Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA.
Department of Medicine, Division of Hematology/Oncology, Columbia University Herbert Irving Comprehensive Cancer Center, New York, NY, USA.
Oncologist. 2023 Feb 8;28(2):139-148. doi: 10.1093/oncolo/oyac217.
Methods for screening agents earlier in development and strategies for conducting smaller randomized controlled trials (RCTs) are needed.
We retrospectively applied a tumor growth model to estimate the rates of growth of pancreatic cancer using radiographic tumor measurements or serum CA 19-9 values from 3033 patients with stages III-IV PDAC who were enrolled in 8 clinical trials or were included in 2 large real-world data sets.
g correlated inversely with OS and was consistently lower in the experimental arms than in the control arms of RCTs. At the individual patient level, g was significantly faster for lesions metastatic to the liver relative to those localized to the pancreas. Regardless of regimen, g increased toward the end of therapy, often by over 3-fold.
Growth rates of PDAC can be determined using radiographic tumor measurement and CA 19-9 values. g is inversely associated with OS and can differentiate therapies within the same trial and across trials. g can also be used to characterize changes in the behavior of an individual's PDAC, such as differences in the growth rate of lesions based on metastatic site, and the emergence of chemoresistance. We provide examples of how g can be used to benchmark phase II and III clinical data to a virtual reference arm to inform go/no go decisions and consider novel trial designs to optimize and accelerate drug development.
需要开发早期筛选药物的方法和进行更小规模随机对照试验（RCT）的策略。
我们回顾性地应用肿瘤生长模型，使用 3033 名 III-IV 期 PDAC 患者的影像学肿瘤测量或血清 CA 19-9 值来估算胰腺癌的生长率，这些患者来自 8 项临床试验或 2 项大型真实世界数据集。
g 与 OS 呈负相关，并且在 RCT 的实验组中始终低于对照组。在个体患者水平上，转移性肝癌的病变比胰腺内病变的 g 值明显更快。无论方案如何，g 值在治疗结束时都会增加，通常增加 3 倍以上。
可以使用影像学肿瘤测量和 CA 19-9 值来确定 PDAC 的生长速度。g 与 OS 呈负相关，可以区分同一试验内和不同试验中的治疗方法。g 还可用于描述个体 PDAC 行为的变化，例如基于转移部位的病变生长速度差异以及化疗耐药性的出现。我们提供了如何使用 g 来将 II 期和 III 期临床数据与虚拟参考臂进行基准测试以告知是否进行或停止决策的示例，并考虑了优化和加速药物开发的新型试验设计。
