Camelia Sima, MD, MS

Assistant Attending Biostatistician
Office Phone:
646-735-8107
E-mail:
simac@mskcc.org
Education:
University of Medicine Bucharest, University of Michigan

Current Research Interests

Since joining the Biostatistics Service in 2006, Cami Sima has collaborated with researchers in the health outcomes, epidemiology and clinical services. Currently, her primary clinical collaborations are in the thoracic oncology, thoracic surgery and head and neck areas. She has been working with investigators from these groups on the design and analysis of prospective and retrospective studies, with a focus on evaluating treatment strategies, exploring various biomarkers, and developing prediction and risk models. Dr. Sima's independent research interests are primarily motivated by her ongoing collaboration with the health-outcomes group. Population-based observational data sources (such as SEER-Medicare, State cancer registries/Medicaid linked data, or National Cancer Center Network) are rich resources for building evidence-based knowledge on the effectiveness of medications, devices and other relevant interventions. However, their utility is limited by inherent selection bias, non-measured confounders and non-ignorable missing data. Dr. Sima is interested in applying and extending causal inference methods such as instrumental variables and quasi-experimental designs to facilitate integrated analyses of observational datasets. She has been working with Drs. Schrag and Panageas in developing methods to characterize patterns of chemotherapy diffusion in the USA using the SEER-Medicare linked registries.

Publications by Camelia Sima

Oxnard GR, Arcila ME, Sima CS, Riely GJ, Chmielecki J, Kris MG, Pao W, Ladanyi M, Miller VA. Acquired resistance to EGFR tyrosine kinase inhibitors in EGFR-mutant lung cancer: distinct natural history of patients with tumors harboring the T790M mutation. Clinical Cancer Research. 2011 Mar 15;17(6):1616-22.

Sima CS, Panageas KS, Schrag D. Cancer screening among patients with advanced cancer. Journal of the American Medical Association (JAMA) 2010: 304 (14), pp. 1584-1591.

Sima CS, Panageas KS, Heller G, Schrag D. Analytical strategies for characterizing chemotherapy diffusion with patient-level population-based data. Applied Health Economics and Health Policy 2010: 8 (1), pp. 37-51

Sima CS, Jarnagin WR, Fong Y, Elkin E, Fischer M, Wuest D, D'Angelica M, DeMatteo RP, Blumgart LH, Gönen M. Predicting the risk of perioperative transfusion for patients undergoing elective hepatectomy. Ann Surg. 2009 Dec;250(6):914-21.

Schaubel DE, Wolfe RA, Sima CS, Merion RM. Estimating the effect of a time-dependent treatment by levels of an internal time-dependent covariate: application to the contrast between liver wait-list and post-transplant mortality. Journal of the American Statistical Association (JASA). 2009 Mar; 104 (485): 49-59