Gregory Walter M, Prior Thomas J, Bartlett J Blake, Sonneveld Pieter, Dimopoulos Meletios A, Moreau Philippe, Usmani Saad, Facon Thierry
Division of Clinical Medicine, University of Sheffield, Sheffield, United Kingdom.
Janssen Research & Development, Spring House, Pennsylvania.
Clin Cancer Res. 2025 Jun 3;31(11):2154-2161. doi: 10.1158/1078-0432.CCR-24-3475.
We designed mathematical models to describe and quantify the mechanisms and dynamics of minimal residual disease (MRD) in order to better understand these MRD dynamics; inform future treatment design, including when to stop or change treatment; and extrapolate from current progression-free survival (PFS) times to predict future PFS curves.
This study aims to model individual sequential MRD data from phase III clinical trials (MAIA, CASTOR, and POLLUX) using previously developed mathematical models, which will be modified as needed to accurately reflect the actual MRD data. These models will then be used to project PFS curves into the future.
Patients with low MRD values either showed rapid disease regrowth, or the MRD values remained low for a prolonged period. Treatment seemed to be most effective in terms of cell kill within the first 6 to 12 months. Regrowth rates were correlated with estimated initial residual disease, particularly in MRD-negative patients. Three-year model extrapolations of PFS were closely comparable with clinical trial data.
This model could provide early prediction of PFS outcomes, which otherwise takes lengthy periods of time to observe in clinical trials. Patients showing rapid rebound from low MRD values may benefit from adding another treatment before reaching progressive disease. The MRD analyses and results presented, such as the results about efficacy occurring early in the first 6 to 12 months, may help guide the development and selection of optimal regimens. Longer follow-up periods and application to other trials and datasets are required to substantiate these findings.
我们设计了数学模型来描述和量化微小残留病（MRD）的机制和动态，以便更好地理解这些MRD动态；为未来的治疗设计提供信息，包括何时停止或改变治疗；并从当前的无进展生存期（PFS）时间进行推断，以预测未来的PFS曲线。
本研究旨在使用先前开发的数学模型对III期临床试验（MAIA、CASTOR和POLLUX）中的个体序贯MRD数据进行建模，并根据需要进行修改，以准确反映实际的MRD数据。然后将这些模型用于预测未来的PFS曲线。
MRD值低的患者要么疾病迅速复发，要么MRD值在较长时间内保持较低水平。在最初的6至12个月内，治疗在细胞杀伤方面似乎最有效。复发率与估计的初始残留病相关，特别是在MRD阴性患者中。PFS的三年模型推断与临床试验数据密切可比。
该模型可以提供PFS结果的早期预测，而这在临床试验中需要很长时间才能观察到。从低MRD值迅速反弹的患者可能在疾病进展前加用另一种治疗会受益。所呈现的MRD分析和结果，如关于在最初6至12个月内早期出现疗效的结果，可能有助于指导最佳方案的开发和选择。需要更长的随访期并应用于其他试验和数据集来证实这些发现。
