Abstract 1059P
Background
The impact of the duration of tumor persistence within the host – tumor longevity (TL) – on patient (pt) outcomes under immune checkpoint inhibitors (ICIs) is unexplored. We hypothesized that this time parameter may influence ICIs efficacy. We investigated this association in head and neck squamous cell carcinoma (HNSCC), non-small cell lung cancer (NSCLC), and renal/urothelial cancer (R/UC) pts.
Methods
Retrospective, observational study including adult pts with primary/recurrent HNSCC, NSCLC, R/UC receiving ICIs (≥first line) in 2 Italian centers. Endpoints were the association between TL and: 1) progressive disease (PD) vs. complete response (CR)/ partial response (PR)/ stable disease (SD); 2) Common Terminology Criteria for Adverse Events (CTCAE) G≥3 toxicity; 3) overall survival (OS). Univariable/multivariable logistic regression model (for PD, toxicity) and Cox proportional hazards model (for OS) were used. TL, defined as time from cancer histological diagnosis to ICIs start, was included as continuous variable using 3 knots restricted cubic spline, comparing third (Q3) vs. first (Q1) quartiles.
Results
304 pts, diagnosed in 2002-2022, started ICIs in 2014-2022. TL had a right-skewed distribution [median: 15.3 (Q1-Q3, 5.5; 33.1) months]. CR, PR, SD, PD occurred in 16 (5.3%), 90 (29.6%), 65 (21.4%), 133 (43.7%) pts, respectively; G≥3 toxicity was reported in 16 (5.3%) pts and 231 (76.0%) pts died. Multivariable models adjusted for relevant variables (Table) suggested that longer TL was associated with lower PD odds (Odds Ratio [OR] Q3 vs. Q1 = 0.31; 95% CI 0.12; 0.81, p = 0.004), higher G≥3 toxicity odds (OR = 1.27; 95% CI 0.39; 4.12), lower death risk (Hazard Ratio = 0.79; 95% CI 0.49; 1.28). Table: 1059P
| Descriptive statistics (N=304) | ||
| Sex | Male | 243 (79.9%) |
| Age at diagnosis (years) | Mean (SD) | 64.7 (10.4) |
| Smoking history | Yes | 226 (74.3%) |
| No | 57 (18.8%) | |
| Unknown | 21 (6.9%) | |
| Primary site | NSCLC | 138 (45.4%) |
| HNSCC | 112 (36.5%) | |
| R/UC | 54 (17.8%) | |
| Stage at diagnosis | IV | 199 (65.5%) |
ConclusionsOur real-world, hypothesis-raising results indicate that longer TL may lead to improved response to ICIs, higher risk of G≥3 toxicity and longer OS. Clinical trial identificationEditorial acknowledgementLegal entity responsible for the studyThe authors. FundingAuthors at Niguarda Cancer Center are supported by Fondazione Oncologia Niguarda ETS. DisclosureA. Sartore Bianchi: Financial Interests, Personal, Advisory Board: Amgen, Servier, Novartis; Financial Interests, Personal, Invited Speaker: Bayer, Guardant Health, Pierre Fabre. S. Siena: Financial Interests, Advisory Board: Agenus, Amgen, AstraZeneca, Bayer, BMS, CheckmAb, Clovis, Daiichi Sankyo, Merck, Novartis, Roche-Genentech, Seattle Genetics. L.F.L. Licitra: Financial Interests, Personal, Advisory Board, for expert opinion in advisory boards: AstraZeneca, Bayer, BMS, Eisai, MSD, Boehringer Ingelheim, F. Hoffmann-La Roche Ltd, Novartis, Roche, Debiopharm International SA, Sobi, Incyte Biosciences Italy srl, Doxa Pharma srl, Amgen, Nanobiotics, GSK; Financial Interests, Institutional, Research Grant, Funds received by my institution for clinical studies and research activities in which I am involved: AstraZeneca, BMS, Boehringer Ingelheim, Celgene International, Eisai, Exelixis, Debiopharm International SA, F. Hoffmann-La Roche ltd, IRX Therapeutics, Medpace, Merck-Serono, Merck Healthcare KGaA, MSD, Novartis, Pfizer, Roche, Adlai Nortye. All other authors have declared no conflicts of interest. Resources from the same session927P - Preliminary results of the BROADEN study: Burden of human papillomavirus-related head and neck cancersPresenter: Laia Alemany Session: Poster session 03 928P - Radiomic analysis based on machine learning of multi-MR sequences to assess early treatment response in locally advanced nasopharyngeal carcinomaPresenter: Lei Qiu Session: Poster session 03 929P - Advanced laryngeal squamous cell carcinoma prognosis and machine learning insightsPresenter: Tala Alshwayyat Session: Poster session 03 Resources: Abstract 930P - Real-world data analysis of oncological outcomes in patients with pathological extranodal extension (ENE) in OSCC: A proposal to refine the pathological nodal staging systemPresenter: Abhinav Thaduri Session: Poster session 03 931P - Deep learning models for predicting short-term efficacy in locally advanced nasopharyngeal carcinomaPresenter: Kexin Shi Session: Poster session 03 932P - Accuracy and prognostic implications of extranodal extension on radiologic imaging in HPV-positive oropharyngeal cancer (HNCIG-ENE): A multinational, real-world studyPresenter: Hisham Mehanna Session: Poster session 03 933P - Prediction of survival in patients with head and neck merkel cell carcinoma: Statistical and machine-learning approachesPresenter: Jehad Yasin Session: Poster session 03 934P - Harnessing artificial intelligence on real-world data to predict recurrence in head and neck squamous cell carcinoma patients: The HNC-TACTIC studyPresenter: Hisham Mehanna Session: Poster session 03 936P - Chronic pain in cancer survivors: Head and neck versus other cancersPresenter: Rong Jiang Session: Poster session 03 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.
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