Related Experiment Video
Updated: Aug 20, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Integrative epidemiology: from risk assessment to outcome prediction
Margaret R Spitz1, Xifeng Wu, Gordon Mills
1Department of Epidemiology, The University of Texas M. D. Anderson Cancer Center, 1515 Holcombe Blvd., Box 189, Houston, TX 77030, USA. mspitz@mdanderson.org
Abstract:
In this paper, we advance the concept of integrative epidemiology. Our unifying premise is that the same genes that are implicated in cancer risk may also be involved in a person's propensity to carcinogenic exposure and/or to modulation of therapeutic outcome. In the coming years, molecular epidemiology will play an increasingly prominent role in early detection of cancer and in identifying genetically high-risk subgroups that might benefit disproportionately from more intensive screening or chemoprevention interventions. Molecular epidemiology is also integral to pharmacogenetic research, by constructing genetic profiles that could be used to individualize therapy and to understand the functional consequences of chemoprevention, chemotherapy, or radiotherapy response. At the level of risk assessment, the focus might be on germline polymorphisms in candidate genes; for early detection, epigenetic events in these same or other genes may be relevant; and tumor tissue expression levels, loss of heterozygosity, genomic amplification, rearrangements, or somatic mutations in the same classes of genes may determine outcome. We will provide examples of how changes in the function of a single gene can contribute to susceptibility to carcinogenic exposure, predisposition to cancer development, patient prognosis, and prediction of outcome.
Related Concept Videos
Introduction to Epidemiology
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Causality in Epidemiology
Strategies for Assessing and Addressing Confounding
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Statistical Methods for Analyzing Epidemiological Data
Steps in Outbreak Investigation
