# An individualized approach to identifying risk for serious infections and kidney outcomes in kidney transplant recipients

> **NIH NIH F32** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2021 · $79,841

## Abstract

PROJECT SUMMARY/ABSTRACT
Immunosuppression is critical for preventing rejection after kidney transplantation but is often associated with a
higher risk for infections. Infections leading to hospitalizations, graft failure, or mortality are more common in
the kidney transplant population compared with the general population and are associated with enormous
human and financial costs. Identifying approaches to reduce the risk for serious infections could improve graft
and patient survival. Mycophenolate is widely used as the backbone of most immunosuppression regimens in
kidney transplantation. Its incorporation into standard immunosuppression regimens has led to a reduction in
the rate of rejection, but mycophenolate use is also associated with increased risk for infections with
subsequent graft function loss related to infectious complications. Personalizing the dose of mycophenolate to
balance the protection of graft function with risk for infections could lead to better patient and allograft survival.
The goal of this proposal is to identify patients at risk for infection-related hospitalizations, infection-related
graft failure, or infection-related mortality in kidney transplant recipients and to identify potential strategies to
reduce this risk. In Aim 1, we will build a risk prediction model to discriminate the risk for infection-related
adverse outcomes using data from the United States Renal Data System (USRDS). We will internally validate
this model using USRDS data and externally validate our model using data from the Folic Acid for Vascular
Outcome Reduction in Transplantation (FAVORIT) Trial. In Aim 2, we will assess the feasibility of developing
an ancillary study in the ongoing PERformance and Frailty at Evaluation for Kidney Transplant (PERFEKT)
study (which has 500 active participants) to understand how mycophenolate dosing (normalized to patient
body surface area [BSA]) relates with infectious hospitalizations, acute kidney injury, and kidney function
decline in kidney transplant recipients. This proposal will train Dr. Dinh in statistical analysis, particularly as it
relates to risk prediction modeling, and will provide him with hands-on experience with prospective patient-
oriented research. UCSF is well suited for the conduct of this proposal, given that UCSF is one of the largest
transplant centers in the United States, performing 300-350 kidney transplants annually.
Our specific aims are:
Aim 1: To develop a prediction model for the risk of a composite of infection-related hospitalizations, infection-
related graft failure, or infection-related death within the first three years of kidney transplantation using a
USRDS cohort with >25,000 kidney transplant recipients, and to validate this model using FAVORIT.
Aim 2: To assess the feasibility of developing an ancillary study to PERFEKT to understand the relationship
between mycophenolate dosing (normalized to BSA), infectious and AKI events, and allograft function in
kidney tra...

## Key facts

- **NIH application ID:** 10233744
- **Project number:** 1F32DK128985-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Alex Dinh
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $79,841
- **Award type:** 1
- **Project period:** 2021-07-01 → 2022-05-21

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10233744

## Citation

> US National Institutes of Health, RePORTER application 10233744, An individualized approach to identifying risk for serious infections and kidney outcomes in kidney transplant recipients (1F32DK128985-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10233744. Licensed CC0.

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