May 29, 2019 10:30 AM - 11:30 AM
The authors propose a general Bayesian nonparametric (BNP) approach to causal inference in the point treatment setting. The joint distribution of the observed data (outcome, treatment, and confounders) is modeled using an enriched Dirichlet process. The combination of the observed data model and causal assumptions allows us to identify any type of causal effect - differences, ratios, or quantile effects, either marginally or for subpopulations of interest.
June 03, 2019 11:00 AM - 12:00 PM
Despite having one of the lowest somatic mutation burdens of any type of cancer, we show that rhabdoid tumors are highly infiltrated in many patients. Integrative profiling of human tumors and genetically engineered mouse models of rhabdoid tumor, including single cell RNA and TCR sequencing, highlight immunosuppressive macrophage populations and clonally expanded resident memory T cells.
June 05, 2019 10:30 AM - 11:30 AM
The advent of single-cell sequencing provides the ability to model clonal evolution of tumors within individual patients. Inference of such within-patient tumor phylogenies has the potential to advance the authors understanding of the variation in the process of tumor progression, with strong clinical implications. Here the authors consider the problem of rapid and robust inference of the tumor phylogeny from a sample of single-cell genotype data under a Markov model that incorporates error in the observed sequencing process.
June 12, 2019 10:30 AM - 11:30 AM
In this talk, the speaker proposes a novel method for individualized treatment selection when the treatment response is multivariate. This method covers multiple (any number) of treatments and it can be applied for a broad set of models. The key idea to handle multivariate response is to employ a rank aggregation technique to estimate an ordering of treatments based on ranked lists of treatment performance measures such as smooth conditional means and conditional probability of a response for one treatment dominating others. An empirical study demonstrates the performance of the proposed method in ﬁnite samples. Finally, the procedure will be illustrated using a real-life dataset on a HIV clinical trial.
June 13, 2019 10:30 AM - 11:30 AM
Using Novel Methods to Understand How Distinct Behaviors Impact Health
June 20, 2019 10:30 AM - 11:30 AM
The Finnish Maternity Cohort (FMC) is a biobank comprising virtually the entire population of women in Finland who have been pregnant between 1983 -2016. The FMC is linkable with population-based health registers including the Finnish Cancer Registry and the Medical Birth Register. Serial prediagnostic serum samples and comprehensive data accessible over three generations provide possibilities for unique study settings. The FMC has made substantial contributions to the scientific literature in terms of our understanding of the associations of various biomarkers with the later health of the mother and child. Studies include epidemiological research of infections associated with certain cancers (cervix, breast, leukemia) and linkage of prenatal exposures/biomarkers (smoking, alcohol, Vitamin D, persistent organic pollutants, steroid hormones, thyroid hormones and antibodies) with development of multiple sclerosis, with mental disorder of the child, or with pregnancy outcomes in general. Dr. Surcel’s presentation will focus on the principles and guidelines for how FMC biospecimens combined with health register data and archived pathologic samples are made available to researchers.
September 09, 2019 8:30 AM - September 12, 2019 5:00 PM
The Radiation Epidemiology and Dosimetry Course is conducted periodically by the Radiation Epidemiology Branch of the NCI Division of Cancer Epidemiology and Genetics (DCEG). This course is intended for people who are interested in learning about the health effects of radiation exposure (environmental, occupational, and medical)—particularly the relationship between ionizing radiation and cancer. The next course will be offered September 9-12, 2019.