4.1 Article Proceedings Paper

Clinical prognostic model for older patients with advanced non-small cell lung cancer

期刊

JOURNAL OF GERIATRIC ONCOLOGY
卷 10, 期 4, 页码 555-559

出版社

ELSEVIER
DOI: 10.1016/j.jgo.2019.02.007

关键词

Prognostic models; Older patients; Survival; Non-small cell lung cancer; Geriatric oncology

资金

  1. National Institutes of Health [R21-AG042894]
  2. National Cancer Institute [P01-CA142538]
  3. Health and Medical Research Fund [15162491]

向作者/读者索取更多资源

Background: Older patients with non-small cell lung cancer (NSCLC) are often not prescribed standard therapy. It is important to know which older patients would be candidates for aggressive therapy based on their prognosis, and to develop a model that can help determine prognosis. Methods: Data on older patients (>= 70 years) enrolled on 38 NCI cooperative group trials of advanced NSCLC from 1991 to 2011 were analyzed. Multivariable Cox PH model was built with a stepwise selection. We derived a prognostic score using the estimated Cox PH regression coefficient. We then calculated the area under receiver operating characteristic (ROC) curve of survival in the testing set. Results: The final analysis included 1467 patients, who were randomly divided into a training (n = 963) and a testing set (n = 504). The prognostic risk score was calculated as: 3 (if male) + 3 (if PS = 1) + 8 (if PS = 2) + 11 (if initial stage = IV) + 4 (if weight loss). Patients were classified into two prognostic groups: good (0-8) and poor (>= 9). The median survival in the two groups in the testing set were 13.15 (95% CI, 10.82-15.91) and 8.52 months (95% CI, 7.5-9.63), respectively. The model had area under the 1-year and 2-year ROCs (0.6 and 0.65, respectively) that were higher than existing models. Conclusions: Male gender, poor performance status, distant metastases and recent weight loss predict for poor overall survival (OS) in older patients with advanced NSCLC. This study proposes a simple prognostic model for older adults with advanced NSCLC. (C) 2019 Published by Elsevier Ltd.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.1
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据