Current Research Interests
Dr. Alexia Iasonos’ expertise is in the design and analysis of clinical trials, primarily dose finding Phase I trials that are model based, as well as predictive modeling in surgical outcomes. Her methodological research is focused on evaluating Bayesian adaptive Phase I designs, specifically the Continual Reassessment Method (CRM). She has compared CRM with the standard 3+3 dose escalation scheme [Abstract] as part of a 2-year award from the Experimental Therapeutic Center of Memorial Sloan-Kettering to study dose finding algorithms. She has lead a team of programmers and data managers to create the infrastructure (software and a web interface) that facilitates clinical personnel in obtaining the dose allocation for CRM seamlessly. Her clinical collaborations focus on gynecologic malignancies. Her work with gynecologic oncologists and surgeons varies from exploring biomarkers to predicting survival outcomes. Most recently she has evaluated clinical endpoints for consolidation or maintenance trials given to patients in remission.
Alexia has previously worked with QoL outcomes as part of collaboration with Health Outcomes (HOGR) where the group analyzed patient reported outcomes and compared these with clinician symptom reporting using the National Cancer Institute common terminology criteria for adverse events. She has also worked with the Urology group in developing predictive models and nomograms that can be used pre-operatively to enable a more informed clinical decision-making process. She has been a statistical reviewer for the institutional Data and Safety Monitoring Committee for Phase I-II trials since 2006.
She is currently the primary statistician for the Gynecology service, Developmental Therapeutic Center and Quality Control Initiative at Memorial Sloan-Kettering. She is serving as a scientific reviewer on the institution’s Research Council and the ASCO Grants selection committee.
Publications by Alexia Iasonos
