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 DCTD: BIOMETRIC RESEARCH PROGRAM

REPRINTS
1. A paradigm for class prediction using gene expression profiles
Michael D. Radmacher, Lisa M. McShane, and Richard Simon
Journal of Computational Biology 9:505-511, 2002.
2. Methods for assessing reproducibility of clustering patterns observed in analyses of microarray data
Lisa M. McShane, Michael D. Radmacher, Boris Freidlin, Ren Yu, Ming-Chung Li, and Richard Simon
Bioinformatics 18:1462-1469, 2002.
3. Controlling the number of false discoveries:Application to high-dimensional genomic data
Edward L. Korn, James F. Troendle, Lisa M. McShane, and Richard Simon
Journal of Statistical Planning and Inference 124:379-398, 2004.
4. Design of studies using DNA microarrays
Richard Simon, Michael D. Radmacher, and Kevin Dobbin
Genetic Epidemiology 23:21-36, 2002.
5. Bioinformatics and Whole Genome Technologies
Richard Simon
6. Comparison of Microarray Design
Kevin Dobbin and Richard Simon
Supplement
7. BRB Array-Tools Users Guide (version 3.2)
Richard Simon and Amy Peng Lam
8. Statistical design of reverse dye microarrays
Kevin Dobbin, Joanna Shih, and Richard Simon
Bioinformatics 19: 803-10, 2003.
Supplement
9. Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification
Richard Simon, Michael D. Radmacher, Kevin Dobbin, and Lisa M. McShane
Journal of the National Cancer Institute 95:14-18, 2003.
Supplement
10. Experimental Design of DNA Microarray Experiments
Richard Simon and Kevin Dobbin
Biotechniques 34: 1-5, 2002.
11. Phase I Clinical Trial Design
L. V. Rubinstein and R. M. Simon
12. Clinical Trial Designs for Therapeutic Vaccine Studies
Richard Simon
Published as Chapter 34, pp519-525, Handbook of Cancer Vaccines, MM Morse, TM Clay, HK Lyerly (eds), Humana Press, 2004.
13. A random variance model for differential gene detection in small sample microarray experiments
George Wright and Richard Simon
Bioinformatics 19: 2448-55, 2003.
Supplement and Tables & Figures
14. Using DNA Microarrays For Diagnostic and Prognostic Prediction
Richard Simon
Expert Review of Molecular Diagnostics 3(5) 587-595, 2003.
15. Statistical issues in the design and analysis of gene expression microarray studies of animal models
Lisa Mcshane, Joanna Shih, and Aleksandra Michalowska
Journal of Mammary Gland Biology and Neoplasia 8, 359-374, 2003.
16. Questions and Answers on Design of Dual Label Microarrays
Kevin Dobbin, Joanna Shih, and Richard Simon
Journal of the National Cancer Institute 95, 1362-1369, 2003.
17. Diagnostic and prognostic prediction using gene expression profiles in high-dimensional microarray data
Richard Simon
British J of Cancer 89:1599-1604, 2003.
18. Supervised analysis when the number of candidate features (p) greatly exceeds the number of cases (n)
Richard Simon
Association of Computing Machinery, SIGKDD Explorations 5(2) 31-36, 2003.
19. Sample Size Determination in Microarray Experiments for Class Comparison and Prognostic Classification
Kevin Dobbin and Richard Simon
Biostatistics, 8, 107-17, 2007.
Supplement
20. On the efficiency of targeted clinical trials
Aboubakar Maitournam and Richard Simon
Statistics in Medicine 24:329-339, 2005.
Supplement
21. Evaluating the efficiency of targeted designs for randomized clinical trials
Richard Simon and Aboubakar Maitournam
Clinical Cancer Research 10:6759-6763, 2005.
Supplement and Correction (Clinical Cancer Research 12:3229, 2006)
22. Experimental Design
Kevin Dobbin and Richard Simon
Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics. John Wiley and Sons, New York.
23. Guidelines for the Design of Clinical Studies for Development and Validation of Therapeutically Relevant Biomarkers and Biomarker Based Classification Systems
Richard Simon
to appear in Biomarkers in Breast Cancer, DF Hayes & G Gasparini (eds)
24. When is a Genomic Classifier Ready for Prime Time
Richard Simon
Nature Clinical Practice Oncology 1:4-5, 2004.
25. An agenda for Clinical Trials: clinical trials in genomic era
Richard Simon
Clinical Trials 1:468-470, 2004.
26. Characterizing dye bias in microarray experiments
Dobbin,K.K., Kawasaki, E.S., Petersen, D.W., and Simon, R.M.
Bioinformatics, 21, 2430-2437, 2005.
Supplement1, Supplement2
27. Estimating the number of rate limiting genomic changes for human breast cancer
Xinan Zhang and Richard Simon
Breast Cancer Research and Treatment 2005;91:121-124
Supplement
28. Bioinformatics in Cancer Therapeutics - Hype or Hope?
Richard Simon
Nature Clinical Practice Oncology 2:223, 2005.
29. BRB Array-Tools Users Guide (version 3.3)
Richard Simon and Amy Peng Lam
30. Prediction Error Estimation: A Comparison of Resampling Methods
Molinaro AM, Simon R, Pfeiffer RM.
31. Development and Validation of Therapeutically Relevant Multi-Gene Biomarker Classifiers
Richard Simon
Journal of the National Cancer Institute, Vol 97, No. 12, 866-867, 2005.
32. Appropriateness of some resampling-based inference procedures for assessing performance of prognostic classifiers derived from microarray data
Lusa L, McShane LM, Radmacher MD, Shih JH, Wright GW, and Simon R.
Statistics in Medicine 26:1102-13, 2007
33. Road map for developing and validating therapeutically relevant genomic classifiers
Richard Simon
Journal of Clinical Oncology Vol 23, No.29, 2005.
34. Designing prospective clinical pharmacogenomic(PG) trials: meeting report on drug development strategies to enhance therapeutic decision making
WL Trepicchio, D Essayan, ST Hall, G Schechter, Z Tezak, SJ Wang, D Weinreich and R Simon.
The Pharmacogenomics Journal Vol 6:89-94 2006.
35. Development and validation of biomarker classifiers for treatment selection
Richard Simon
Journal of Statistical Planning & Inference 138:308-320, 2008.
36. Validation of pharmacogenomic biomarker classifiers for treatment selection
Richard Simon
To appear in Disease Markers 21 1-8, 2005.
37. An evaluation of randomized discontinuation design
Boris Freidlin & Richard Simon
Journal of Clinical Oncology 23, 5094-5098.
38. Adaptive signature design: An adaptive clinical trial design for generating and prospectively testing a gene expression signature for sensitive patients
Boris Freidlin & Richard Simon
Clinical Cancer Research 11:7872-7878.
39. Bias in error estimation when using cross-validation for model selection
Sudhir Varma & Richard Simon
BMC Bioinformatics 7:91, 2006.
40. On estimating diagnostic accuracy with multiple raters and partial gold standard evaluation
Paul S. Albert and Lori E. Dodd
under review at the Journal of the American Statistical Association.
41. Imputation approaches for estimating diagnostic accuracy for multiple tests from partially verified designs
Paul S. Albert
under review at Biometrics
42. Sample size planning for developing classifiers using high dimensional data
Kevin Dobbin and Richard Simon
Biostatistics 8:101-117, 2007.
43. Sample size determination in microarray experiments for class comparison and prognostic classification
Kevin Dobbin and Richard Simon
Biostatistics 6:27-38, January 2005.
44. Use of genomic signatures in therapeutics development in oncology and other diseases
Richard Simon and S-J Wang
The Pharmacogenomics Journal 6:166-173, 2006.
45. A checklist for evaluating reports of expression profiling for treatment selection
Richard Simon
Clinical Advances in Hematology & Oncology 4:219-224, 2006.
46. BRB Array-Tools Users Guide (version 3.4)
Richard Simon and Amy Peng Lam
47. Sample Size Planning for Bayesian Randomized Clinical Trials
Richard Simon
Statistical Science 15:103-105, 2000.
48. Development and validation of therapeutically relevant predictive classifiers using gene expression profiling
Richard Simon
Journal of the National Cancer Institute 98:1169-71, 2006.
49. How large a training set is needed to develop a classifier for microarray data?
Kevin K. Dobbin, Yingdong Zhao, and Richard M. Simon
Clinical Cancer Research 14:108-114, 2008
Supplement and Correction
50. The Norton-Simon hypothesis: designing more effective and less toxic chemotherapeutic regimens
Richard Simon and Larry Norton
Nature Clinical Practice Oncology 3(8):406-7, 2006
51. Clinical Trial Designs for Therapeutic Cancer Vaccines
Richard Simon
Cancer Treatment Research 123:9-350, 2005.
52. Identification of Pharmacogenomic Biomarker Classifiers in Cancer Drug Development
Richard Simon
To appear as a chapter in Pharmacogenomics, Anticancer Drug Discovery and Response, (F Innocenti editor), Humana Press.
53. Biomarker Adaptive Threshold Design: A Procedure for Evaluating Treatment with Possible Biomarker-defined Subset Effect
Wenyu Jiang, Boris Freidlin and Richard Simon
Journal on National Cancer Institute 99:1036-43, 2007.
54. Critical Review of Published Microarray Studies for Cancer Outcome and Guidelines on Statistical Analysis and Reporting
Alain Dupuy and Richard Simon
Journal of the National Cancer Institute 99:147-157, 2007.
55. A comparison of bootstrap methods and an adjusted bootstrap approach for estimating prediction error in microarray classification and Supplement
Wenyu Jiang and Richard Simon
Submitted to Statistics in Medicine
56. Calculating Confidence Intervals for Prediction Error in Microarray Classification Using Resampling and Supplement
Wenyu Jiang, Sudhir Varma and Richard Simon
Submitted to publication
57. An Investigation of Two Multivariate Permutation Methods for Controlling the False Discovery Proportion
Korn EL, Li MC, Mcshane LM and Simon R.
Statistics in Medicine 26:4428-40, 2007.
58. Design Issues of Randomized Phase II Trials and a Proposal for Phase II Screening Trials
Lawrence V. Rubinstein, Edward L. Korn, Boris Freidlin, Sally Hunsberger, S. Percy Ivy, and Malcolm A. Smith
Journal of Clinical Oncology 23(28):7199-7206, 2005.
59. Analysis of Gene Expression Data Using BRB-Array Tools
Richard Simon, Amy Lam, Ming-Chung Li, Michael Ngan, Supriya Menenzes, Yingdong Zhao
Cancer Informatics 2:11-17, 2007.
60. Questions and Answers on Design of Dual-Label Microarrays for Identifying Differentially Expressed Genes
Kevin Dobbin,Joanna H.Shih, Richard Simon
Journal of the National Cancer Institute 95:1362-1369, 2003.
61. Validation of pharmacogenomic biomarker classifiers for treatment selection
Richard Simon
Cancer Biomarkers 2:89-96,2006.
62. Accelerated Titration Designs
Janet Dancey, Boris Freidlin and Larry Rubinstein
Statistical Methods for Dose-Finding Experiments, S. Chevret, ed., John Wiley & Sons, 2006.
63. Random Effects Modeling Approaches for Estimating ROC Curves from Repeated Ordinal Tests without a Gold Standard
Paul Albert
In press at Biometrics (2007).
64. Modeling Longitudinal Biomarker Data With Multiple Assays Which Have Different Known Detection Limits
Paul Albert
Revised for Biometrics (2007).
65. Panel Discussion on Bayesian Methods in Clinical Trials
Richard Simon
FDA-NIH Conference on Bayesian Methods in Clinical Trials, Clinical Trials 2:352-58, 2005.
66. Bayesian Analysis for Longitudinal Semicontinuous Data
Pulak Ghosh and Paul Albert
Submitted for publication
67. Use of Predictive Biomarker Classifiers in the Design of Pivotal Clinical Trials
Richard Simon
To appear as a Chapter in Pharmacogenomics & Personalized Medicine, (N Cohen, editor).
68. New challenges for 21st century clinical trials
Richard Simon
Clinical Trials 4:167-169,2007
69. BRB Array-Tools Users Guide (version 3.6)
Richard Simon and Amy Peng Lam
70. Interpretation of Genomic Data: Questions and Answers
Richard Simon
Seminars in Hematology 45:196-204, 2008.
71. Microarray based expression profiling and informatics
Richard Simon
Current Opinion in Biotechnology 19:26-29, 2008.
72. Lost in Translation: Problems and Pitfalls in Translating Laboratory Observations to Clinical Utility
Richard Simon
To appear in European Journal of Cancer.
73. Using Genomics in Clinical Trial Design
Richard Simon
Clinical Cancer Research 14:5984-93, 2008.
74. Designs and Adaptive Analysis Plans for Pivotal Clinical Trials of Therapeutics and Companion Diagnostics
Richard Simon
Expert Opinion in Medical Diagnostics, 2:721-29, 2008.
75. Drug and Pharmacodiagnostic Co-Development: Statistical Considerations
Richard Simon
To appear in Developing Molecular Diagnostics for Cancer (Winther & Jorgensen eds).
76. Gene Set Expression Comparison kit for BRB-ArrayTools
Xiaojiang Xu, Yingdong Zhao and Richard Simon
Bioinformatics 24(1):137-139, 2008.
77. Use of Partial Surrogate Endpoints in Integrated Phase II/III Designs
Sally Hunsberger, Yingdong Zhao and Richard Simon
Clinical Cancer research 15:5950-5955, 2010.
78. Tumor Markers: A new standard of breast cancer care
Bob Carlson
Biotechnology Healthcare, May/June 2008.
79. BRB Array-Tools Users Guide (version 4.1) and Chinese translation
Richard Simon and BRB-ArrayTools Development Team
Translated by YU Jian, MS in Bioinformatics, Tongji University and Shanghai Center for Bioinformation Technology. Email: yujian@scbit.org.
80. A Class Comparison Method with Filtering Enhanced Variable Selection for High-Dimensional Data Sets
Lara Lusa, Edward L. Korn, and Lisa M. McShane
Statistics in Medicine 27:5834-49, 2008.
81. On estimating the relationship between longitudinal measurements and time-to-event data using a simple two-stage procedure
Paul Albert and Joanna Shih
82. Accelerated titration designs
Janet Dancey, Boris Freidlin, and Larry Rubinstein
in Statistical Methods for Dose-Finding Experiments, Edited by S. Chevret, John Wiley & Sons, Ltd., 2006.
83. Use of Archived Specimens in Evaluation of Prognostic and Predictive Biomarkers
Richard M. Simon, Soonmyung Paik, Daniel F. Hayes
Journal of National Cancer Institute 101:1446-1452, 2009.
84. Analysis of DNA microarray expression data
Richard Simon
Clinical Haematology 22:271-282, 2009.
85. Advances in Clinical Trial Designs for Predictive Biomarker Discovery and Validation
Richard Simon
Current Breast Cancer Reports 1:216-221, 2009.
86. Questioning the utility of pooling samples in microarray experiments with cell lines. International Journal of Biological Markers
Lusa L, Cappelletti V, Gariboldi M, Ferrario C, Cecco LD, Reid JF, Toffanin S, Gallus G, McShane LM, Diadone MG, Pierotti MA.
International Journal of Biological Markers, 21(2):67-73, 2006.
87. Challenges in projecting clustering results across gene expression profiling data sets.
Lusa L, McShane LM, Reid JF, Cecco LD, Ambrogi F, Biganzoli E, Gariboldi M, Pierotti MA.
Journal of the National Cancer Institute, 99(22):1715-1723, 2007.
88. Effective incorporation of biomarkers into phase II trials.
McShane LM, Hunsberger S, Adjei AA.
Clinical Cancer Research, 15(6): 1898-1905, 2009.
89. A perspective on challenges and issues in biomarker development and drug and biomarker codevelopment.
Taube SE, Clark GM, Dancey JE, McShane LM, Sigman CC, Gutman SI.
Journal of the National Cancer Institute, 101: 1453-1463, 2009.
90. Randomized clinical trials with biomarkers: Design issues.
Freidlin B, McShane LM, Korn EL.
Journal of the National Cancer Institute, 102(3): 152-160, 2010.
91. Gene Expression Based Prognostic Signatures in Lung Cancer: Ready for Clinical Use?
Subramanian J, Simon R.
Journal of the National Cancer Institute, 102(7):464-474, 2010.
92. Clinical trial designs for evaluating the medical utility of prognostic and predictive biomarkers in oncology
Simon R.
Personalized Medicine 7(1):33-47, 2010.
93. Design and Analysis of DNA Microarray Investigations
Simon RM, Korn EL, McShane LM, Radmacher MD, Wright GW, Zhao Y.
Springer, 2004.
94. What should physicians look for in evaluating prognostic gene-expression signatures?
Subramanian J. and Simon R.
Nature Reviews Clinical Oncology, 7:327-334, 2010.
95. The cross-Validated Adaptive Signature Design
Freidlin B, Jiang W, Simon R.
Clinical Cancer Research, 16(2):691-698, 2010.
96. Clinical trials for predictive medicine: new challenges and paradigms
Simon R.
Clinical Trials, Mar 25, 2010.
97. Optimally splitting cases for training and testing high dimensional classifiers
Dobbin K and Simon R.
BMC Medical Genomics 4:31, 2011.
Supplement
98. Translational research in oncology: key bottle necks and new paradigms.
Simon R.
Expert Rev. Mol. Med. Vol.12, e32, October, 2010.
99. Advances in Clinical Trial Designs for Predictive Biomarker Discovery and Validation.
Simon R.
Current Breast Cancer Reports 1:216-221, 2009.
100. Moving from correlative science to predictive oncology.
Simon R.
EPMA Journal 1:377-387, 2010.
101. Probabilistic classiers with high-dimensional data.
Kyung In Kim and Richard Simon
Biostatistics, 2010.
102. Gene expression deconvolution in clinical samples.
Yingdong Zhao and Richard Simon
Genome Medicine 2:93, 2010.
103. Development and validation of biomarker classifiers for treatment selection.
Richard Simon
Journal of Statistical Planning and Inference 138(2):308-20, 2008.
104. Using cross-validation to evaluate predictive accuracy of survival risk classifiers based on high-dimensional data
Richard Simon, Jyothi Subramanian, Ming-Chung Li and Supriya Menezes
Briefings in Bioinformatics, 2011.
105. An evaluation of resampling methods for assessment of survival risk prediction in high-dimensional settings
Jyothi Subramanian and Richard Simon
Statistics in Medicine 30:642-653, 2011.
106. Genomic biomarkers in predictive medicine. An interim analysis
Richard Simon
EMBO Molecular Medicine, 3:1-7, 2011.
107. Adaptive Clinical Trial Designs for Simultaneous Testing of Matched Diagnostics and Therapeutics
Howard I. Scher, Shelley Fuld Nasso, Eric H. Rubin, and Richard Simon
Clin Cancer Res.,17:6634-6640, 2011.
108. A two-stage Bayesian design for co-development of new drugs and companion diagnostics
Stella Karuri and Richard Simon
Statistics in Medicine 31:901-914, 2012.
109. How to develop treatments for biologically heterogeneous "diseases"
Richard Simon
Clinical Cancer Res 18:4001-4003, 2012.
110. Implementing personalized cancer genomics in clinical trials
Richard Simon and Sameek Roychowdhury
Nature Reviews: Drug Discovery 12:358-369, 2013.
111. Considerations for the successful co-development of targeted cancer therapies and companion diagnostics
Fridlyand J, Simon RM, Walrath JC, Roach N, Buller R, Schenkein DP, Flaherty KT, Allen JD, Sigal EV and Scher HI
Nature Reviews: Drug Discovery 12:743-755, 2013.
112. Clinical trials for precision oncology using next-generation sequencing
Richard Simon and Eric Polley
Personalized Medicine (2013) 10(5), 485-495
113. Overfitting in prediction models - Is it a problem only in high dimensions?
Jyothi Subramanian and Richard Simon
Contemporary Clinical Trials 36 (2013) 636-641
114. Identification of potential synthetic lethal genes to p53 using a computational biology approach
Xiaosheng Wang and Richard Simon
BMC Medical Genomics 2013, 6:30
115. Using passenger mutations to estimate the timing of driver mutations and identify mutator alterations
Ahrim Youn and Richard Simon
BMC Bioinformatics 2013, 14:363.
116. Stratification and Partial Ascertainment of Biomarker Value in Biomarker-Driven Clinical Trials
Richard Simon
Journal of Biopharmaceutical Statistics, 24:5, 1011-1021, 2014.
117. Using single cell sequencing data to model the evolutionary history of a tumor
Kyung In Kim and Richard Simon
BMC Bioinformatics 15:27, 2014.
118. The Role of Non-Randomized Trials in the Evaluation of Oncology Drugs
Richard Simon, Gideon Blumenthal, Mace L. Rothenberg, Josh Sommer, Samantha A. Roberts, Deborah K. Armstrong, Lisa M. LaVange, and Richard Pazdur
Clinical Pharm, doi: 10.1002/cpt.86, 2015.
119. Biomarker based clinical trial design
Richard Simon
Chin Clin Oncol 3(3):39, 2015.
120. Sensitivity, Specificity, PPV, and NPV for Predictive Biomarkers
Richard Simon
J Natl Cancer Inst (2015) 107(8): djv153
Supplement

Updated on March 31, 2016