In anticancer research, tumor growth measured in mouse models is important for assessing treatment efficacy for a treatment to progress to human clinical trials. Statistical analysis of time-to-event tumor volume data is complex because of heterogeneity in response and welfare-related data loss. Traditional statistical methods of testing the mean difference between groups are not robust because they assume common responses across a population. Heterogeneity in response is also seen in the clinic, and consequently, the assessment of the treatment considers the diversity through classification of the individual’s response using the RECIST (Response Evaluation Criteria in Solid Tumors). To provide a comparable and translatable assessment of in vivo tumor response, we developed a statistical method called INSPECT (IN vivo reSPonsE Classification of Tumors) for analyzing heterogeneous responses through Bayesian modeling. This method can classify individual tumor behaviors into the categories of nonresponder, modest responder, stable responder, and regressing responder. Using both published and simulated data, we show that INSPECT methodology is more accurate and sensitive than existing methods with respect to balancing false-negative and false-positive rates. A case study demonstrates the value of INSPECT in drug projects for supporting the translation of drug efficacy from the preclinical phase into clinical trials. We also provide a package, “INSPECTumours,” that launches a web interface to enable users to conduct the analysis and generate reports.

中文翻译：

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用于分析临床前小鼠肿瘤模型中异质性反应的贝叶斯模型


在抗癌研究中，在小鼠模型中测量的肿瘤生长对于评估治疗进展到人体临床试验的治疗效果非常重要。由于反应的异质性和福利相关数据丢失，事件发生时间肿瘤体积数据的统计分析很复杂。测试组间平均差异的传统统计方法并不稳健，因为它们假设整个群体的共同响应。在临床上也可以看到反应的异质性，因此，通过使用 RECIST（实体瘤反应评估标准）对个体反应进行分类来评估治疗的治疗评估考虑了多样性。为了提供对体内肿瘤反应的可比较和可翻译的评估，我们开发了一种称为 INSPECT（体内 reSPonsE 肿瘤分类）的统计方法，用于通过贝叶斯建模分析异质反应。该方法可将个体肿瘤行为分为无反应者、中等反应者、稳定反应者和消退反应者等类别。使用已发布的和模拟的数据，我们表明 INSPECT 方法在平衡假阴性和假阳性率方面比现有方法更准确、更敏感。案例研究证明了 INSPECT 在药物项目中支持将药物疗效从临床前阶段转化为临床试验的价值。我们还提供了一个软件包“INSPECTumours”，它启动了一个 Web 界面，使用户能够执行分析并生成报告。