Opportunity Information: Apply for PA 07 021
Apply for PA 07 021
- The National Institutes of Health in the education health sector is offering a public funding opportunity titled "Development, Application, and Evaluation of Prediction Models for Cancer Risk and Prognosis (R01)" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.393 Cancer Cause and Prevention Research 93.394 Cancer Detection and Diagnosis Research 93.395 Cancer Treatment Research 93.399 Cancer Control.
- This funding opportunity was created on Dec 5, 2008 and posted on Nov 20, 2006.
- Applicants must submit their applications by Multiple Receipt Dates See Link to Full Announcement for details.. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- Eligible applicants include: For profit organizations other than small businesses Nonprofits having a 501(c)(3) status with the IRS, other than institutions of higher education Small businesses Nonprofits that do not have a 501(c)(3) status with the IRS, other than institutions of higher education Others (see text field entitled Additional Information on Eligibility for clarification) Public and State controlled institutions of higher education Private institutions of higher education.
- Foreign institutions are eligible to apply.
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Opportunity Summary:
The Development, Application, and Evaluation of Prediction Models for Cancer Risk and Prognosis (R01) opportunity (Funding Opportunity Number PA-07-021) is a National Institutes of Health program led by the National Cancer Institute, specifically through NCI's Division of Cancer Control and Population Sciences (DCCPS) and Division of Cancer Treatment and Diagnosis (DCTD). It was created in response to NCI's emphasis on risk prediction as a high-impact priority area described in its 2006 Plan and Budget Proposal, and it supports investigator-initiated research projects that build better tools for estimating a person's cancer risk and predicting outcomes after a cancer diagnosis. The intent is to fund work that results in practical, validated prediction models that can be used by researchers, clinicians, and, in some cases, the general public.
The core goal of the FOA is to improve and expand cancer risk and prognostic modeling by encouraging innovative projects that either refine existing models or develop new ones. The announcement is geared toward multidisciplinary teams and welcomes applications from clinicians, epidemiologists, geneticists, statisticians, and translational researchers. Projects are expected to make strong use of existing data resources, whether that means leveraging large cohort studies, clinical trial datasets, tumor registries, electronic health records, biobanks, or linked data systems. A major theme is moving beyond single-source or single-variable approaches and instead building models that reflect the real complexity of cancer prevention and care.
Two challenges are highlighted as especially important and are essentially the backbone of what this funding mechanism is trying to solve. First is data integration: applicants are encouraged to combine diverse kinds of information such as clinical variables, demographics, pathology, environmental exposures, epidemiologic measures, outcomes, and genetic data, often pulled from multiple "data marts" or warehouses rather than a single clean dataset. Second is rigorous validation: the FOA stresses that model performance must be tested in multiple independent populations, not just the dataset used to build the model. In practical terms, this means applicants should plan to evaluate sensitivity and specificity as well as positive and negative predictive values, and to show that the model performs reliably across different groups and settings rather than only within a narrow or convenient sample.
The projects supported under this FOA can cover the full lifecycle of prediction modeling, including developing new models, updating or recalibrating established models for new populations, applying models to answer research questions, and evaluating whether the models are actually useful in clinical or research workflows. That "utility" component matters: the NCI is not only looking for statistical performance but also for evidence that a model can be implemented and interpreted in ways that improve decision-making, such as identifying high-risk groups for screening or prevention, guiding prognosis discussions, or informing follow-up strategies. At the same time, the FOA draws a clear boundary around what is not a fit. Applications focused primarily on discovering or characterizing new prognostic or diagnostic biomarkers, without a real emphasis on building and validating a prediction model, are considered non-responsive.
Administratively, this is an R01 research project grant, categorized as discretionary funding in the health area, and it spans multiple NCI-related CFDA program areas (including cancer cause and prevention, detection and diagnosis, treatment, and cancer control). There is no cost-sharing or matching requirement. Eligibility is broad: public and private institutions of higher education, nonprofits (with or without 501(c)(3) status), for-profit organizations (including small businesses), and other eligible entities as described in the full announcement can apply, and foreign institutions are explicitly eligible as well. The announcement used multiple receipt dates rather than a single deadline, with applicants directed to the full NIH posting for the specific schedule and submission details.
Frequently Asked Questions (FAQs)
What is the name of this funding opportunity?
The opportunity is titled The Development, Application, and Evaluation of Prediction Models for Cancer Risk and Prognosis (R01).
What is the Funding Opportunity Number (FON)?
The Funding Opportunity Number is PA-07-021.
Which agency and institute are leading this program?
This is a National Institutes of Health (NIH) program led by the National Cancer Institute (NCI), specifically through NCI's Division of Cancer Control and Population Sciences (DCCPS) and Division of Cancer Treatment and Diagnosis (DCTD).
Why was this FOA created?
It was created in response to NCI's emphasis on cancer risk prediction as a high-impact priority area described in NCI's 2006 Plan and Budget Proposal.
What is the main purpose of the FOA?
The FOA supports investigator-initiated research projects aimed at building better tools for estimating a person's cancer risk and predicting outcomes after a cancer diagnosis, with the intent of producing practical, validated prediction models that can be used by researchers, clinicians, and in some cases the general public.
What types of projects does the FOA encourage?
The FOA encourages innovative projects that refine existing models or develop new models to improve and expand cancer risk and prognostic modeling.
Does the FOA support work across the full model lifecycle?
Yes. Supported projects can span the full lifecycle of prediction modeling, including developing new models, updating or recalibrating existing models for new populations, applying models to research questions, and evaluating whether models are useful in clinical or research workflows.
What does the FOA mean by "utility" of a prediction model?
Utility refers to whether the model is useful in real-world decision-making, not just whether it has strong statistical performance. The FOA highlights usefulness for activities such as identifying high-risk groups for screening or prevention, guiding prognosis discussions, or informing follow-up strategies.
Is this funding opportunity intended for multidisciplinary teams?
Yes. The announcement is geared toward multidisciplinary teams and welcomes applications involving clinicians, epidemiologists, geneticists, statisticians, and translational researchers.
What kinds of data resources are applicants expected to use?
Projects are expected to make strong use of existing data resources. Examples mentioned include large cohort studies, clinical trial datasets, tumor registries, electronic health records, biobanks, and linked data systems.
What is meant by "data integration" in this FOA?
Data integration is a central theme. Applicants are encouraged to combine diverse information (for example clinical variables, demographics, pathology, environmental exposures, epidemiologic measures, outcomes, and genetic data), often drawn from multiple data sources ("data marts" or warehouses) rather than a single dataset.
What is meant by "rigorous validation" in this FOA?
Rigorously validating a model means testing its performance in multiple independent populations, not only in the dataset used to develop the model, and demonstrating reliable performance across different groups and settings.
What performance metrics does the FOA call out for validation?
The FOA highlights evaluating sensitivity, specificity, positive predictive value, and negative predictive value as part of demonstrating model performance.
Is model development alone sufficient, or is evaluation required too?
The FOA emphasizes both. It aims to fund work that results in practical, validated models, and it explicitly stresses rigorous validation and evaluation of utility in clinical or research workflows.
What is considered non-responsive to this FOA?
Applications focused primarily on discovering or characterizing new prognostic or diagnostic biomarkers, without a real emphasis on building and validating a prediction model, are described as non-responsive.
What grant mechanism is used for this opportunity?
This is an R01 research project grant.
What funding category and general area does this opportunity fall under?
It is categorized as discretionary funding in the health area.
Does this FOA span multiple NCI/CFDA program areas?
Yes. The announcement spans multiple NCI-related CFDA program areas, including cancer cause and prevention, detection and diagnosis, treatment, and cancer control.
Is cost-sharing or matching required?
No. The FOA states there is no cost-sharing or matching requirement.
Who is eligible to apply?
Eligibility is broad and includes public and private institutions of higher education, nonprofits (with or without 501(c)(3) status), for-profit organizations (including small businesses), and other eligible entities as described in the full announcement.
Are foreign institutions eligible to apply?
Yes. Foreign institutions are explicitly eligible under this opportunity.
Is there a single deadline to apply?
No. The announcement used multiple receipt dates rather than a single deadline, with applicants directed to the full NIH posting for the specific schedule and submission details.
Where should applicants look for the official receipt dates and submission instructions?
Applicants are directed to the full NIH posting for the specific receipt date schedule and submission details.
Who are the intended end users of the prediction models developed under this FOA?
The intent is for models to be usable by researchers, clinicians, and in some cases the general public.
What kinds of real-world decisions could these models support?
Examples described include identifying higher-risk groups for screening or prevention, guiding prognosis discussions, and informing follow-up strategies after diagnosis.
Does the FOA encourage moving beyond single-variable or single-source approaches?
Yes. A major theme is building models that reflect the complexity of cancer prevention and care, moving beyond models based on a single source or a single variable.
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