Novel endpoints based on tumor growth dynamics – A comprehensive simulation study with retrospective validation
Authors: Hamada Izumi , Aggarwal Kshitij , Chowdhury Marzana , Chakraborty Shubhadeep , Hu Chuanpu , Kondic Anna , Paulucci David , Mishra Kaushal , Balan Mariann Micsinai , Appanna Kalyanee , Kumar Arun 
Published: February 2025

Objectives: In oncology drug development, the overall response rate (ORR) is commonly used as an early endpoint to assess the clinical benefit of a new intervention. ORR benefits, however, may not always translate well into long-term clinical benefits, such as overall survival (OS) [1-2]. In recent decades, exploring different metrics capturing tumor growth dynamics (TGD) has been of interest to the drug developers and regulatory agencies as an alternative to the ORR to make early clinical trial decisions [3-5]. However, there has not been a systematic evaluation of the TGD endpoints, resulting in a lack of generalizability across indications and therapeutic modes. Additionally, in many cases, patients with limited observations are dropped from the analysis, which introduces bias in the summary information. In the current work, our aim is to develop novel endpoints that utilize tumor size data from all patients and can improve clinical trial decision-making compared to ORR. Methods: We evaluated multiple candidate endpoints that are continuous in scale, using longitudinal tumor size data from all patients, and relying solely on tumor size and new lesion information. A computational framework was built to simulate clinical trials exploring a wide spectrum of tumor size data and overall survival outcomes, covering a broad range of trial characteristics such as slow vs fast tumor growth, high vs low drug efficacy rates as well as variability in the number of patients, patients’ responses and follow-up periods, and to compare the performances of the proposed novel endpoints and ORR in terms of correlations with the OS. Furthermore, a retrospective validation on BMS clinical trials was performed, using data from n = 5193 non-small cell lung cancer patients from six trials and n = 1797 hepatocellular carcinoma patients from three trials were used for the validation. Results: The extensive analysis of simulated clinical trials indicated that the endpoints based on tumor size ratio consistently outperform the ORR by having a comparable or higher correlation with the OS compared to the ORR. Furthermore, the novel endpoints exhibit superior accuracy compared to the ORR in predicting the long-term OS benefit. A retrospective empirical validation confirmed the simulation findings.Conclusions: The extensive simulation results across the broad spectrum of the simulated clinical trials and empirical findings demonstrate the robustness of the proposed tumor size ratio-based endpoints. These endpoints can be considered as alternatives to ORR in various indications and therapeutic modalities, offering improved early clinical decision-making in oncology drug development.Citations: [1] Bruno et al., Br J Cancer. 2023;129(9):1383-1388 [2] Michaelis et al., Nat Rev Cancer. 2006;6(5):409-414 [3] Wang et al., Clin Pharmacol Ther. 2009;86(2):167-174 [4] Tourneau et al., Br J Cancer. 2012;106(5):854-857[5] Claret et al., J Clin Oncol. 2013;31(17):2110-2114