Literature DB >> 24122760

Prediction of overall survival or progression free survival by disease control rate at week 8 is independent of ethnicity: Western versus Chinese patients with first-line non-small cell lung cancer treated with chemotherapy with or without bevacizumab.

Laurent Claret1, Manish Gupta, Kelong Han, Amita Joshi, Nenad Sarapa, Jing He, Bob Powell, René Bruno.   

Abstract

Categorizations of best response observed at week 8 (between week 3 and 14) of first-line treatment in two studies of bevacizumab plus chemotherapy in Western (878 patients) and Chinese (198 patients) patients with non-small cell lung cancer were assessed together with baseline prognostic factors in multivariate parametric models to predict overall survival (OS) and progression free survival (PFS). Predictive performances of the models were assessed by simulating multiple replicates of the studies. Disease control rate (DCR) was the best response categorization to predict OS and PFS. In the OS model, DCR fully captured bevacizumab effect. For PFS, DCR did not fully capture bevacizumab treatment effect. The models adequately predicted OS and PFS distributions in each arm as well as bevacizumab hazard ratio (HR) for OS and PFS, for example, in Western patients (model prediction [95% prediction interval]: 0.84 [0.71-0.98] vs. observed: 0.77 for OS and 0.59 [0.49-0.72] vs. observed: 0.58 for PFS). Covariates in the models captured endpoint differences seen in Chinese patients. There was no impact of Chinese ethnicity on the DCR relationship to OS or PFS. DCR predicted OS benefit with bevacizumab in first-line NSCLC patients. Western data can be used to inform design of studies in Chinese patients.
© 2013, The American College of Clinical Pharmacology.

Entities:  

Keywords:  NSCLC; ethnic differences; overall survival; predictive model; progression free survival; response categories

Mesh:

Substances:

Year:  2013        PMID: 24122760     DOI: 10.1002/jcph.191

Source DB:  PubMed          Journal:  J Clin Pharmacol        ISSN: 0091-2700            Impact factor:   3.126


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