查看全文
  • Yuxia Du,
  • Weihong Qiu,
  • Fei He,
  • Zhibin Zhou,
  • Weimin Ye

摘要

Background

Lung cancer with the highest incidence and mortality rates of malignant tumors in the world, has become one of the greatest economic burden diseases in China. To construct a simple, efficient, and practical prognostic model for lung cancer can accurately guide the development of treatment plans for patients without additional expenses, which is beneficial for reducing medical costs and improving patients’ quality of life.

Methods

Clinical characteristics and blood inflammatory biomarkers (BIBs) of 501 patients diagnosed with NSCLC for the first time between June 2004 and December 2016 were collected. Group analyses were conducted on clinical characteristics and BIBs. Relevant factors for overall survival were selected using LASSO regression, and a prognostic model based on BIBs was established.

Results

Kaplan–Meier analysis indicated statistically significant differences in lung cancer survival among subgroups of gender, smoking, pathological type, TNM stage, surgical status, and Performance Status (PS) score (all P < 0.05), whereas no significant differences were observed among age and Charlson Comorbidity Index (CCI) subgroups (all P > 0.05). Statistically significant differences in lung cancer survival were also observed among subgroups of various BIBs (all P < 0.05). The BIBs prognostic model demonstrated good predictive value with AUCs of 0.811, 0.891, 0.856, and 0.841 for 1-year, 3-year, 5-year, and 10-year survival, respectively, effectively predicting NSCLC prognosis.

Conclusion

The prognostic model based on clinical characteristics and BIBs exhibit simplicity, efficiency, and broad application prospects.