Tissue-based Genomics Augments Post-prostatectomy Risk Stratification in a Natural History Cohort of Intermediate- and High-Risk Men.

[1]  B. Trock,et al.  Utility of Risk Models in Decision Making After Radical Prostatectomy: Lessons from a Natural History Cohort of Intermediate- and High-Risk Men. , 2016, European urology.

[2]  Darby J. S. Thompson,et al.  Recalibration of genomic risk prediction models in prostate cancer to improve individual-level predictions. , 2015 .

[3]  M. Kattan,et al.  A genomic classifier improves prediction of metastatic disease within 5 years after surgery in node-negative high-risk prostate cancer patients managed by radical prostatectomy without adjuvant therapy. , 2015, European urology.

[4]  F. Feng,et al.  Genomic classifier identifies men with adverse pathology after radical prostatectomy who benefit from adjuvant radiation therapy. , 2015, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[5]  A. Vickers,et al.  Guidelines for reporting of statistics in European Urology. , 2015, European urology.

[6]  Anamaria Crisan,et al.  Combined value of validated clinical and genomic risk stratification tools for predicting prostate cancer mortality in a high-risk prostatectomy cohort. , 2015, European urology.

[7]  David C. Miller,et al.  Contemporary use of initial active surveillance among men in Michigan with low-risk prostate cancer. , 2015, European urology.

[8]  John W. Davis.  Novel commercially available genomic tests for prostate cancer: a roadmap to understanding their clinical impact , 2014, BJU international.

[9]  P. Febbo,et al.  A 17-gene assay to predict prostate cancer aggressiveness in the context of Gleason grade heterogeneity, tumor multifocality, and biopsy undersampling. , 2014, European urology.

[10]  F. Feng,et al.  Genomic Prostate Cancer Classifier Predicts Biochemical Failure and Metastases in Patients After Postoperative Radiation Therapy , 2014, International journal of radiation oncology, biology, physics.

[11]  Anirban P. Mitra,et al.  Validation of a genomic classifier that predicts metastasis following radical prostatectomy in an at risk patient population. , 2013, The Journal of urology.

[12]  Andrea Califano,et al.  A Molecular Signature Predictive of Indolent Prostate Cancer , 2013, Science Translational Medicine.

[13]  Anirban P. Mitra,et al.  Discovery and Validation of a Prostate Cancer Genomic Classifier that Predicts Early Metastasis Following Radical Prostatectomy , 2013, PloS one.

[14]  Stephen R. Piccolo,et al.  A single-sample microarray normalization method to facilitate personalized-medicine workflows. , 2012, Genomics.

[15]  Patrik Magnusson,et al.  American Journal of Epidemiology Practice of Epidemiology Risk Prediction Measures for Case-cohort and Nested Case-control Designs: an Application to Cardiovascular Disease , 2022 .

[16]  M. Cooperberg,et al.  The CAPRA‐S score , 2011, Cancer.

[17]  Brent A. Johnson,et al.  Protein‐coding and MicroRNA Biomarkers of Recurrence of Prostate Cancer Following Radical Prostatectomy , 2011, The American journal of pathology.

[18]  T. Golub,et al.  mRNA expression signature of Gleason grade predicts lethal prostate cancer. , 2011, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[19]  Helen E. Lockstone,et al.  Exon array data analysis using Affymetrix power tools and R statistical software , 2011, Briefings Bioinform..

[20]  B. Pang,et al.  Analysis of differentially expressed genes in LNCaP prostate cancer progression model. , 2011, Journal of andrology.

[21]  Misop Han,et al.  Predicting 15-year prostate cancer specific mortality after radical prostatectomy. , 2011, The Journal of urology.

[22]  C. Compton,et al.  TNM seventh edition: What's new, what's changed , 2010, Cancer.

[23]  David Boulware,et al.  A gene expression model of intrinsic tumor radiosensitivity: prediction of response and prognosis after chemoradiation. , 2009, International journal of radiation oncology, biology, physics.

[24]  Elena B. Elkin,et al.  Extensions to decision curve analysis, a novel method for evaluating diagnostic tests, prediction models and molecular markers , 2008, BMC Medical Informatics Decis. Mak..

[25]  Holly Janes,et al.  Pivotal Evaluation of the Accuracy of a Biomarker Used for Classification or Prediction: Standards for Study Design , 2008, Journal of the National Cancer Institute.

[26]  C. D. Savci-Heijink,et al.  Gene panel model predictive of outcome in men at high-risk of systemic progression and death from prostate cancer after radical retropubic prostatectomy. , 2008, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[27]  F. Monzon,et al.  Longitudinal analysis of androgen deprivation of prostate cancer cells identifies pathways to androgen independence , 2008, The Prostate.

[28]  M. Ringnér,et al.  Poor prognosis in carcinoma is associated with a gene expression signature of aberrant PTEN tumor suppressor pathway activity , 2007, Proceedings of the National Academy of Sciences.

[29]  L. Egevad,et al.  The 2005 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma , 2005, The American journal of surgical pathology.

[30]  W. Sauerbrei,et al.  REporting recommendations for tumor MARKer prognostic studies (REMARK) , 2005, Nature Clinical Practice Oncology.

[31]  T. Lumley,et al.  Time‐Dependent ROC Curves for Censored Survival Data and a Diagnostic Marker , 2000, Biometrics.

[32]  W E Barlow,et al.  Analysis of case-cohort designs. , 1999, Journal of clinical epidemiology.

[33]  D. Chan,et al.  Natural History of Progression After PSA Elevation Following Radical Prostatectomy , 1999 .

[34]  Robert Gray,et al.  A Proportional Hazards Model for the Subdistribution of a Competing Risk , 1999 .

[35]  T M Therneau,et al.  Computing the Cox Model for Case Cohort Designs , 1999, Lifetime data analysis.

[36]  W. Sauerbrei,et al.  Dangers of using "optimal" cutpoints in the evaluation of prognostic factors. , 1994, Journal of the National Cancer Institute.

[37]  Z. Ying,et al.  Cox Regression with Incomplete Covariate Measurements , 1993 .