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Poster session 14

767P - Refining patients’ selection for immunotherapeutic early-phase clinical trials (ieCTs): A single phase I unit experience

Date

10 Sep 2022

Session

Poster session 14

Topics

Clinical Research;  Tumour Immunology;  Translational Research;  Molecular Oncology;  Immunotherapy

Tumour Site

Presenters

Agnese Losurdo

Citation

Annals of Oncology (2022) 33 (suppl_7): S331-S355. 10.1016/annonc/annonc1058

Authors

A. Losurdo, P. Persico, E. Lorenzi, A. Dipasquale, A. Di Muzio, L. Giordano, M. Simonelli, A. Santoro

Author affiliations

  • Oncology And Hematology Department, IRCCS Humanitas Research Hospital, 20089 - Rozzano/IT

Resources

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Abstract 767P

Background

Identifying patients mostly benefitting from ieCTs is of crucial importance in the era of precision medicine. The Gustave Roussy Immune Score (GRImS) identifies two prognostic categories (low risk, 0-1; high risk, 2-3) based on three objective variables: LDH > ULN, albumin < 35 g/dl, NLR>6 and has been proved to work as a good prognostic index. However, no predictive score has been validated to be used in clinical practice so far.

Methods

We retrospectively collected clinical-pathologic, laboratory and treatment-specific characteristic of consecutive patients, enrolled in ieCTs from January 2014 to July 2020 at Humanitas Research Hospital Phase I Unit. A large series of variables were correlated with progression-free survival (PFS) and overall survival (OS) through univariate and multivariate analysis (UVA; MVA). P-value for statistical significance was set at 0.050.

Results

A total of 208 pts (M/F:119/89; median age: 62.5 yrs) with advanced solid tumors treated into ieCTs have been selected. The most frequent histologies were NSCLC (22%), HCC (19%), and glioblastoma (11%). With a median follow-up of 28.4 months (mos), the PFS was 3.6 mos, and the OS was 10.8 mos. At the UVA, among clinical-pathologic characteristics, the number of metastatic sites (NMS, 1-2 sites vs >2 sites) proved statistically significant in terms of both PFS and OS, while NLR predicted better OS and age did not influence prognosis. In the MVA, GRImS (OS HR:1.64, p=0.009; PFS HR:1.36, p=0.083) and NMS (OS HR:2.07, p<0.001; PFS HR:1.49, p=0.018) confirmed their prognostic effect. Thus, we crossed GRImS and NMS and observed a statistically significant prognostic trend, with GRImS low/NMS low (mPFS 5.7 mos; mOS 20.5 mos) reporting a statistically significant better mPFS and mOS compared to GRImS low/NMS high (mPFS 3.5 mos; mOS 8.5 mos), GRImS high/NMS low (mPFS 3 mos; mOS 10.4 mos), and GRImS high/NMS high (mPFS 1.1 mos; mOS 4.4 mos).

Conclusions

We assessed the prognostic accuracy of GRImS in our ieCTs cohort. We found that NMS might be usefully integrated into the GRImS in order to better refine prognosis and potentially identify patients who may benefit more from enrollment in ieCTs.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

A. Santoro: Financial Interests, Personal, Advisory Board: Sandoz, Servier, Pfizer, BMS, Eisai, Roche, Novartis, Gilead. All other authors have declared no conflicts of interest.

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