# Core C: Data Management, Biostatistics and Modelling

> **NIH NIH U19** · HENNEPIN HEALTHCARE RESEARCH INSTITUTE · 2022 · $1,353,396

## Abstract

CORE C. DATA MANAGEMENT, BIOSTATISTICS AND MODELLING
SUMMARY/ABSTRACT
ASPREE maintained excellent data quality (99.6% accuracy) and performed crucial biostatistical analysis for a
vast quantity of data (~26 million data values) collected as part of the ASPREE Clinical trial. This Core will build
on the success of ASPREE by expanding capability, accessibility and methodological reach. It will implement
and maintain a sophisticated technology platform to support: i) in-field data collection (the focus of Core A); ii)
facilitate the capture of clinical events and documents (Cores A & B); iii) support adjudication of clinical events
(Core B); iv) provide storage and analysis of clinical images and biospecimen data (Core D); v) support linkage
with national and state data repositories (Admin Core); vi) undertake linkage of participant measures and clinical
data (Core A & B) with analysis-ready biospecimen (Core D) and genomic (Core E) data; and vii) support study
administration and governance (refer to Figure 1 in Research Strategy). Core C will also develop a hub of
biostatistical and modeling expertise to support the complex analysis of longitudinal data on disease and aging
processes across Projects 1-3 of the U19. Specifically, this Core will apply state transition models to disentangle
transitions of participants from being cancer-free to various cancer states, including death from cancer, with a
key focus on the effect of long-term LDA use; complete continuous biomarker and health measure tracking to
analyze trajectories of cognitive change; develop prediction models for Alzheimer’s disease risk and cognitive
resilience, specific to older people, incorporating lifestyle, health, genomic and biomarker data to analyze
cognitive decline; conduct continuous biomarker tracking analysis to analyze changes in score-based measures
of health to investigate the development and progression of frailty and the relationship between frailty and
disability; and employ multi-state time-to-event models to analyze complex disease pathways for disability. The
impact of findings will be explored through projection modeling, and young investigators will be trained in best
practice data management, data science, biostatistics and modeling. The activity of Core C is essential for the
exploration of outcomes related to cancer, Alzheimer ’s disease and disability. Consequently, the activity of Core
C is fundamental to addressing the research Aims for this U19.

## Key facts

- **NIH application ID:** 10428604
- **Project number:** 5U19AG062682-04
- **Recipient organization:** HENNEPIN HEALTHCARE RESEARCH INSTITUTE
- **Principal Investigator:** Rory Wolfe
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $1,353,396
- **Award type:** 5
- **Project period:** 2019-07-15 → 2024-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10428604

## Citation

> US National Institutes of Health, RePORTER application 10428604, Core C: Data Management, Biostatistics and Modelling (5U19AG062682-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10428604. Licensed CC0.

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