Assessing immunotherapy response: going beyond RECIST by integrating early tumor growth kinetics

评估免疫疗法反应:超越RECIST标准,整合早期肿瘤生长动力学

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Abstract

OBJECTIVE: Assess the contribution of early tumor growth dynamics modeling to predict clinical outcomes in non-small cell lung cancer patients receiving immunotherapy, alongside standard RECIST 1.1 criteria. METHODS: Our retrospective studies used data from 861 patients with advanced NSCLC enrolled in three randomized Phase III trials evaluating immunotherapy plus chemotherapy were analyzed. Tumor size measurements up to two follow-up time points were used to fit a novel Gompertz model and estimate growth rate (GR) and kinetic parameters representing depth of response (A), speed of response (B), and long-term modulation (M). Correlations between these early tumor growth parameters and clinical outcomes such as progression-free survival (PFS) and time to response (TTR) were assessed. Descriptive and discriminative analyses were performed to delineate tumor growth dynamics across various response profiles based on RECIST 1.1 criteria. RESULTS: The novel Gompertz model accurately described early tumor growth kinetics in 861 non-small cell lung cancer patients treated with immunotherapy. Lower growth rate (GR) and model parameter M were associated with longer progression-free survival (PFS) (HR=0.897 and 7.47x10^-7, respectively). Higher GR and parameter A correlated with shorter time to response (HR=0.575 and 0.696, respectively). Responders had significantly lower A (p=1.51e-53) and higher GR (p=0.4e-12) than non-responders. Non-durable stable disease patients had higher GR (p=0.0001) and parameter B (p=0.0002) compared to late responders. Early tumor growth parameters showed potential for predicting long-term outcomes and treatment response patterns.

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