TITLE

Nomogram Predicting Clinical Outcomes in Non-small Cell Lung Cancer Patients Treated with Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors

AUTHOR(S)
Bhumsuk Keam; Dong-Wan Kim; Jin Hyun Park; Jeong-Ok Lee; Tae Min Kim; Se-Hoon Lee; Doo Hyun Chung; Dae Seog Heo
PUB. DATE
October 2014
SOURCE
Cancer Research & Treatment;2014, Vol. 46 Issue 4, p323
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Purpose The aim of this study was to develop a pragmatic nomogram for prediction of progressionfree survival (PFS) for the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) in EGFR mutant non-small cell lung cancer (NSCLC). Materials and Methods A total of 306 recurred or metastatic NSCLC patients with EGFR mutation, who received EGFR TKIs, were enrolled in this study. We developed the nomogram, using a Cox proportional hazard regression model for PFS. Results The median PFS was 11.2 months. Response rate to EGFR TKI was 71.9%. Multivariate Cox model identified disease status, performance status, chemotherapy line, response to EGFR TKI, and bone metastasis as independent prognostic factors, and the nomogram for PFS was developed, based on these covariates. The concordance index for a nomogram was 0.708, and the calibration was also good. Conclusion We developed a nomogram, based on clinical characteristics, for prediction of the PFS to EGFR TKI in NSCLC patients with EGFR mutation.
ACCESSION #
98855008

 

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