# Biostatistics Core

> **NIH NIH P20** · UNIVERSITY OF WASHINGTON · 2021 · $110,115

## Abstract

ABSTRACT: BIOSTATISTICS CORE
The Biostatistics Core (BC) will support the study design, data processing, and analysis needs for individual
projects as well as enhance interactions among all the projects in the P20. Experience has shown that
involvement of biostatisticians and data scientists from the concept phase yields studies that are better
designed, more likely to answer the scientific questions of interest, and, ultimately, more compelling in their
conclusions. The goal of the Biostatistics Core is to support the investigators through all phases of their studies
from design to publication via the following Specific Aims.
Specific Aim 1: Study Design
The BC will employ the 5-phase early detection biomarker development guideline as well as the PRoBE study
design standards in order to help the P20 team establish a road map and research strategies for improving
liver cancer early detection in AI/AN patients. The use of the 5-phase guideline will allow P20 investigators to
strategize and make long-term plans, helping move biomarkers from discovery phases 1-2 to validation phases
3-5, fulfilling the translational continuum. Adhering to PRoBE standards will guide the study design driven by
intended clinical application, reducing systematic bias, and ensuring a high likelihood of reproducible and
clinically relevant study conclusions.
Specific Aim 2: Analysis and Interpretation
The BC will play a leadership role in statistical analysis and interpretation for the proposed Li-CAD P20 projects.
The BC will identify and implement quantitative methods to address the scientific questions of interest and
provide valid statistical inferences about the evidence addressing the various study hypotheses. For example,
Parametric Empirical Bayesian (PEG) and Multivariate Fully Bayesian (mFB) approaches will be used to model
longitudinal biomarkers, which will be used to build risk prediction models for the early detection of HCC in AI/AN
population. Additionally, data visualization will be conducted to investigate HBV mutations, and state-of-the-art
machine learning approaches will be utilized to develop and validate HCC risk prediction models in AI/AN
persons. The BC will also work with study investigators to clearly communicate methods and results in study
publications and insure that reported conclusions are justified.
Specific Aim 3: Promote Interactions with DRP and Other Cores
The BC will interact with the DRP as well as the Biospecimen and Pathology Core to ensure efforts within the
Li-CAD P20 are on track, including all proposed P20 projects as well as DRP projects. The BC leader will
communicate directly with the P20 Executive Committee to ensure any decision that has statistical implications
has appropriate and timely inputs from the Core.

## Key facts

- **NIH application ID:** 10286762
- **Project number:** 1P20CA252732-01A1
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Ziding Feng
- **Activity code:** P20 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $110,115
- **Award type:** 1
- **Project period:** 2021-09-06 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10286762

## Citation

> US National Institutes of Health, RePORTER application 10286762, Biostatistics Core (1P20CA252732-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10286762. Licensed CC0.

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