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), patients characteristics (such as mean or median of age, percentage of male, number of patients stratified by biomarker status etc.), biomarkers detection and treatment protocol (such as methods for testing biomarkers status, lines of treatment, study treatment protocols etc.) and outcome assessment [such as the response criteria, objective response rate (ORR), PFS, OS etc.]. The results on clinical outcomes were extracted http://www.selleck.cn/products/bgj398-nvp-bgj398.html in a stratified manner according to the biomarkers status. In the absence of widely accepted criteria for the methodological or internal quality of the kind of studies that we included, we assessed the study quality in a descriptive and qualitative approach rather than a quantitative one, with regard to the following aspects which were largely consistent with REporting recommendations for tumor MARKer prognostic studies (REMARK) guidelines:[20] design of the parent study (if http://www.selleckchem.com/products/Bortezomib.html applicable), methods of patient sampling, length of follow-up, whether the biomarker analysis was prespecified, whether tumor tissue samples were available for the majority of participants in the parent study, whether the patients with biomarker testing results were clinically representative, methods of biomarker testing, definitions of clinical end points, methods of outcome measurement and methods of data analysis. The primary outcomes were PFS and OS. The association between biomarker status and PFS or OS was expressed as a hazard ratio (HR) with 95% confidence interval (CI). The secondary outcome was objective response. The association between biomarker status and objective response was expressed as a rate difference (RD [95% CI]), which was defined as the ORR in biomarker-positive group (e.g. patients with BRAF mutations) minus that in biomarker-negative group (e.g. patients with wt-BRAF). The HRs or RDs from different studies were meta-analyzed by using the random-effects (DerSimonian-Laird) model as appropriate.[21, 22] The statistical heterogeneity among the studies was assessed by the Cochran's Q-test and the I2 statistic.[21, 23] A p value ��0.10 for the Cochran's http://www.selleckchem.com/products/gsk1120212-jtp-74057.html Q-test or an I2?��?50% was suggestive of significant between-study heterogeneity. For the main effect meta-analyses on the primary outcomes that did not reach statistical significance, power was calculated according to the following formula: , where is the critical value of Z associated with significance level �� (for ��?=?0.05, ) and is the summary effect size divided by its variance.[24] If the power is low, e.g.