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1 Identifying biomarkers that predict survival and guide individualized therapy is urgently needed.
2 We hypothesized that changes in physiologic and radiographic parameters would predict survival .
3 Some recent reports suggest it may be used to predict survival .
4 Persistent endothelial activation and dysfunction predict survival in children admitted with severe malaria.
5 The ability of the staging systems to predict survival was assessed.
6 Other MHC class II genes were found to predict survival similarly.
7 Conclusions: RH and the development of new lesions may predict survival in metastatic ccRCC.
8 A Cox regression model was used to determine symptoms that could predict survival time.
9 The aim of this study was to determine whether pretreatment PET-CT could predict survival .
10 Preoperative CEA and overall stage predict survival by multivariate analysis.
11 Affordable serial measurements parallel the response to therapy and predict survival in HIV-associated PTB.
12 Univariable logistic regression was used to evaluate each parameter for its ability to predict survival .
13 Changes in alpha-fetoprotein after treatment did not predict survival .
14 Conclusions: This novel and simple prognostic tool could predict survival more accurately in patients with NSCLC.
15 Conclusions: We identified 4 risk groups to predict survival in previously treated patients with renal cell carcinoma.
16 Results: In a univariate analysis, genes were ranked on the basis of their ability to predict survival .
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