Otani Yuki, Zhao Yunqi, Wang Guanyu, Labotka Richard, Rogge Mark, Gupta Neeraj, Vakilynejad Majid, Bottino Dean, Tanigawara Yusuke
Laboratory of Pharmacometrics and Systems Pharmacology, Keio Frontier Research and Education Collaboration Square (K-FRECS) at Tonomachi, Keio University, Kanagawa, Japan.
Takeda Development Center Americas, Inc. (TDCA), Lexington, Massachusetts, USA.
CPT Pharmacometrics Syst Pharmacol. 2024 Dec;13(12):2124-2136. doi: 10.1002/psp4.13225. Epub 2024 Sep 17.
Multiple myeloma (MM) treatment guidelines recommend waiting for formal progression criteria (FPC) to be met before proceeding to the next line of therapy. As predicting progression may allow early switching to next-line therapy while the disease burden is relatively low, we evaluated the predictive accuracy of a mathematical model to anticipate relapse 180 days before the FPC is met. A subset of 470/1143 patients from the IA16 dataset who were initially treated with VRd (Velcade (bortezomib), Revlimid (lenalidomide), and dexamethasone) in the CoMMpass study (NCT01454297) were randomly split 2:1 into training and testing sets. A model of M-protein dynamics was developed using the training set and used to predict relapse probability in patients in the testing set given their response histories up to 12 or more months of treatment. The predictive accuracy of this model and M-protein "velocity" were assessed via receiver operating characteristics (ROC) analysis. The final model was a two-population tumor growth inhibition model with additive drug effect and transit delay compartments for cell killing. The ROC area under the curve value of relapse prediction 180 days ahead of observed relapse by FPC was 0.828 using at least 360 days of response data, which was superior to the M-protein velocity ROC score of 0.706 under the same conditions. The model can predict future relapse from early M-protein responses and can be used in a future clinical trial to test whether early switching to second-line therapy results in better outcomes in MM.
多发性骨髓瘤(MM)治疗指南建议,在开始下一线治疗之前,需等待满足正式的疾病进展标准(FPC)。由于预测疾病进展可能有助于在疾病负担相对较低时尽早切换至下一线治疗,我们评估了一个数学模型在FPC满足前180天预测复发的准确性。在CoMMpass研究(NCT01454297)中,最初接受VRd(万珂(硼替佐米)、来那度胺和地塞米松)治疗的IA16数据集中的470/1143例患者被随机按2:1比例分为训练集和测试集。利用训练集建立了M蛋白动力学模型,并根据患者长达12个月或更长时间的治疗反应史,用于预测测试集中患者的复发概率。通过受试者工作特征(ROC)分析评估该模型和M蛋白 “速度” 的预测准确性。最终模型是一个具有加性药物效应和细胞杀伤转运延迟区室的双群体肿瘤生长抑制模型。使用至少360天的反应数据,在FPC观察到复发前提前180天进行复发预测的ROC曲线下面积值为0.828,优于相同条件下M蛋白速度的ROC评分0.706。该模型可以根据早期M蛋白反应预测未来复发,并可用于未来的临床试验,以测试早期切换至二线治疗是否能在MM中带来更好的结果。