Lost in translation: problems and pitfalls in translating laboratory observations to clinical utility.
暂无分享,去创建一个
[1] Daniel J Sargent,et al. Clinical trial designs for predictive marker validation in cancer treatment trials. , 2005, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[2] W. Hait. Translating Research into Clinical Practice: Deliberations from the American Association for Cancer Research , 2005, Clinical Cancer Research.
[3] R. Simon,et al. On the dynamics of breast tumor development in women carrying germline BRCA1 and BRCA2 mutations , 2007, International journal of cancer.
[4] Mari Paul,et al. Translational investigators: life sciences' application engineers , 2007, Nature Biotechnology.
[5] K R Hess,et al. Clinical trial design for microarray predictive marker discovery and assessment. , 2004, Annals of oncology : official journal of the European Society for Medical Oncology.
[6] Jeffrey S. Morris,et al. Serum proteomics profiling—a young technology begins to mature , 2005, Nature Biotechnology.
[7] Richard Simon,et al. When is a genomic classifier ready for prime time? , 2004, Nature Clinical Practice Oncology.
[8] L. Ein-Dor,et al. Thousands of samples are needed to generate a robust gene list for predicting outcome in cancer. , 2006, Proceedings of the National Academy of Sciences of the United States of America.
[9] R. Simon,et al. Development and evaluation of therapeutically relevant predictive classifiers using gene expression profiling. , 2006, Journal of the National Cancer Institute.
[10] Yudong D. He,et al. Gene expression profiling predicts clinical outcome of breast cancer , 2002, Nature.
[11] Xinan Zhang,et al. Estimating the number of rate limiting genomic changes for human breast cancer , 2005, Breast Cancer Research and Treatment.
[12] Stefan Michiels,et al. Prediction of cancer outcome with microarrays: a multiple random validation strategy , 2005, The Lancet.
[13] Yingdong Zhao,et al. How Large a Training Set is Needed to Develop a Classifier for Microarray Data? , 2008, Clinical Cancer Research.
[14] R Simon,et al. Statistical model to determine the relationship of response and survival in patients with advanced ovarian cancer treated with chemotherapy. , 1992, Journal of the National Cancer Institute.
[15] Geoffrey J McLachlan,et al. Selection bias in gene extraction on the basis of microarray gene-expression data , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[16] R. Simon,et al. Evaluating the Efficiency of Targeted Designs for Randomized Clinical Trials , 2004, Clinical Cancer Research.
[17] S. Paik. Development and clinical utility of a 21-gene recurrence score prognostic assay in patients with early breast cancer treated with tamoxifen. , 2007, The oncologist.
[18] Richard Simon,et al. Bias in error estimation when using cross-validation for model selection , 2006, BMC Bioinformatics.
[19] J. Minna,et al. The impact of epidermal-growth-factor-receptor mutations in response to lung-cancer therapy , 2004, Nature Clinical Practice Oncology.
[20] K. Coombes,et al. Microarrays: retracing steps , 2007, Nature Medicine.
[21] M. Eigen,et al. The Hypercycle: A principle of natural self-organization , 2009 .
[22] W. Hait. Sustaining the Clinical in Clinical Translational Research , 2006, Clinical Cancer Research.
[23] L. V. van't Veer,et al. Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer. , 2006, Journal of the National Cancer Institute.
[24] A. Nobel,et al. Concordance among Gene-Expression – Based Predictors for Breast Cancer , 2011 .
[25] Lajos Pusztai,et al. Clinical application of cDNA microarrays in oncology. , 2003, The oncologist.
[26] Marcel J. T. Reinders,et al. A comparison of univariate and multivariate gene selection techniques for classification of cancer datasets , 2006, BMC Bioinformatics.
[27] R. Simon,et al. Adaptive Signature Design: An Adaptive Clinical Trial Design for Generating and Prospectively Testing A Gene Expression Signature for Sensitive Patients , 2005, Clinical Cancer Research.
[28] Richard M. Simon,et al. A Paradigm for Class Prediction Using Gene Expression Profiles , 2003, J. Comput. Biol..
[29] R. Simon,et al. On the efficiency of targeted clinical trials , 2005, Statistics in medicine.
[30] George Y H Chi,et al. A method for testing a prespecified subgroup in clinical trials , 2007, Statistics in medicine.
[31] R. Simon. Bioinformatics in cancer therapeutics—hype or hope? , 2005, Nature Clinical Practice Oncology.
[32] R. Simon,et al. Biomarker-adaptive threshold design: a procedure for evaluating treatment with possible biomarker-defined subset effect. , 2007, Journal of the National Cancer Institute.
[33] S Michiels,et al. Prediction of cancer outcome with microarrays , 2005, The Lancet.
[34] A. Dupuy,et al. Critical review of published microarray studies for cancer outcome and guidelines on statistical analysis and reporting. , 2007, Journal of the National Cancer Institute.
[35] M. Radmacher,et al. Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification. , 2003, Journal of the National Cancer Institute.
[36] M. Cronin,et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. , 2004, The New England journal of medicine.
[37] Annette M. Molinaro,et al. Prediction error estimation: a comparison of resampling methods , 2005, Bioinform..
[38] R. Simon,et al. Use of genomic signatures in therapeutics development in oncology and other diseases , 2006, The Pharmacogenomics Journal.
[39] J. D. Miller. Finding clinical meaning in cancer data. , 2007, Journal of the National Cancer Institute.
[40] R. Simon,et al. Sample size planning for developing classifiers using high-dimensional DNA microarray data. , 2007, Biostatistics.