Oops, you're using an old version of your browser so some of the features on this page may not be displaying properly.

MINIMAL Requirements: Google Chrome 24+Mozilla Firefox 20+Internet Explorer 11Opera 15–18Apple Safari 7SeaMonkey 2.15-2.23

Poster Display session

28P - Generation and validation of a predictive model using pretreatment clinical factors for estimating survival and T790M mutation in EGFR-mutated non-small cell lung cancer in Taiwan

Date

31 Mar 2023

Session

Poster Display session

Presenters

Chien-Chung Lin

Citation

Journal of Thoracic Oncology (2023) 18 (4S): S35-S88.
<article-id>elcc_Ch01

Authors

C. Lin1, Y. Chou2, C. Lin2, C. Wu3, C. Yang3, J.W. Chang4

Author affiliations

  • 1 Tainan City/TW
  • 2 NCKU - National Cheng Kung University, Tainan City/TW
  • 3 Chang Gung Medical Foundation - Linkou Chang Gung Memorial Hospital, Taoyuan City/TW
  • 4 Chang Gung Medical Foundation- Taipei Chang Gung Memorial Hospital, Taipei City/TW

Resources

Login to get immediate access to this content.

If you do not have an ESMO account, please create one for free.

Abstract 28P

Background

Although epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) have been the standard treatment for advanced EGFR-Mutated NSCLC, the generation and validation of a comprehensive platform in predicting survival of these patients remain rare.

Methods

From October 2010 to 2021, we collected potential prognostic factors from advanced stage NSCLC patients receiving EGFR-TKI treatment at National Chen-Kung University, Tainan, Taiwan (NCKUH). Using univariate and multivariate analyses, we identify potential prognostic factors and create a nomogram for risk stratification accordingly. Then we validated the platform in another cohort from Chang Gung Memorial Hospital.

Results

Records of 761 EGFR-Mutated NSCLC patients from NCKUH were retrospectively reviewed. Using univariate analysis, we identified 8 prognostic factors including sex, ECOG status, morphology, mutation, stage, the choice of EGFR-TKIs, and metastasis to liver, brain and multivariate analysis confirmed their independent significance. We established a nomogram based on these factors and successfully classified patients into different risk groups with different survival. This nomogram can be used to predict the possibility of 6-,9-, and 12-month PFS and stratify patients into different risk groups for PFS and OS. In addition, patients with shorter PFS predicted by the nomogram had significantly higher incidence of acquired T790M mutation upon disease progression, which implied the early emergence of T790M might be predicted by this nomogram. We then successful validated the risk score in another cohort including 751 EGFR-Mutated NSCLC patients from Chang-Gung Memorial Hospital. The calibration curves for the probability of survival at 6, 9, and 12 months after EGFR-TKI use revealed a good concordance between the nomogram prediction and actual observation. Moreover, the calibration curves of these two cohorts showed similar pattern.

Conclusions

Our risk stratification can provide additional information to clinicians to evaluate the prognosis and the chance of sequential therapy in patients with EGFR-Mutated NSCLC patients who received targeted therapy.

Legal entity responsible for the study

The authors.

Funding

National Science and Technology Council (110-2314-B-006 -098 -MY3,109-2314-B-006-083 and MOST 108-2314-B-006-092-MY2.

Disclosure

All authors have declared no conflicts of interest.

This site uses cookies. Some of these cookies are essential, while others help us improve your experience by providing insights into how the site is being used.

For more detailed information on the cookies we use, please check our Privacy Policy.

Customise settings
  • Necessary cookies enable core functionality. The website cannot function properly without these cookies, and you can only disable them by changing your browser preferences.