Current Research:
Dr. Gönen's clinical collaborations focus on surgical treatment of gastrointestinal and hepatobiliary cancers, including a series of studies evaluating the impact of blood transfusions on patient outcome as well as evaluating and improving colorectal cancer staging. He also has a long-standing collaboration with Nuclear Medicine which encompasses the development of Positron Emission Tomography (PET) in cancer diagnosis and prognosis. Most of Dr Gönen's methodological research originates from these collaborations, including building, assessing and comparing predictive models as well as the design and analysis of radiologic studies with clustered data. He recently published a book on the use of receiver operating characteristic (ROC) curves using SAS®. Dr. Gonen serves on the faculty of AACR/ASCO Vail Workshop on Method in Clinical Cancer Research and he is a member of NCI Subcommittee J (Population and Patient-Based Training). He is serving the American Statistical Association as the vice president of the New York Chapter (since 2004) and member of the committee on international relations (since 2006). He is also a member of the data and safety monitoring boards of two NIH-supported clinical trials.
Selected Bibliography:
- Gönen M, Panageas KS, Larson SM. Statistical issues in the analysis of diagnostic imaging experiments with multiple observations per patient. Radiology 2001;221:763-767.
- Gönen M, Hummer A, Zervoudakis A, Sullivan D, Fong Y, Banerjee D, Klimstra D, Cordon-Cardo C, Bertino J, Kemeny N. Thymidylate synthase expression in hepatic tumors is a predictor of survival and progression in patients with resectable metastatic colorectal cancer. Journal of Clinical Oncology 2003;21:406-412.
- Gönen M, Westfall PH, Johnson WO. Bayesian multiple testing for two-sample multivariate endpoints. Biometrics. 2003;59:76-82.
- Gönen M, Johnson WO, Lu Y, Westfall PH. A Bayesian two-sample t-test. The American Statistician 2005;59:252-257.
- Gönen M, Heller G. Concordance Probability and Discriminative Power of Proportional Hazards Regression. Biometrika 2005;92:965-970.
