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

ePoster Display

1001P - A radiomics model for effective prediction of the treatment benefits of programmed cell death 1 inhibitors in advanced gastric cancer

Date

16 Sep 2021

Session

ePoster Display

Presenters

Ai Huang

Citation

Annals of Oncology (2021) 32 (suppl_5): S829-S866. 10.1016/annonc/annonc705

Authors

A. Huang1, H. Ma1, J. Bi2, Y. Xiao1, Z. liang1, T. Zhang1

Author affiliations

  • 1 Oncology Department, Cancer Center Union Hospital, 430023 - Wuhan/CN
  • 2 Department Of Radiation Oncology, Hubei Cancer Hospital, 430030 - Wuhan/CN
More

Abstract 1001P

Background

Screening main beneficiaries of PD-1inhibitors are vital for desired outcomes in advanced gastric cancer. The present study aimed to construct an individualized radiomics model to predict the treatment benefits of Programmed cell death 1 (PD-1) inhibitors in advanced gastric cancer.

Methods

Clinical data of 58 patients with advanced gastric cancer receiving PD-1 inhibitors were retrospective analyzed to identify major clinicopathological factors related to treatment outcomes. The pretreatment-enhanced computed tomography (CT) imaging data were extracted, and an individual radiomics nomogram was constructed based on the imaging features and clinicopathological risk factors. The performance and clinical utility of radiomics model to predict anti-PD-1efficacy was evaluated through receiver operator characteristic (ROC), and further survival prediction was explored.

Results

Serum carcinoembryonic antigen and tumor metastasis site showed a correlation with PD-1 inhibitors response. The radiomics nomogram based on these two clinical factors and imaging features effectively predicted the treatment response of PD-1 inhibitors in both training (the area under curve [AUC] 0.813, 95% confidence interval [CI]: 0.803–0.822) and validation cohorts (AUC, 0.750, 95% CI: 0.717–0.782), obviously prior to the above clinical factors (P < 0.01). Patients with a low-risk probability of disease progress discriminated by the nomogram showed a significantly longer median progression-free survival time than that those with a high risk (9.7 vs. 5.8 months, HR 0.278, 95% CI: 0.084-0.918, P = 0.036).

Conclusions

The CT-based radiomics nomogram could predict the treatment benefits of PD-1 inhibitors in advanced gastric cancer, thereby guiding the decision-making of clinical treatment.

Clinical trial identification

This clinical trial is a retrospective observational study that was approved by the Ethics Committee of Huazhong University of Science and Technology, (number UHCT-IEC-SOP-016-02-03).

Editorial acknowledgement

Legal entity responsible for the study

Wuhan Union Hospital.

Funding

National Key R&D Program of China (2018YFC1313300), the Natural Science Foundation of Hubei Province of China (Grant No. 2019CFB720) and the Chinese Society of Clinical Oncology (CSCO) (Grant No. Y-MX2016-051).

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.