A Nomogram for Predicting Cancer-Specific Survival of TNM 8th Edition Stage I Non-small-cell Lung Cancer.

Journal Article (Journal Article)

BACKGROUND: 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. METHODS: 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). RESULTS: 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). CONCLUSIONS: 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.

Full Text

Duke Authors

Cited Authors

  • Zeng, Y; Mayne, N; Yang, C-FJ; D'Amico, TA; Ng, CSH; Liu, C-C; Petersen, RH; Rocco, G; Brunelli, A; Liu, J; Liu, Y; Huang, W; He, J; Wang, W; Jiang, L; Cui, F; Wang, W; Liang, W; He, J; AME Thoracic Surgery Collaborative Group,

Published Date

  • July 2019

Published In

Volume / Issue

  • 26 / 7

Start / End Page

  • 2053 - 2062

PubMed ID

  • 30900105

Electronic International Standard Serial Number (EISSN)

  • 1534-4681

Digital Object Identifier (DOI)

  • 10.1245/s10434-019-07318-7


  • eng

Conference Location

  • United States