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Meta-analyses are popular tools to summarize the results of publications. Prognostic performances of a marker are usually summarized by meta-analyses of survival curves or hazard ratios. These approaches may detect a difference in survival according to the marker but do not allow evaluation of its prognostic capacity. Time-dependent receiver operating characteristic curves evaluate the ability of a marker to predict time-to-event. In this article, we describe an adaptation of time-dependent summary receiver operating characteristic curves from published survival curves. To achieve this goal, we modeled the marker and the time-to-event distributions using non-linear mixed models. First, we applied this methodology to individual data in kidney transplantation presented as aggregated data, in order to validate the method. Second, we re-analyzed a published meta-analysis, which focused on the capacity of KI-67 to predict the overall survival of patients with breast cancer., (© The Author(s) 2012.)

In rheumatoid arthritis (RA) there are currently no good indicators to predict a clinical response to rituximab. The purpose of this study was to monitor and determine the role of peripheral blood cytokine profiling in differentiating between a good versus poor response to rituximab in RA. Blood samples were collected at baseline and at 3 months from 46 RA patients who were treated with rituximab. Responders are defined by the presence of three of four American College of Rheumatology criteria: ≥ 20% decrease in C-reactive protein, visual analogical score of disease activity, erythrocyte sedimentation rate and improvement of the disease activity score (28) (four values) by ≥ 1·2 obtained at 3 months. Twelve cytokines were measured from serum collected on days 0 and 90 by proteomic array, including interleukin-6 (IL-6), tumour necrosis factor-α, IL-1a, IL-1b, IL-2, IL-8, interferon-γ, IL-4, IL-10, monocyte chemoattractant protein-1, epidermal growth factor and vascular growth factor. We showed that C-reactive protein and IL-6 levels decrease significantly at 3 months in the responder group compared with baseline. At day 90 we identified a cytokine profile which differentiates responders and non-responders. High serum levels of two proinflammatory cytokines, monocyte chemoattractant protein-1 and epidermal growth factor, were significantly higher in the responder group at day 90 compared with non-responders. However, we were not able to identify a baseline cytokine profile predictive of a good response at 3 months. These findings suggest that cytokine profiling by proteomic analysis may be a promising tool for monitoring rituximab and may help in the future to identify responder RA patients. [ABSTRACT FROM AUTHOR]

In rheumatoid arthritis (RA) there are currently no useful indicators to predict a clinical response to tumour necrosis factor-α (TNF-α) blockade. The purpose of this study was to determine the role of peripheral blood cytokine profiling in differentiating between a good versus poor response to etanercept in RA. Peripheral blood samples were collected at baseline and at 3 months from 33 patients with active disease who were treated twice weekly by etanercept therapy. Responders are defined by the presence of three of four American College of Rheumatology criteria: ≥20% decrease in C-reactive protein (CRP), visual analogue score of disease activity, erythrocyte sedimentation rate and improvement of the disease activity score (28; four values) by ≥1·2 obtained at 3 months. Twelve cytokines were measured from serum collected on days 0 and 90 by proteomic array (protein biochip array, Investigator Evidence, Randox France), including interleukin (IL)-6, TNF-α, IL-1a, IL-1b, IL-2, IL-8, interferon-γ, IL-4, IL-10, monocyte chemoattractant protein (MCP)-1, epidermal growth factor (EGF) and vascular endothelium growth factor. Our results showed that high serum levels of MCP-1 and EGF were associated with a response to etanercept. In addition, the increase of two combined parameters CRP and EGF was predictive of a response to etanercept treatment at 3 months (sensitivity: 87·5% and specificity: 75%, accuracy: 84·4%). These findings suggest that cytokine profiling by proteomic analysis before treatment initiation may help to identify a responder patient to TNF-α blocking agents in RA. [ABSTRACT FROM AUTHOR]