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阐明非小细胞肺癌患者肿瘤大小与生存率之间的关系有助于临床药物开发中的早期决策。

Elucidation of relationship between tumor size and survival in non-small-cell lung cancer patients can aid early decision making in clinical drug development.

作者信息

Wang Y, Sung C, Dartois C, Ramchandani R, Booth B P, Rock E, Gobburu J

机构信息

Division of Pharmacometrics, Office of Clinical Pharmacology, US Food and Drug Administration, Silver Spring, Maryland, USA.

出版信息

Clin Pharmacol Ther. 2009 Aug;86(2):167-74. doi: 10.1038/clpt.2009.64. Epub 2009 May 13.

Abstract

Four non-small-cell lung cancer (NSCLC) registration trials were utilized to develop models linking survival to risk factors and changes in tumor size during treatment. The purpose was to leverage existing quantitative knowledge to facilitate future development of anti-NSCLC drugs. Eleven risk factors were screened using a Cox model. A mixed exponential decay and linear growth model was utilized for modeling tumor size. Survival times were described in a parametric model. Eastern Cooperative Oncology Group (ECOG) score and baseline tumor size were consistent prognostic factors of survival. Tumor size was well described by the mixed model. The parametric survival model includes ECOG score, baseline tumor size, and week 8 tumor size change as predictors of survival duration. The change in tumor size at week 8 allows early assessment of the activity of an experimental regimen. The survival model and the tumor model will be beneficial for early screening of candidate drugs, simulating NSCLC trials, and optimizing trial designs.

摘要

利用四项非小细胞肺癌(NSCLC)注册试验来开发将生存与风险因素以及治疗期间肿瘤大小变化相关联的模型。目的是利用现有的定量知识来促进未来抗NSCLC药物的开发。使用Cox模型筛选了11个风险因素。采用混合指数衰减和线性生长模型对肿瘤大小进行建模。生存时间在参数模型中进行描述。东部肿瘤协作组(ECOG)评分和基线肿瘤大小是生存的一致预后因素。混合模型能很好地描述肿瘤大小。参数生存模型包括ECOG评分、基线肿瘤大小和第8周肿瘤大小变化作为生存持续时间的预测因子。第8周时肿瘤大小的变化有助于早期评估实验方案的活性。生存模型和肿瘤模型将有助于早期筛选候选药物、模拟NSCLC试验以及优化试验设计。

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