Systematic review and meta-analysis of temozolomide in animal models of glioma : was clinical efficacy predicted?

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Hirst, T C and Vesterinen, H M and Sena, E S and Egan, K J and MacLeod, M R and Whittle, I R (2013) Systematic review and meta-analysis of temozolomide in animal models of glioma : was clinical efficacy predicted? British Journal of Cancer, 108. pp. 64-71. ISSN 1532-1827 (https://doi.org/10.1038/bjc.2012.504)

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Abstract

Background:Malignant glioma is an aggressive tumour commonly associated with a dismal outcome despite optimal surgical and radio-chemotherapy. Since 2005 temozolomide has been established as first-line chemotherapy. We investigate the role of in vivo glioma models in predicting clinical efficacy.Methods:We searched three online databases to systematically identify publications testing temozolomide in animal models of glioma. Median survival and number of animals treated were extracted and quality was assessed using a 12-point scale; random effects meta-analysis was used to estimate efficacy. We analysed the impact of study design and quality and looked for evidence of publication bias.Results:We identified 60 publications using temozolomide in models of glioma, comprising 2443 animals. Temozolomide prolonged survival by a factor of 1.88 (95% CI 1.74-2.03) and reduced tumour volume by 50.4% (41.8-58.9) compared with untreated controls. Study design characteristics accounted for a significant proportion of between-study heterogeneity, and there was evidence of a significant publication bias.Conclusion:These data reflect those from clinical trials in that temozolomide improves survival and reduces tumour volume, even after accounting for publication bias. Experimental in vivo glioma studies of temozolomide differ from those of other glioma therapies in their consistent efficacy and successful translation into clinical medicine.

ORCID iDs

Hirst, T C, Vesterinen, H M, Sena, E S, Egan, K J ORCID logoORCID: https://orcid.org/0000-0002-1639-4281, MacLeod, M R and Whittle, I R;
CORE (COnnecting REpositories)