Efficient and knowledgeable biostatistical support is crucial to the proper design and interpretation of research in the biomedical sciences. The principal objective of the Biostatistics Core will be to provide the Thyroid cancer investigators a centralized resource for statistical expertise. Statistical issues will be addressed at all levels of investigation: from the design of experiments, to the integration of data sources and maintenance of data quality, and from descriptions of modeling to inferential statements required for accurate dissemination. In support of this objective, the specific aims of the Biostatistics Core include: 1. To collaborate with project investigators in the formulation of hypotheses and hypotheses testing strategies for all mouse and cell line experiments, and in the design of prognostic/diagnostic, linkage, and micro-array studies. 2. To conduct and direct the statistical analysis of data generated by project investigators including: descriptive summary statistics, error modeling, experimental data inference and decision making, analysis and data preparation for linkage and microarray studies, and prognostic/diagnostic equation modeling and accuracy estimation. 3. To ensure that statistical principles associated with: modeling nuisance or block effects, minimizing inference errors (Type I and II error) by correcting for multiple comparisons and multiple measures, randomizing conditions properly, and decreasing measurement error are employed in all studies. 4. Provide data transfer, management, and integration services that ensure high integrity, security and investigator accessibility. 5. To collaborate with Core A (Clinical Data) and Core B (Mouse) directors to ensure the above principles are used in obtaining valid and reliable data from fully powered and unbiased study designs. 6. To coordinate the development and investigation of newer statistical methodologies, when needed, to directly support ongoing research.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Program Projects (P01)
Project #
Application #
Study Section
Special Emphasis Panel (ZCA1)
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Ohio State University
United States
Zip Code
Chakedis, Jeffery; Shirley, Lawrence A; Terando, Alicia M et al. (2018) Identification of the Thoracic Duct Using Indocyanine Green During Cervical Lymphadenectomy. Ann Surg Oncol 25:3711-3717
Saporito, Donika; Brock, Pamela; Hampel, Heather et al. (2018) Penetrance of a rare familial mutation predisposing to papillary thyroid cancer. Fam Cancer 17:431-434
Segkos, Konstantinos; Porter, Kyle; Senter, Leigha et al. (2018) Neck Ultrasound in Patients with Follicular Thyroid Carcinoma. Horm Cancer 9:433-439
Kotlarek, Marta; Kubiak, Anna; Czetwerty?ska, Ma?gorzata et al. (2018) The rs2910164 Genetic Variant of miR-146a-3p Is Associated with Increased Overall Mortality in Patients with Follicular Variant Papillary Thyroid Carcinoma. Int J Mol Sci 19:
Russart, Kathryn L G; Huk, Danielle; Nelson, Randy J et al. (2018) Elevated aggressive behavior in male mice with thyroid-specific Prkar1a and global Epac1 gene deletion. Horm Behav 98:121-129
Ashtekar, Amruta; Huk, Danielle; Magner, Alexa et al. (2018) Alterations in Sod2-Induced Oxidative Stress Affect Endocrine Cancer Progression. J Clin Endocrinol Metab 103:4135-4145
Smith, Iris Nira; Thacker, Stetson; Jaini, Ritika et al. (2018) Dynamics and structural stability effects of germline PTEN mutations associated with cancer versus autism phenotypes. J Biomol Struct Dyn :1-17
Feng, Fang; Yehia, Lamis; Ni, Ying et al. (2018) A Nonpump Function of Sodium Iodide Symporter in Thyroid Cancer via Cross-talk with PTEN Signaling. Cancer Res 78:6121-6133
Byrd, Victoria; Getz, Ted; Padmanabhan, Roshan et al. (2018) The microbiome in PTEN hamartoma tumor syndrome. Endocr Relat Cancer 25:233-243
Yehia, Lamis; Jindal, Supriya; Komar, Anton A et al. (2018) Non-canonical role of cancer-associated mutant SEC23B in the ribosome biogenesis pathway. Hum Mol Genet 27:3154-3164

Showing the most recent 10 out of 131 publications