# PHCOC - SR Component

> **NIH NIH P30** · UNIVERSITY OF VIRGINIA · 2024 · $51,006

## Abstract

POPULATION HEALTH AND CANCER OUTCOMES CORE (PHCOC) – PROJECT SUMMARY
 The University of Virginia Cancer Center's (UVACC's) Population Health and Cancer Outcomes Core
(PHCOC) supports investigators in the conduct of rigorous population-based cancer research to reduce
cancer risk and support cancer care in survivorship, policy, and implementation. These efforts contribute to the
UVACC's overall mission to reduce the burden of cancer in its catchment area. In working to address these
goals, PHCOC provides expert data services and study and measure development services. Data services
within PHCOC offer assistance in data procurement, management, and analyses in order to assist
investigators with hypothesis development for grant applications. Study and measure design services include
piloting studies, evaluation, data collection, and the development of study instruments and measures in order
to assess health and quality of life in populations with cancer. PHCOC services are available at an hourly fee
for service to all investigators engaged in population-based cancer research, with priority given to UVACC
members. By providing population-level data analysis and guiding investigators through population-based
study methods, PHCOC strives to enhance cancer researchers' findings and results by connecting results and
data to larger population patterns and trends in cancer.

## Key facts

- **NIH application ID:** 10766183
- **Project number:** 5P30CA044579-33
- **Recipient organization:** UNIVERSITY OF VIRGINIA
- **Principal Investigator:** Wen You
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $51,006
- **Award type:** 5
- **Project period:** 1997-09-16 → 2027-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10766183

## Citation

> US National Institutes of Health, RePORTER application 10766183, PHCOC - SR Component (5P30CA044579-33). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10766183. Licensed CC0.

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