Abstract 129P
Background
ICIs are widely used in aNSCLC, but reliable predictive markers are still missing. Preliminary data suggest potential role for longitudinal LB in predicting clinical outcome and identifying pts likely to derive detrimental effects. Aim of this work is to develop a model integrating clinico-pathological variables with longitudinal LB results.
Methods
We prospectively enrolled aNSCLC pts treated with ICIs at Veneto Institute of Oncology from 2017 to 2019. LB was performed at baseline (T1), after 3-4 weeks of ICI treatment (T2). Each sample was evaluated for cell free DNA (cfDNA) quantification and analysed with a 56 gene amplicon-based NGS panel. cfDNA quantification and variant allele fraction (VAF) of tumor-associated genetic alterations were evaluated as static and dynamic parameters. The genetic alteration with the highest VAF at baseline was considered as reference for NGS analysis. Variables independently associated with the clinical outcome (p<0.05) in a multiple Cox survival model were used to derive a risk score for predicting survival probabilities.
Results
One hundred thirteen pts were included in the analysis, 57 of them were treated in first-line. cfDNA quantification at T1, VAF at T2, cfDNA change (T2-T1), PD-L1 expression and non squamous histology were significantly associated with progression-free survival (PFS); cfDNA at T2, VAF at T2, histology and PD-L1 >/=50% were associated with overall survival (OS). Pts with all favourable variables had 70% probability of 2 year-survival and 56% probability of 3 year-survival, while all unfavourable variables were associated with only 6% probability of 6 month-survival. LB at T2 is also able to identify pts at higher risk of death within 12 weeks since the start of ICIs and define prognostic groups in pts with equal radiological response.
Conclusions
Association of clinical variables and LB performed early during ICI treatment is able to predict OS. This integrated model upon further validation could be implemented in clinical practice to personalize treatment strategies.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Istituto Oncologico Veneto IOV IRCCS.
Funding
Istituto Oncologico Veneto IOV IRCCS.
Disclosure
L. Bonanno: Financial Interests, Personal, Advisory Board: AstraZeneca, MSD, BMS, Roche; Financial Interests, Personal, Invited Speaker: AstraZeneca, MSD, BMS, Roche; Financial Interests, Personal and Institutional, Invited Speaker: AstraZeneca. G. Pasello: Financial Interests, Institutional, Advisory Board: AstraZeneca, Boehringer Ing, MSD, Pfizer, Takeda; Financial Interests, Institutional, Invited Speaker: BMS, Eli Lilly, Novartis, Roche; Non-Financial Interests, Institutional, Principal Investigator: Amgen, AstraZeneca, Roche, Novartis, Eli Lilly. M. Fassan: Non-Financial Interests, Personal and Institutional, Research Grant: QED Therapeutics, Astellas Pharma; Financial Interests, Personal, Invited Speaker: Astellas Pharma, Tesaro, Roche, Diaceutics. V. Guarneri: Financial Interests, Personal, Advisory Board: Roche, Eli Lilly, Novartis, MSD, Gilead; Financial Interests, Personal, Invited Speaker: Eli Lilly, Novartis; Financial Interests, Institutional, Invited Speaker: Eli Lilly, Roche, BMS, Novartis, AstraZeneca, MSD, Synton Biopharmaceuticals, Merck. S. Indraccolo: Financial Interests, Personal, Invited Speaker: AstraZeneca. All other authors have declared no conflicts of interest.