The Geisel School of Medicine Events Calendar
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Co-Sponsored by Department of Medical Education & Dartmouth Health Office of Research Operations.
Tasha R. Wyatt, PhD
Tasha R. Wyatt, PhD
Please join us for our April Implementation Science Works in Progress session with Caitlin Howe, PhD, Assistant Professor of Epidemiology. Dr. Howe's research focuses on toxic metal exposures and their impacts on maternal and child health, with a particular interest in effects on early life growth and cardiometabolic health.
Co-sponsored by Department of Medical Education & Dartmouth Health Office of Research Operations.
Tasha Wyatt, PhD
Tasha Wyatt, PhD
Geisel School of Medicine at Dartmouth
Guarini School of Graduate and Advanced Studies
Microbiology and Immunology
Graduate Program
THESIS DEFENSE
Alia Sajani
“Heterogeneity and plasticity of the naïve CD4+ T cell compartment”
Friday, April 12, 2024
9:00A.M.
Auditorium H (DH)
Zoom https://dartmouth.zoom.us/j/98751493800?pwd=RkVXRkxiTW82T3UwVFJBVlF2MGpoUT09
Meeting ID: 987 5149 3800
Passcode: Thesis
Advisors: Randolph Noelle and Mary Jo Turk
Guarini School of Graduate and Advanced Studies
Microbiology and Immunology
Graduate Program
THESIS DEFENSE
Alia Sajani
“Heterogeneity and plasticity of the naïve CD4+ T cell compartment”
Friday, April 12, 2024
9:00A.M.
Auditorium H (DH)
Zoom https://dartmouth.zoom.us/j/98751493800?pwd=RkVXRkxiTW82T3UwVFJBVlF2MGpoUT09
Meeting ID: 987 5149 3800
Passcode: Thesis
Advisors: Randolph Noelle and Mary Jo Turk
Geisel School of Medicine at Dartmouth
Guarini School of Graduate and Advanced Studies
Microbiology and Immunology
Graduate Seminar
"Regulation of the magnitude and duration of the immune response"
PRESENTED BY
Carla Rothlin, Ph.D.
PROFESSOR
Yale University
New Haven, CT
HOST: Alia Sajani
Friday, April 12, 2024
2:00 P.M.
Auditorium G (DHMC)
Guarini School of Graduate and Advanced Studies
Microbiology and Immunology
Graduate Seminar
"Regulation of the magnitude and duration of the immune response"
PRESENTED BY
Carla Rothlin, Ph.D.
PROFESSOR
Yale University
New Haven, CT
HOST: Alia Sajani
Friday, April 12, 2024
2:00 P.M.
Auditorium G (DHMC)
Newborn provider perspectives when asked by a mother to not share their infant’s prenatal substance exposure.
Colby Kearl, MD
Neonatal Fellow
Dartmouth Health Children’s
To view Grand Rounds at another time visit the following link: https://video.dartmouth-hitchcock.org/category/Grand+Rounds%3EPediatric/86113381
Colby Kearl, MD
Neonatal Fellow
Dartmouth Health Children’s
To view Grand Rounds at another time visit the following link: https://video.dartmouth-hitchcock.org/category/Grand+Rounds%3EPediatric/86113381
John R. Desjarlais
Executive Vice President,
Research & Chief Scientific Officer
Xencor
465 North Halstead Street, Suite 200
Pasadena, CA
Host: Tyler Curiel
“Bispecific antibodies to promote T cell signals 1 and 2 for the treatment of solid tumors”
Tuesday, April 9, 2024 @ 10AM
Auditorium G (DH Complex)
Or Via ZOOM
https://dartmouth.zoom.us/j/99411458598?pwd=TThlanExb1hkV2h1czNJcUxGVTFSdz09
MEETING ID: 994 1145 8598
PASSCODE: 343665
Executive Vice President,
Research & Chief Scientific Officer
Xencor
465 North Halstead Street, Suite 200
Pasadena, CA
Host: Tyler Curiel
“Bispecific antibodies to promote T cell signals 1 and 2 for the treatment of solid tumors”
Tuesday, April 9, 2024 @ 10AM
Auditorium G (DH Complex)
Or Via ZOOM
https://dartmouth.zoom.us/j/99411458598?pwd=TThlanExb1hkV2h1czNJcUxGVTFSdz09
MEETING ID: 994 1145 8598
PASSCODE: 343665
Auditorium E and Livestream
Topic: AI & Teaching in Neurology
Presented by: Erik Kobylarz, MD, PhD, Clinical Neurophysiology Fellowship Director, Intraoperative Neurophysiologic Monitoring Director, Dartmouth Hitchcock Medical Center and Thomas Thesen, PhD, Associate Professor of Medical Education, Co-Director, Neuroscience & Neurology - MD Program, Co-Director, Medical Learning Sciences - MD Program, Dartmouth Geisel School of Medicine
Topic: AI & Teaching in Neurology
Presented by: Erik Kobylarz, MD, PhD, Clinical Neurophysiology Fellowship Director, Intraoperative Neurophysiologic Monitoring Director, Dartmouth Hitchcock Medical Center and Thomas Thesen, PhD, Associate Professor of Medical Education, Co-Director, Neuroscience & Neurology - MD Program, Co-Director, Medical Learning Sciences - MD Program, Dartmouth Geisel School of Medicine
The Department of Biomedical Data Science at Geisel invites you to attend a Grand Rounds presentation by Jeremy Taylor, PhD, Professor of Biostatistics and Radiation Oncology, University of Michigan School of Public Health, on Thursday, April 11 from 12:00-1:00pm at DHMC, Auditorium H (or via Zoom).
Talk title: “Estimation and interpretation of time-varying effects of demographic, tumor, access to care and SES factors in cancer survival studies”
Host: Tor Tosteson, ScD
Location: In-person at DHMC, Auditorium H or via Zoom (no registration required)
Please see link below for more details.
Zoom meeting ID: 503 779 5102
Zoom passcode: 6501974
URL: https://dartmouth.zoom.us/j/5037795102
Phone (if needed for audio only, or to join by phone only): 669-900-6833
Presentation Summary
There have been thousands of studies that used the Cox proportional hazards model to analyze data and assess the association between factors measured at the time of diagnosis and survival outcomes in patients diagnosed with cancer. The Cox model makes the assumption of proportional hazards, but a more general model may give a more accurate description of the data. In a more flexible model, the hazard ratio associated with any factor can be allowed to vary over time. In this talk I will describe how we overcame the computational and statistical challenges of fitting such a model when the datasets are extremely large. I will then use the model to examine data from the SEER and NCDB cancer registries. I will take a pan cancer approach and consider 14 different cancer types. For SEER I consider a basic set of standard factors (age, race, stage, year of diagnosis, gender) and two outcomes, either death due to cancer or death due to other causes. The analyses reveal some substantial time-varying associations, especially for stage and age. The NCDB registry only has death from any cause, but it has additional factors, including comorbidities, SES variables and access to care variables. We investigate whether the time-varying age effect can be explained by other factors. The answer is generally no. I will invite the audience to speculate on possible reasons for the time varying association with age.
Biography
Jeremy M. G. Taylor, PhD, is the Pharmacia Professor of Biostatistics at the University of Michigan School of Public Health. He obtained a bachelor’s degree in mathematics and a diploma in statistics from Cambridge University, and a PhD in statistics from University of California-Berkeley. He was a faculty member in the Department of Biostatistics and the Department of Radiation Oncology at UCLA from 1983 to 1998. He is currently a faculty member in the Department of Biostatistics, the Department of Radiation Oncology, and the Department of Computational Medicine and Bioinformatics, and the Director of the Center for Cancer Biostatistics at the University of Michigan School of Public Health. Dr. Taylor is the winner of the Michael Fry Award from the Radiation Research Society, the Mortimer Spiegelman Award from the American Public Health Association, the Jerome Sacks Award from the National Institute of Statistical Science, and the Samuel Wilks award from the American Statistical Association. He is a former chair of the Biometrics Section of the American Statistical Association (ASA) and a fellow of the ASA. Dr. Taylor is the former chair of the Biostatistical Methods and Research Design grant review committee for the National Institutes of Health, and he was one of the coordinating editors of Biometrics from 2012-2014. He has over 400 publications and research interests in longitudinal and survival data, cure models, methods for missing data, causal inference, biomarkers, surrogate and auxiliary variables, and data integration. Dr. Taylor worked previously in AIDS research, but currently he mainly focuses on cancer research. He has served as the dissertation chair for 41 PhD students in biostatistics at UCLA and the University of Michigan.
Talk title: “Estimation and interpretation of time-varying effects of demographic, tumor, access to care and SES factors in cancer survival studies”
Host: Tor Tosteson, ScD
Location: In-person at DHMC, Auditorium H or via Zoom (no registration required)
Please see link below for more details.
Zoom meeting ID: 503 779 5102
Zoom passcode: 6501974
URL: https://dartmouth.zoom.us/j/5037795102
Phone (if needed for audio only, or to join by phone only): 669-900-6833
Presentation Summary
There have been thousands of studies that used the Cox proportional hazards model to analyze data and assess the association between factors measured at the time of diagnosis and survival outcomes in patients diagnosed with cancer. The Cox model makes the assumption of proportional hazards, but a more general model may give a more accurate description of the data. In a more flexible model, the hazard ratio associated with any factor can be allowed to vary over time. In this talk I will describe how we overcame the computational and statistical challenges of fitting such a model when the datasets are extremely large. I will then use the model to examine data from the SEER and NCDB cancer registries. I will take a pan cancer approach and consider 14 different cancer types. For SEER I consider a basic set of standard factors (age, race, stage, year of diagnosis, gender) and two outcomes, either death due to cancer or death due to other causes. The analyses reveal some substantial time-varying associations, especially for stage and age. The NCDB registry only has death from any cause, but it has additional factors, including comorbidities, SES variables and access to care variables. We investigate whether the time-varying age effect can be explained by other factors. The answer is generally no. I will invite the audience to speculate on possible reasons for the time varying association with age.
Biography
Jeremy M. G. Taylor, PhD, is the Pharmacia Professor of Biostatistics at the University of Michigan School of Public Health. He obtained a bachelor’s degree in mathematics and a diploma in statistics from Cambridge University, and a PhD in statistics from University of California-Berkeley. He was a faculty member in the Department of Biostatistics and the Department of Radiation Oncology at UCLA from 1983 to 1998. He is currently a faculty member in the Department of Biostatistics, the Department of Radiation Oncology, and the Department of Computational Medicine and Bioinformatics, and the Director of the Center for Cancer Biostatistics at the University of Michigan School of Public Health. Dr. Taylor is the winner of the Michael Fry Award from the Radiation Research Society, the Mortimer Spiegelman Award from the American Public Health Association, the Jerome Sacks Award from the National Institute of Statistical Science, and the Samuel Wilks award from the American Statistical Association. He is a former chair of the Biometrics Section of the American Statistical Association (ASA) and a fellow of the ASA. Dr. Taylor is the former chair of the Biostatistical Methods and Research Design grant review committee for the National Institutes of Health, and he was one of the coordinating editors of Biometrics from 2012-2014. He has over 400 publications and research interests in longitudinal and survival data, cure models, methods for missing data, causal inference, biomarkers, surrogate and auxiliary variables, and data integration. Dr. Taylor worked previously in AIDS research, but currently he mainly focuses on cancer research. He has served as the dissertation chair for 41 PhD students in biostatistics at UCLA and the University of Michigan.