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Dr. Tayob is a Member of the Faculty in the Department of Data Science at Dana-Farber Cancer Institute and the Department of Medicine at Harvard Medical School. Dr. Tayob obtained her undergraduate degree in Statistics from the University of Cape Town in South Africa and her Masters and PhD in Biostatistics from the University of Michigan. She did a postdoctoral fellowship in the Department of Biostatistics at The University of Texas MD Anderson Cancer Center and was an Assistant Professor in the same department prior to joining DFCI. Her research focus is in early detection of cancer, biomarker evaluation and survival analysis. Dr. Tayob collaborates with researchers in the Susan F. Smith Center for Women's Cancers. She is an active NIH-funded investigator.
Dr. Tayob is co-Director of the Biostatistics and Computational Biology Core of the DF/HCC Breast SPORE and the co-Lead of the Biostatistics Core of the DF/HCC Ovarian SPORE. She is an active collaborator on research projects with investigators in the Susan F. Smith Center for Women's Cancers. She is also co-investigator on multiple NIH funded projects studying the early detection of hepatocellular carcinoma (HCC) and is the PI of an NIH funded project to develop statistical methods to improve early detection of HCC. Dr. Tayob's current statistical methods research focuses on biomarker study design, evaluation and screening for early detection of cancer. Recent work includes developing statistical methods for evaluating a biomarker panel in a two-stage study with early termination for futility. Two-stage group sequential designs with early termination for futility are important and widely used in biomarker development studies because they allow us to conserve valuable sample specimens in the case of inadequate biomarker performance at interim analysis. A key focus of her research is the development of statistical methods that use multiple longitudinal biomarkers when screening for early detection of HCC. Patients with cirrhosis are at high risk for HCC and recommended to undergo regular six-month surveillance. She has an NIH funded project where the goal is to develop statistical methods that use biomarker information collected at the current screening visit, as well as prior screening visits, to improve the likelihood of early detection of HCC. These types of screening algorithms could potentially be used in other high-risk cancer populations that undergo surveillance with biomarkers. Dr. Tayob's doctoral research focused on developing statistical methods around the restricted mean survival, a clinically meaningful short-term outcome measure. Future research will explore the use of this measure in biomarker studies.
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