Assessing Immunotherapy Response: Going Beyond RECIST by Integrating Early Tumor Growth Kinetics

Overview

Journal Front Immunol

Specialty Allergy & Immunology

Date 2025 Jan 6

PMID 39759519

Authors

Mehdi Felfli

Alexandre Thinnes

Sebastien Jacques

Yan Liu

Antoine Iannessi

Affiliations

Soon will be listed here.

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.

References

Okada H, Weller M, Huang R, Finocchiaro G, Gilbert M, Wick W . Immunotherapy response assessment in neuro-oncology: a report of the RANO working group. Lancet Oncol. 2015; 16(15):e534-e542. PMC: 4638131. DOI: 10.1016/S1470-2045(15)00088-1. View

Nishino M, Lu J, Hino T, Vokes N, Janne P, Hatabu H . Tumor Growth Rate After Nadir Is Associated With Survival in Patients With -Mutant Non-Small-Cell Lung Cancer Treated With Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitor. JCO Precis Oncol. 2022; 5:1603-1610. PMC: 9848598. DOI: 10.1200/PO.21.00172. View

Ferte C, Fernandez M, Hollebecque A, Koscielny S, Levy A, Massard C . Tumor growth rate is an early indicator of antitumor drug activity in phase I clinical trials. Clin Cancer Res. 2013; 20(1):246-52. PMC: 3947306. DOI: 10.1158/1078-0432.CCR-13-2098. View

Bruno R, Bottino D, De Alwis D, Fojo A, Guedj J, Liu C . Progress and Opportunities to Advance Clinical Cancer Therapeutics Using Tumor Dynamic Models. Clin Cancer Res. 2019; 26(8):1787-1795. PMC: 8415106. DOI: 10.1158/1078-0432.CCR-19-0287. View

Humbert O, Chardin D . Dissociated Response in Metastatic Cancer: An Atypical Pattern Brought Into the Spotlight With Immunotherapy. Front Oncol. 2020; 10:566297. PMC: 7531255. DOI: 10.3389/fonc.2020.566297. View

Borcoman E, Nandikolla A, Long G, Goel S, Le Tourneau C . Patterns of Response and Progression to Immunotherapy. Am Soc Clin Oncol Educ Book. 2018; 38:169-178. DOI: 10.1200/EDBK_200643. View

Somarouthu B, Lee S, Urban T, Sadow C, Harris G, Kambadakone A . Immune-related tumour response assessment criteria: a comprehensive review. Br J Radiol. 2017; 91(1084):20170457. PMC: 5966001. DOI: 10.1259/bjr.20170457. View

Yin A, Moes D, van Hasselt J, Swen J, Guchelaar H . A Review of Mathematical Models for Tumor Dynamics and Treatment Resistance Evolution of Solid Tumors. CPT Pharmacometrics Syst Pharmacol. 2019; 8(10):720-737. PMC: 6813171. DOI: 10.1002/psp4.12450. View

Berz A, Dromain C, Vietti-Violi N, Boughdad S, Duran R . Tumor response assessment on imaging following immunotherapy. Front Oncol. 2022; 12:982983. PMC: 9641095. DOI: 10.3389/fonc.2022.982983. View

10.

Wang M, Chen C, Jemielita T, Anderson J, Li X, Hu C . Are tumor size changes predictive of survival for checkpoint blockade based immunotherapy in metastatic melanoma?. J Immunother Cancer. 2019; 7(1):39. PMC: 6368769. DOI: 10.1186/s40425-019-0513-4. View

11.

Carroll K . On the use and utility of the Weibull model in the analysis of survival data. Control Clin Trials. 2003; 24(6):682-701. DOI: 10.1016/s0197-2456(03)00072-2. View

12.

Han K, Claret L, Sandler A, Das A, Jin J, Bruno R . Modeling and simulation of maintenance treatment in first-line non-small cell lung cancer with external validation. BMC Cancer. 2016; 16:473. PMC: 4944249. DOI: 10.1186/s12885-016-2455-2. View

13.

Stein W, Figg W, Dahut W, Stein A, Hoshen M, Price D . Tumor growth rates derived from data for patients in a clinical trial correlate strongly with patient survival: a novel strategy for evaluation of clinical trial data. Oncologist. 2008; 13(10):1046-54. PMC: 3313464. DOI: 10.1634/theoncologist.2008-0075. View

14.

Al-Huniti N, Feng Y, Yu J, Lu Z, Nagase M, Zhou D . Tumor Growth Dynamic Modeling in Oncology Drug Development and Regulatory Approval: Past, Present, and Future Opportunities. CPT Pharmacometrics Syst Pharmacol. 2020; 9(8):419-427. PMC: 7438808. DOI: 10.1002/psp4.12542. View

15.

Eisenhauer E, Therasse P, Bogaerts J, Schwartz L, Sargent D, Ford R . New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer. 2008; 45(2):228-47. DOI: 10.1016/j.ejca.2008.10.026. View

16.

Yeh C, Zhou M, Sigel K, Jameson G, White R, Safyan R . Tumor Growth Rate Informs Treatment Efficacy in Metastatic Pancreatic Adenocarcinoma: Application of a Growth and Regression Model to Pivotal Trial and Real-World Data. Oncologist. 2022; 28(2):139-148. PMC: 9907043. DOI: 10.1093/oncolo/oyac217. View

17.

Ramon-Patino J, Schmid S, Lau S, Seymour L, Gaudreau P, Li J . iRECIST and atypical patterns of response to immuno-oncology drugs. J Immunother Cancer. 2022; 10(6). PMC: 9207898. DOI: 10.1136/jitc-2022-004849. View

18.

Bruno R, Marchand M, Yoshida K, Chan P, Li H, Zou W . Tumor Dynamic Model-Based Decision Support for Phase Ib/II Combination Studies: A Retrospective Assessment Based on Resampling of the Phase III Study IMpower150. Clin Cancer Res. 2023; 29(6):1047-1055. PMC: 10023325. DOI: 10.1158/1078-0432.CCR-22-2323. View

19.

He L, Zhang X, Li H, Chen T, Chen C, Zhou Y . Pre-Treatment Tumor Growth Rate Predicts Clinical Outcomes of Patients With Advanced Non-Small Cell Lung Cancer Undergoing Anti-PD-1/PD-L1 Therapy. Front Oncol. 2021; 10:621329. PMC: 7863973. DOI: 10.3389/fonc.2020.621329. View

20.

Bilous M, Serdjebi C, Boyer A, Tomasini P, Pouypoudat C, Barbolosi D . Quantitative mathematical modeling of clinical brain metastasis dynamics in non-small cell lung cancer. Sci Rep. 2019; 9(1):13018. PMC: 6736889. DOI: 10.1038/s41598-019-49407-3. View