# Novel evidence-accumulation-driven methods for characterizing kidney stone progression

> **NIH NIH R01** · UT SOUTHWESTERN MEDICAL CENTER · 2024 · $671,867

## Abstract

PROJECT SUMMARY
Preventing kidney stone progression remains a serious obstacle in public health, despite advances unravelling
the underlying mechanisms of stone formation. Kidney stone disease, often along with excruciating pain, is highly
prevalent around the globe, affecting nearly 12% of the world population. In the United States, the estimated
lifetime prevalence of kidney stone disease is approximately 10.6% in men and 7.1% in women. Following their
initial episode, stone formers are at higher risk for recurrent stone formation, with more than 50% experiencing
a recurrence within 10 years, reflecting the inadequacies of current prevention regimens. In addition, the
formation of stone disease is strongly associated with long-term complications of chronic kidney disease and
end-stage renal disease, along with significant morbidity, mortality as well as burden of health care cost.
 In response to PA-20-185, the overarching goal of this proposal is to maximize the efficacy of preventive
strategies against kidney stone disease progression by developing clinical prediction tools as well as
computational algorithms and software. More specifically, we propose novel evidence-accumulation-driven
methods (1) to develop patient-level risk prediction models for kidney stone disease progression accounting for
subtypes of stone conditions; and (2) to identify modifiable risk factors for stone disease progression by
integrating historically existing prediction models into new EHR or registry datasets. We will apply and validate
the proposed methods to real-world data, including the UTSW Mineral Metabolism Stone Registry, the PUSH
trial conducting by the Urinary Stone Disease Research Network (which is a clinical research network funded by
NIDDK), and the Swiss Kidney Stone Cohort.
 The success of this project will fill the knowledge gap of kidney stone disease progression, and lead to a
predictive toolbox to inform clinicians on the risk of kidney stone progression, thereby facilitating timely clinical
decision-making and implementation of targeted strategies to prevent or reduce stone disease progression.

## Key facts

- **NIH application ID:** 10749911
- **Project number:** 5R01DK128237-03
- **Recipient organization:** UT SOUTHWESTERN MEDICAL CENTER
- **Principal Investigator:** Yu-Lun Liu
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $671,867
- **Award type:** 5
- **Project period:** 2022-03-01 → 2026-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10749911

## Citation

> US National Institutes of Health, RePORTER application 10749911, Novel evidence-accumulation-driven methods for characterizing kidney stone progression (5R01DK128237-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10749911. Licensed CC0.

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