| Title: | Normalized creatinine-to-cystatin C ratio and atherosclerotic cardiovascular disease risk in the UK Biobank |
| Journal: | European Journal of Preventive Cardiology |
| Published: | 17 Feb 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41701638/ |
| DOI: | https://doi.org/10.1093/eurjpc/zwag113 |
Publication 17733
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Abstract
OBJECTIVE: The normalized creatinine-to-cystatin C ratio (NCCR) is a novel composite biomarker that approximates relative skeletal muscle mass and diabetes risk. However, the association between NCCR and atherosclerotic cardiovascular disease (ASCVD) remains unclear. In this study, we obtained data from the UK Biobank with the aim to assess the association between the NCCR and ASCVD risk.</p>
METHODS: This study included 267167 participants from the UK Biobank enrolled between 2006 and 2010. Baseline NCCR was determined using the following formula: creatinine [mg/dL]/cystatin C [mg/L] × 10/body weight [kg]. The primary study outcome was the all-cause ASCVD incidence. Multivariable Cox proportional hazards regression was used to estimate the relationship between NCCR and ASCVD. Kaplan-Meier curves, restricted cubic spline (RCS), subgroup, and sensitivity analyses was conducted to enhance the robustness of our results.</p>
RESULTS: During a 15 years follow-up in average, 27026 participants developed ASCVD. NCCR showed a significant negative association with ASCVD (hazard ratio [HR] = 0.91, 95% CI: 0.89 - 0.92). Further sex-specific analysis revealed significant negative non-linear associations between NCCR and ASCVD in males, whereas a stronger linear association in females. Moreover, stratified and interaction analyses of the subgroups and several sensitivity analyses confirmed the stability of our core results.</p>
CONCLUSIONS: A high NCCR was independently associated with a reduced risk of ASCVD, particularly in females. Therefore, NCCR, which can be easily calculated from standard blood biochemistry, may potentially improve ASCVD risk assessment without the requirement of additional laboratory testing.</p>
5 Authors
- Xiaoyan Liu
- Huizhi Zhan
- Yi Ou
- Yuwen Shangguan
- Jingbo Zhang
1 Application
| Application ID | Title |
|---|---|
| 747364 | Identification and Prediction of Risk Factors for Immune-Mediated Inflammatory Diseases, with a Focus on Skin Disorders: An Integrated Epidemiological, Genetic, and Environmental Approach |
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