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使用动态生物标志物总生存期模型为药物开发和个性化医学中的早期临床决策提供支持,以使用检查点抑制剂。

Support to early clinical decisions in drug development and personalised medicine with checkpoint inhibitors using dynamic biomarker-overall survival models.

机构信息

Clinical Pharmacology, Genentech-Roche, Marseille, France.

Clinical Pharmacology, Genentech-Roche, Lyon, France.

出版信息

Br J Cancer. 2023 Oct;129(9):1383-1388. doi: 10.1038/s41416-023-02190-5. Epub 2023 Feb 10.

Abstract

Longitudinal models of biomarkers such as tumour size dynamics capture treatment efficacy and predict treatment outcome (overall survival) of a variety of anticancer therapies, including chemotherapies, targeted therapies, immunotherapies and their combinations. These pharmacological endpoints like tumour dynamic (tumour growth inhibition) metrics have been proposed as alternative endpoints to complement the classical RECIST endpoints (objective response rate, progression-free survival) to support early decisions both at the study level in drug development as well as at the patients level in personalised therapy with checkpoint inhibitors. This perspective paper presents recent developments and future directions to enable wider and robust use of model-based decision frameworks based on pharmacological endpoints.

摘要

生物标志物(如肿瘤大小动态)的纵向模型可捕获各种抗癌疗法(包括化疗、靶向治疗、免疫治疗及其组合)的治疗效果,并预测治疗结果(总生存期)。这些药理学终点(如肿瘤动态[肿瘤生长抑制]指标)已被提议作为替代终点,以补充经典的 RECIST 终点(客观缓解率、无进展生存期),以支持药物开发中的研究层面以及检查点抑制剂的个体化治疗中的患者层面的早期决策。本观点文章介绍了使基于药理学终点的基于模型的决策框架得到更广泛和稳健应用的最新进展和未来方向。

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