Mayada Aljehani is a Cancer Epidemiologist at the Ellison Institute. Mayada is based in the Lee/Matasci Lab, but helps all Ellison Institute faculty and individual researchers through the lifecycle of their scientific projects with study design, data collection, statistical analysis and results dissemination. In addition to the internal pre-clinical research work with biologists to design and conduct biomarker & drug efficacy studies, Mayada collaborates with the Institute’s external research partners in investigating health economic disparities and their impact on patients and population outcomes. Mayada is also a Big Data Scientist Research Fellow with the Department of Veterans Affairs.
After completing her BS in mathematics in Saudi Arabia, she moved to California and received her MSPH in biostatistics and DrPH in epidemiology from Loma Linda University. Mayada conducted her dissertation thesis within the California Cancer Registry (CCR), where she focused on the assessment of the impact of tumor and patients’ characteristics on colon cancer survival in the state of California. Using CCR database, she demonstrated differential impact of Bevacizumab and Cetuximab depending on whether the primary tumor location was in the left or the right colon. She also showed that for patients with stage II colon cancer, in addition to the binary classification of low and high risk, inclusion of number and type of risk features was more informative for treatment response and patient prognosis. Published studies from her dissertation have been used to inform clinical support resources such as UpToDate.com.
After completing her BS in mathematics in Saudi Arabia, she moved to California and received her MSPH in biostatistics and DrPH in epidemiology from Loma Linda University. Mayada conducted her dissertation thesis within the California Cancer Registry (CCR), where she focused on the assessment of the impact of tumor and patients’ characteristics on colon cancer survival in the state of California. Using CCR database, she demonstrated differential impact of Bevacizumab and Cetuximab depending on whether the primary tumor location was in the left or the right colon. She also showed that for patients with stage II colon cancer, in addition to the binary classification of low and high risk, inclusion of number and type of risk features was more informative for treatment response and patient prognosis. Published studies from her dissertation have been used to inform clinical support resources such as UpToDate.com.