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Posted · PA-07-022

Development, Application, and Evaluation of Prediction Models for Cancer Risk and Prognosis (R21)

National Institutes of Health  ·  HHS

CFDA Numbers

93.393, 93.394, 93.395, 93.399

Award Ceiling

Award Floor

Expected Awards

Close Date

Section I

How to Apply

Apply Online ↗

View on grants_gov ↗

Program Contact

NIH OER Webmaster<br/>FBOWebmaster@OD.NIH.GOV<br/>
FBOWebmaster@OD.NIH.GOV

Section II

Eligibility

Foreign institutions are eligible to apply.

Eligible Applicant Types

06, 12, 13, 20, 22, 23, 25

Section III

Description

-The National Cancer Institute (NCI) has identified risk prediction as an area of extraordinary opportunity in NCI s 2006 Plan and Budget Proposal: The Nation's Investment in Cancer Research (http://plan2006.cancer.gov/). To explore this opportunity, the NCI Division of Cancer Control and Population Sciences (DCCPS) and the Division of Cancer Treatment and Diagnosis (DCTD) solicit applications for research projects to develop, apply, and evaluate new and existing cancer risk and prognostic prediction models for use by researchers, clinicians, and the general public. -The purpose of this Funding Opportunity Announcement (FOA) is to encourage clinicians, epidemiologists, geneticists, statisticians, and translational researchers working in the field of cancer control and prevention to improve existing models for cancer risk and prognosis by developing innovative research projects that use existing data; develop new models for cancer risk and prognosis; and validate new models and evaluate their utility in research and clinic settings. Applications that are focused on the identification and characterization of prognostic/diagnostic markers are NOT responsive to this FOA. -This FOA is designed to provide a mechanism of support for investigators to address two major challenges in model development, which are: integrating diverse types of data (e.g., clinical, demographic, pathologic, environmental, epidemiologic, outcomes, and genetic data from varied data marts or warehouses); and ensuring adequate validation (i.e., using multiple separate populations to define sensitivity, specificity, and positive and negative predictive values).

Section IV

Key Dates

Posted
Nov 1, 2006
Archive
Feb 2, 2010