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 3

2601 - Comparison 18F-FDG-PET/CT criteria for prediction of therapy response and clinical outcome in patients with metastatic melanoma treated with Ipilimumab and PD-1 inhibitors

Date

30 Sep 2019

Session

Poster Display session 3

Topics

Immunotherapy

Tumour Site

Melanoma

Presenters

Sabrina Vari

Citation

Annals of Oncology (2019) 30 (suppl_5): v475-v532. 10.1093/annonc/mdz253

Authors

S. Vari1, A. Annovazzi2, D. Giannarelli3, R. Pasqualoni2, R. Sciuto2, S. Carpano4, V. Ferraresi1, F. Cognetti1

Author affiliations

  • 1 First Oncology Dept., Regina Elena National Cancer Institute, 00144 - Rome/IT
  • 2 Nuclear Medicine Unit, Regina Elena National Cancer Institute, 00144 - Rome/IT
  • 3 Biostatistical Unit, Regina Elena National Cancer Institute, 00144 - Rome/IT
  • 4 Second Oncology Dept., Regina Elena National Cancer Institute, 00144 - Rome/IT

Resources

Login to get immediate access to this content.

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

Abstract 2601

Background

Immune checkpoint inhibitors (ICIs) acting against CTLA-4 and PD-1 represent a strenght therapy in patients (pts) with metastatic melanoma (MM). Antineoplastic activity of ICIs through the activation of immune cells in tumor lesions raised challenge in evaluation of treatment response by imaging. Aim of this study was to compare diagnostic accuracy of different 18F-FDG PET/CT parameters (Metabolic Tumor Volume, MTV; Total Lesion Glycolisis, TLG; Maximum Standardised Uptake Value, SUVmax) to predict therapy response and clinical outcome in pts with MM treated with Ipilimumab (Ipi) and Nivolumab (Nivo) or Pembrolizumab (Pem) and to check for accuracy differences specific for the class of treatment.

Methods

57 MM pts receiving Ipi (25) or PD-1 inhibitors (Nivo 19; Pem 13) who performed a 18F-FDG PET/CT scan at the beginning (PET0) and after completion of Ipi or during anti PD-1 (PET1), were retrospectively evaluated. Response at PET1 was classified as PD, SD, PR and CR according to RECIST 1.1, EORTC criteria and by percentage change of MTV and TLG (cut off values: +43% for PD and -43% for PR, calculated by ROC analysis) of up to 5 target lesions. PET Response Evaluation Criteria for Immunotherapy (PERCIMT) were assessed alone and with the previously described parameters. Performance of each criteria at PET1 to predict pts having clinical benefit (CR, PR and SD) and no clinical benefit (PD) at 6 months since starting ICIs were assessed and correlated to time-to-progression.

Results

For Ipi pts group, best predictors of response were: variation of MTV (Sensitivity 1; Specificity 0.84; accuracy 0.96) and TLG (Se 0.89; Sp; 93.8; acc 0.92), with PERCIMT criteria for progressive disease. In anti-PD1 group overlapping predictivity values were found for EORTC, MTV and TLG (Se 0.95; Sp 1; Acc 0.97). Reliability of above parameters was also confirmed in predicting pts progression free survival at 12 and 24 months.

Conclusions

18F-FDG PET/CT performed 3 months later the first administration could predict response to ICIs and long-term patient clinical outcome. Performance of 18F-FDG PET/CT parameters and criteria in predicting response to ICIs is influenced by the class of treatment.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

Local Ethic committee.

Funding

Has not received any funding.

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.