Paul J. Catalano

Overview

Dr. Catalano's major interests involve research in methods for the analysis of multiple outcomes and repeated measures and their application to environmental dose-response modeling and quantitative risk assessment. In particular, he has developed models for the analysis of data from developmental and neurological toxicity studies in animals, where interest centers on characterization of the dose-response profile for a variety of adverse outcomes such as fetal death, a variety of developmental alterations, and lowered birth weight. In addition to providing valuable information on the quantitative relationship between exposure and adverse health effects, such models can be used to estimate a dose level corresponding to a specified arbitrary level of overall risk above background. These levels are useful in helping to understand risk to humans. The statistical analysis of data from such studies is complicated because the outcomes are composed of clusters of multivariate continuous and binary responses, requiring methods for repeated measures that incorporate multiple data types.

He and colleagues in the Department of Biostatistics have also conducted research on the role of experimental design (number of doses, dose spacings, etc.) in the estimation of low risk dose levels. Dr. Catalano is also involved in the development of computer software to implement some of the modeling algorithms that he and his colleagues have described. In addition, he is working with researchers at EPA and in the Department of Environmental Health at Harvard School of Public Health on methods for the analysis of multiple outcomes arising from neurotoxicity screening assays where, as in the developmental studies, multiplicity is an important problem.

Dr. Catalano is also involved in collaborative research in cancer through his work with the statistical centers of the Eastern Cooperative Oncology Group and the Cancer Care Outcomes Research and Surveillance Consortium (CanCORS) at the Dana-Farber Cancer Institute. He is the statistician for many phase II and phase III therapeutic clinical trials in colorectal and genito-urinary cancer. He is also involved in several laboratory-based and natural history studies to identify prognostic factors in human malignancies.