Sylvia K. Plevritis, PhD

Postdoctoral Advisees

• Sarah Geneser, Peng Qiu

Web Site Links

• http://rsl.stanford.edu/plevritis

Research Interests

My research program focuses on computational modeling of cancer biology and cancer outcomes. We develop stochastic models of the natural history of cancer based on clinical research data. We estimate population-level outcomes under differing screening and treatment interventions. We also analyze genomic and proteomic cancer data in order to identify molecular networks that are perturbed in cancer initiation and progression and relate these perturbations to patient outcomes.

Publications

• Effects of Mammography Screening Under Different Screening Schedules: Model Estimates of Potential Benefits and Harms. Mandelblatt JS,  Cronin KA, Bailey S, Berry DA, de Koning HJ, Draisma G, Huang H, Lee SJ, Munsell M, Plevritis SK, Ravdin P, Schechter CB, Sigal B, Stoto MA, Stout NK, van Ravesteyn NT, Venier J, Zelen M, Feuer EJ.  Ann Intern Med.  2009; 151 (10): 738-747
• A pluripotency signature predicts histologic transformation and influences survival in follicular lymphoma patients. Gentles AJ,  Alizadeh AA, Lee SI, Myklebust JH, Shachaf CM, Shahbaba B, Levy R, Koller D, Plevritis SK.  Blood.  2009; 114 (15): 3158-66
• Modeling the transition of lung cancer from early to advanced stage. Pashkevich MA,  Sigal BM, Plevritis SK.  Cancer Causes Control.  2009; 20 (9): 1559-69
• Simultaneous class discovery and classification of microarray data using spectral analysis. Qiu P,  Plevritis SK.  J Comput Biol.  2009; 16 (7): 935-44
• Fast calculation of pairwise mutual information for gene regulatory network reconstruction. Qiu P,  Gentles AJ, Plevritis SK.  Comput Methods Programs Biomed.  2009; 94 (2): 177-80
• Ly6d marks the earliest stage of B-cell specification and identifies the branchpoint between B-cell and T-cell development. Inlay MA,  Bhattacharya D, Sahoo D, Serwold T, Seita J, Karsunky H, Plevritis SK, Dill DL, Weissman IL.  Genes Dev.  2009; 23 (20): 2376-81
• Genomic and proteomic analysis reveals a threshold level of MYC required for tumor maintenance. Shachaf CM,  Gentles AJ, Elchuri S, Sahoo D, Soen Y, Sharpe O, Perez OD, Chang M, Mitchel D, Robinson WH, Dill D, Nolan GP, Plevritis SK, Felsher DW.  Cancer Res.  2008; 68 (13): 5132-42
• Ductal pattern enhancement on magnetic resonance imaging of the breast due to ductal lavage. Ghanouni P,  Kurian AW, Margolis D, Hartman AR, Mills MA, Plevritis SK, Ford JM, Daniel BL.  Breast J.  2007 May-Jun; 13 (3): 281-6
• A natural history model of stage progression applied to breast cancer. Plevritis SK,  Salzman P, Sigal BM, Glynn PW.  Stat Med.  2007; 26 (3): 581-95
• Extracting binary signals from microarray time-course data. Sahoo D,  Dill DL, Tibshirani R, Plevritis SK.  Nucleic Acids Res.  2007; 35 (11): 3705-12
• Cost-effectiveness of screening BRCA1/2 mutation carriers with breast magnetic resonance imaging. Plevritis SK,  Kurian AW, Sigal BM, Daniel BL, Ikeda DM, Stockdale FE, Garber AM.  JAMA.  2006; 295 (20): 2374-84
• A stochastic simulation model of U.S. breast cancer mortality trends from 1975 to 2000. Plevritis SK,  Sigal BM, Salzman P, Rosenberg J, Glynn P.  J Natl Cancer Inst Monogr.  2006; (36): 86-95
• Effect of screening and adjuvant therapy on mortality from breast cancer. Berry DA,  Cronin KA, Plevritis SK, Fryback DG, Clarke L, Zelen M, Mandelblatt JS, Yakovlev AY, Habbema JD, Feuer EJ.  N Engl J Med.  2005; 353 (17): 1784-92
• Decision analysis and simulation modeling for evaluating diagnostic tests on the basis of patient outcomes. Plevritis SK,  AJR Am J Roentgenol.  2005; 185 (3): 581-90
• The effect of age, race, tumor size, tumor grade, and disease stage on invasive ductal breast cancer survival in the U.S. SEER database. Rosenberg J,  Chia YL, Plevritis S.  Breast Cancer Res Treat.  2005; 89 (1): 47-54
• Simulation-based parameter estimation for complex models: a breast cancer natural history modelling illustration. Chia YL,  Salzman P, Plevritis SK, Glynn PW.  Stat Methods Med Res.  2004; 13 (6): 507-24
• Breast magnetic resonance image screening and ductal lavage in women at high genetic risk for breast carcinoma. Hartman AR,  Daniel BL, Kurian AW, Mills MA, Nowels KW, Dirbas FM, Kingham KE, Chun NM, Herfkens RJ, Ford JM, Plevritis SK.  Cancer.  2004; 100 (3): 479-89
• Spectral extrapolation of spatially bounded images [MRI application]. Plevritis SK,  Macovski A.  IEEE Trans Med Imaging.  1995; 14 (3): 487-97