Academic journal article Environmental Health Perspectives

Cancer Intervention and Surveillance Modeling Network (CISNET)

Academic journal article Environmental Health Perspectives

Cancer Intervention and Surveillance Modeling Network (CISNET)

Article excerpt

The Division of Cancer Control and Population Sciences (DCCPS) of the National Cancer Institute (NCI) invites applications from domestic and foreign applicants to support collaborative research using simulation and other modeling techniques to describe the impact of interventions in population-based settings that will shed light on U.S. population-based trends. It is well known that great progress in the war against cancer is possible by the complete use and adequate delivery of existing modalities of cancer control. The primary goals of this research are to determine the impact of cancer control interventions on observed trends in incidence and/or mortality, and to determine if recommended interventions are having their expected population impact by examining discrepancies between controlled cancer intervention study results and the population experience.

Once a general understanding of the various factors influencing current trends has been achieved, a number of secondary goals may be addressed. Applicants may propose secondary goals of modeling the potential impact of new interventions on future national trends, and/or evaluating optimal cancer control strategies.

The NCI has a long-standing function of providing answers to critical policy questions, which can only be answered through an indirect synthesis of available information and assumptions. A commitment to modeling of this type will allow the NCI to apply the most sophisticated tools available for evidence-based planning to several areas: 1) Be responsive to challenges due to the increasing pace of technology, and to provide short-term answers while randomized controlled trials (RCTs) are still in progress. In the future we will be increasingly faced with new interventions, biomarkers, and diagnostic and genetic tests that will become widely disseminated prior to rigorous testing in controlled settings, and therefore the evaluation of population impact will become even more important. 2) Address emerging questions while they are still being debated in the policy forum. For example, new smokeless tobacco products are coming on the market, and modeling of their potential impact can benefit the Federal Trade Commission and other policy makers. 3) Translate RCT evidence of quantities to the population setting. 4) Provide estimates of quantities that will never be derived from RCTs. For example, half of Americans alive today who ever smoked are ex-smokers. It is important to understand the patterns of quitting, the process of carcinogenesis for ex-smokers, and the implications for future lung cancer trends.

DCCPS, which fulfills a federal-level function to respond to evolving surveillance questions of national policy relevance, helps focus research questions and acts as a conduit to national data resources necessary for parameter estimation, model calibration, validation, and population trends. An emergent property of this collaborative agreement is progress toward a comprehensive understanding of the determinants of site-specific cancer trends at the population level and a better understanding of the science of modeling.

Modeling is the use of mathematical and statistical techniques within a logical framework to integrate and synthesize known biological, epidemiological, clinical, behavioral, genetic, and economic information. Prior to the Cancer Intervention and Surveillance Modeling Network (CISNET), many of the simulation and other modeling techniques had been utilized to describe the impact of cancer interventions (i.e., primary prevention, screening, treatment) for hypothetical cohorts or in trial and other clinical settings. The goal of this request for applications (RFA) is to promote the application and extension of these models to population-based settings in order to ascertain determinants of cancer trends. This information is critical to the NCI because of the necessity of understanding whether recommended interventions are having their expected population impact, and of predicting the potential impact of new interventions on national trends. …

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