# Refining repeat screening for coronary artery disease in kidney transplant candidates

> **NIH NIH K23** · STANFORD UNIVERSITY · 2020 · $166,536

## Abstract

7. Project Summary
This K23 proposal will provide Xingxing S. Cheng, MD, MS with the protected time, mentorship, training, and
research experience to become an independent clinical investigator. Dr. Cheng is a board-certified
nephrologist and accredited transplant nephrologist, with a long-term vision of improving the effectiveness of
health care for kidney transplant patients. She seeks to combine patient-oriented research and decision
science to find innovative solutions to clinical problems. Skills she will acquire in this grant, under the guidance
of a strong mentorship team, include 1) integration of patient-oriented research and decision analytic models;
2) assessing the heterogeneity of response in different patient subgroups; and 3) advanced modelling skills.
This grant proposes to refine the process of screening of coronary artery disease in patients with chronic
kidney disease on the wait-list awaiting kidney transplantation. Currently, patients undergo repeat cardiac
screening tests at frequent intervals, few of which result in interventions. These tests impose a high treatment
burden on patients and potentially delay time to transplant, while bringing unclear benefit to the patient. This
grant proposes to refine the cardiac screening strategy and personalize it for specific patient subgroups (e.g.
elderly patients with diabetes mellitus). It will examine strategies that vary the frequency of cardiac testing and
risk stratification for cardiac testing based on a simple, inexpensive, and non-invasive test that can be
performed in routine clinical settings, a 6-minute walk test (6MWT). This project will achieve this broad aim by
three specific aims: 1) to characterize the 6MWT in identifying low-risk patients who do not additional cardiac
testing; 2) to model strategies varying the frequency of cardiac testing and use of 6MWT; 3) to design
strategies personalized for specific patient subgroups and model them in the entire kidney transplant candidate
population of the United States (US). The first two aims will arise from a well-characterized cohort of patients at
Dr. Cheng’s institution. Machine-learning systems will be used to identify which patient subgroups are best
served by which strategies (i.e. the heterogeneity of response). The third aim will leverage the US Renal Data
System, which Dr. Cheng’s mentors and institution has a track record of leveraging for innovative research.
The proposed work has high potential to make a significant clinical impact. Its completion will enable the
identification and characterization of rational strategies for pre-transplant screening of coronary artery disease
that may be incorporated into clinical practice or pave the way for a future multi-center comparative
effectiveness trial. The proposed work is realistic and feasible within the award period, and will allow Dr. Cheng
to build research skills, advance and disseminate scientific knowledge, create additional collaborative
networks, and compete...

## Key facts

- **NIH application ID:** 9871208
- **Project number:** 1K23DK123410-01
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Xingxing Shelley Cheng
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $166,536
- **Award type:** 1
- **Project period:** 2020-07-01 → 2025-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9871208

## Citation

> US National Institutes of Health, RePORTER application 9871208, Refining repeat screening for coronary artery disease in kidney transplant candidates (1K23DK123410-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9871208. Licensed CC0.

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