Chakraborty Shubhadeep, Aggarwal Kshitij, Chowdhury Marzana, Hamada Izumi, Hu Chuanpu, Kondic Anna, Mishra Kaushal, Paulucci David, Tiwari Ram, Appanna Kalyanee Viraswami, Balan Mariann Micsinai, Kumar Arun
Bristol-Myers Squibb Company, Princeton, NJ, USA.
Global Stat Solutions, Reston, VA, USA.
J Pharmacokinet Pharmacodyn. 2024 Dec 20;52(1):9. doi: 10.1007/s10928-024-09946-3.
In oncology drug development, overall response rate (ORR) is commonly used as an early endpoint to assess the clinical benefits of new interventions; however, ORR benefit may not always translate into a long-term clinical benefit such as overall survival (OS). Most of the work on developing endpoints based on tumor growth dynamics relies on empirical validation, leading to a lack of generalizability of the endpoints across indications and therapeutic modalities. Additionally, many of these metrics are model-based and do not use data from all the patients. The objective of this work is to use longitudinal tumor size data and new lesion information (that is, the same information used by the ORR) to develop novel endpoints that can improve early clinical decision-making compared to the ORR. We investigate in this work multiple candidate novel endpoints based on tumor size ratio that utilize longitudinal tumor size data from all the patients regardless of their follow-up, rely only on tumor size and new lesion information, and are model-free. An extensive simulation study is conducted, exploring a wide spectrum of tumor size data and overall survival outcomes by modulating a variety of trial characteristics such as slow vs fast tumor growth, high vs low drug efficacy rates, variability in patients' responses, variations in the number of patients, follow-up periods, new lesion rates and survival curve shapes. The proposed novel endpoints based on tumor size ratio consistently outperform the ORR by having a comparable or higher correlation with the OS. Further, the novel endpoints exhibit superior accuracy compared to the ORR in predicting the long-term OS benefit. Retrospective empirical validation on BMS clinical trials confirms our simulation findings. These findings suggest that the tumor size ratio-based endpoints could replace ORR for early clinical decision-making in oncology drug development.
在肿瘤学药物研发中，总缓解率（ORR）通常被用作评估新干预措施临床益处的早期终点；然而，ORR获益并不总是能转化为诸如总生存期（OS）等长期临床益处。大多数基于肿瘤生长动力学开发终点的工作依赖于经验验证，导致这些终点在不同适应症和治疗方式之间缺乏通用性。此外，许多这些指标是基于模型的，并未使用所有患者的数据。这项工作的目的是利用纵向肿瘤大小数据和新病灶信息（即与ORR使用的相同信息）来开发新的终点，与ORR相比，这些新终点能够改善早期临床决策。在这项工作中，我们研究了多个基于肿瘤大小比的候选新终点，这些终点利用了所有患者的纵向肿瘤大小数据，无论其随访情况如何，仅依赖肿瘤大小和新病灶信息，并且是无模型的。我们进行了广泛的模拟研究，通过调节各种试验特征，如肿瘤生长快慢、药物有效率高低、患者反应的变异性、患者数量的变化、随访期、新病灶发生率和生存曲线形状，探索了广泛的肿瘤大小数据和总生存结果。所提出的基于肿瘤大小比的新终点与OS具有可比或更高的相关性，始终优于ORR。此外，在预测长期OS获益方面，新终点比ORR表现出更高的准确性。对百时美施贵宝（BMS）临床试验的回顾性经验验证证实了我们的模拟结果。这些结果表明，基于肿瘤大小比的终点可在肿瘤学药物研发的早期临床决策中取代ORR。
