Dr. Panageas' main biostatistical research interests involve the analysis of cluster correlated data primarily in the context of volume-outcome studies (with the Health Outcomes Research Group), and she has recently been awarded an R21 grant to study this further. The primary focus of this research is to develop methods and software that will account for the correlation among patient outcomes within both hospital and surgeon in a non-nested manner. She is investigating statistical methods that are appropriate for the analysis of cross-classified data both with a binary endpoint as well as a survival endpoint. This scenario is common in studies evaluating procedure volume and surgical outcomes.
Other methodologic research areas involve developing novel phase II clinical trial designs for oncologic and ordinal endpoints as well as evaluating the effects of interval censored data in phase II clinical trials with progression-free survival as a primary endpoint. Dr Panageas is also working on a project evaluating patterns and outcomes of adjuvant chemotherapy in women 65 and older with hormone receptor negative breast cancer using the SEER-Medicare linked database.
Dr. Panageas is involved in collaborative work with the Clinical Immunology, Breast, Leukemia, and Neurology Services. She has been working with investigators of these services to design and analyze prospective and retrospective studies. She continues to serve as the primary statistician for the NIH program project entitled Biological Approaches to the Treatment of Cancer (PI, Alan Houghton).
Selected Bibiography:
1. Begg MD, Panageas KS. Interval estimation of the common odds ratio from k(2x2) tables under cluster sampling. Statistics in Medicine 1999;18:1087-1100.
2. Mazumdar M, Fazzari M, Panageas KS. A standardization method to adjust for the effect of patient selection in phase II clinical trials. Statistics in Medicine 2001;20: 883-892.
3. Panageas KS, Smith A, Gonen M, Chapman PB. An optimal two‑stage phase II design utilizing complete and partial response information separately. Controlled Clinical Trials 2002;23: 355-366.
4. Satagopan JM, Panageas KS. A statistical perspective on gene expression data analysis. Statistics in Medicine 2003;22:482-499.
5. Panageas KS, Schrag D, Riedel E, Bach PB, Begg CB. The effect of clustering on the association of procedure volume and surgical outcomes. Annals of Internal Medicine 2003;139:658-65.
