A Nomogram for Predicting Cancer-Specific Survival of TNM 8th Edition Stage I Non-small-cell Lung Cancer.
Clicks: 294
ID: 96044
2019
Article Quality & Performance Metrics
Overall Quality
Improving Quality
0.0
/100
Combines engagement data with AI-assessed academic quality
Reader Engagement
Emerging Content
0.3
/100
1 views
1 readers
Trending
AI Quality Assessment
Not analyzed
Abstract
Models for predicting the survival outcomes of stage I non-small-cell lung cancer (NSCLC) defined by the newly released 8th edition TNM staging system are scarce. This study aimed to develop a nomogram for predicting the cancer-specific survival (CSS) of these patients and identifying individuals with a higher risk for CSS.A total of 30,475 NSCLC cases were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. We identified and integrated the risk factors to build a nomogram. The model was subjected to bootstrap internal validation with the SEER database, and external validation with a multicenter cohort of 1133 patients from China. The difference in the impact of adjuvant chemotherapy on model-defined high- and low-risk patients was examined using the National Cancer Database (NCDB).Eight independent prognostic factors were identified and integrated into the model. The calibration curves showed good agreement. The concordance index (C-index) of the nomogram was higher than that of the staging system (IA1, IA2, IA3, and IB) (internal validation set 0.63 vs. 0.56; external validation set 0.66 vs. 0.55; both p < 0.01). Specifically, 21.7% of stage IB patients (7.5% of all stage I) were categorized into the high-risk group (score > 30). There was a significant interaction effect between the adjuvant chemotherapy and risk groups in the NCDB cohort (p = 0.003).We established a practical nomogram to predict CSS for 8th edition stage I NSCLC. A prospective study is warranted to determine its role in identifying adjuvant chemotherapy candidates.Reference Key |
zeng2019aannals
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
---|---|
Authors | Zeng, Yuan;Mayne, Nicholas;Yang, Chi-Fu Jeffrey;D'Amico, Thomas A;Ng, Calvin S H;Liu, Chia-Chuan;Petersen, René Horsleben;Rocco, Gaetano;Brunelli, Alessandro;Liu, Jun;Liu, Yang;Huang, Weizhe;He, Jiaxi;Wang, Wei;Jiang, Long;Cui, Fei;Wang, Wenjun;Liang, Wenhua;He, Jianxing;, ; |
Journal | annals of surgical oncology |
Year | 2019 |
DOI | 10.1245/s10434-019-07318-7 |
URL | |
Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.