从患者衍生异种移植(PDX)模型预测未治疗患者的肿瘤体积倍增时间和无进展生存期:基于转化模型的方法。

IF 5 3区 医学 Q1 PHARMACOLOGY & PHARMACY
E M Tosca, D Ronchi, M Rocchetti, P Magni
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引用次数: 0

摘要

肿瘤体积倍增时间(TVDT)已被证明是肿瘤生物活性的潜在替代标记物。然而,由于伦理和实际原因,其在临床上的应用受到很大限制,因为对其进行评估需要对未经治疗的患者进行至少两次肿瘤体积测量。在此,我们提出了一个转化建模框架,根据患者异种移植(PDX)小鼠的肿瘤生长数据预测未经治疗的癌症患者群体中的 TVDT 分布。研究考虑了 11 种实体瘤类型。针对每种癌症类型,我们都选择了一组 PDX 小鼠肿瘤生长研究数据,并通过数学模型分析了小鼠肿瘤指数增长率的分布特征。然后,假定人类的肿瘤体积呈指数增长,通过异速缩放法将 PDX 小鼠的增长率按比例放大到人类,并用于预测未经治疗的患者的 TVDT。结果发现,模型预测的 TVDT 与临床观察到的 TVDT 非常吻合,91% 的预测 TVDT 中值在观察值的 1.5 倍以内。此外,利用肿瘤生长动态与无进展生存期(PFS)之间的内在关系,利用人类的指数增长率生成了在没有抗癌治疗的情况下的预期无进展生存期曲线。预测的曲线与已发表的无进展生存期数据非常接近,这些数据来自接受支持性治疗或低效疗法的患者群组研究。所提出的方法有望成为一种潜在的工具,无需直接测量未接受治疗患者的肿瘤尺寸,就能增加对人体 TVDT 的了解,并预测未接受治疗患者的 PFS 曲线,从而弥补临床试验中缺乏安慰剂对照组来比较踩踏组的不足。然而,要全面评估其在这方面的有效性,还需要进一步的验证和改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Predicting Tumor Volume Doubling Time and Progression-Free Survival in Untreated Patients from Patient-Derived-Xenograft (PDX) Models: A Translational Model-Based Approach.

Predicting Tumor Volume Doubling Time and Progression-Free Survival in Untreated Patients from Patient-Derived-Xenograft (PDX) Models: A Translational Model-Based Approach.

Tumor volume doubling time (TVDT) has been shown to be a potential surrogate marker of biological tumor activity. However, its availability in clinics is strongly limited due to ethical and practical reasons, as its assessment requires at least two subsequent tumor volume measurements in untreated patients. Here, a translational modeling framework to predict TVDT distributions in untreated cancer patient populations from tumor growth data in patient-derived xenograft (PDX) mice is proposed. Eleven solid cancer types were considered. For each of them, a set of tumor growth studies in PDX mice was selected and analyzed through a mathematical model to characterize the distribution of the exponential tumor growth rate in mice. Then, assuming an exponential growth of the tumor mass in humans, the growth rates were scaled from PDX mice to humans through an allometric scaling approach and used to predict TVDTs in untreated patients. A very good agreement was found between model predicted and clinically observed TVDTs, with 91% of the predicted TVDT medians fell within 1.5-fold of observations. Further, exploiting the intrinsic relationship between tumor growth dynamics and progression free survival (PFS), the exponential growth rates in humans were used to generate the expected PFS curves in absence of anticancer treatment. Predicted curves were extremely close to published PFS data from studies involving patient cohorts treated with supportive care or low effective therapies. The proposed approach shows promise as a potential tool to increase knowledge about TVDT in humans without the need of directly measuring tumor dimensions in untreated patients, and to predict PFS curves in untreated patients, that could fill the absence of placebo-controlled arms against which to compare treaded arms during clinical trials. However, further validation and refinement are needed to fully assess its effectiveness in this regard.

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来源期刊
AAPS Journal
AAPS Journal 医学-药学
CiteScore
7.80
自引率
4.40%
发文量
109
审稿时长
1 months
期刊介绍: The AAPS Journal, an official journal of the American Association of Pharmaceutical Scientists (AAPS), publishes novel and significant findings in the various areas of pharmaceutical sciences impacting human and veterinary therapeutics, including: · Drug Design and Discovery · Pharmaceutical Biotechnology · Biopharmaceutics, Formulation, and Drug Delivery · Metabolism and Transport · Pharmacokinetics, Pharmacodynamics, and Pharmacometrics · Translational Research · Clinical Evaluations and Therapeutic Outcomes · Regulatory Science We invite submissions under the following article types: · Original Research Articles · Reviews and Mini-reviews · White Papers, Commentaries, and Editorials · Meeting Reports · Brief/Technical Reports and Rapid Communications · Regulatory Notes · Tutorials · Protocols in the Pharmaceutical Sciences In addition, The AAPS Journal publishes themes, organized by guest editors, which are focused on particular areas of current interest to our field.
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