Abstract 2346: Association of serum creatinine- and cystatin c-based diagnostic indices for sarcopenia with major chronic diseases

Abstract Background: Sarcopenia is a risk factor for chronic non-communicable diseases. The serum creatinine (Cr)/cystatin C (CysC) ratio (CCR) and the sarcopenia index (SI) have attracted attention as a surrogate marker for sarcopenia but have not been adequately studied in the general population. We aimed to explore the relationships of CCR and SI with major chronic diseases [cancer, cardiovascular disease (CVD), respiratory disease], investigate the validity of CCR and SI as predictors of sarcopenia and propose statistical cut-off values. Methods: We utilized two large-scale cohorts: the UK Biobank (UKB) and the National Health and Nutrition Examination Survey (NHANES). Serum creatinine and cystatin C levels were measured at baseline to calculate the CCR and SI. Cox regression models were applied to evaluate the impact of CCR and SI on major chronic diseases' incidence and mortality risks. Diagnostic value was analyzed through receiver operating characteristic (ROC) curves. The Youden index was calculated to determine the optimal cut-off points. Sarcopenia was then defined separately utilizing CCR, SI, and the European Working Group of Sarcopenia in Older People 2 criteria. Results: CCR and SI had negative associations with incidence and mortality risks of major chronic diseases as well as all-cause mortality. For the UK general population, the optimal cut-off values of CCR and SI for sarcopenia were 95.246 and 82.018 in men and 79.326 and 68.516 in women, respectively, with areas under the ROC curves (AUCs) of 0.717 and 0.709 in men, and 0.693 and 0.682 in women, respectively. For the USA general population, the optimal cut-off values of CCR and SI for sarcopenia were 94.521 and 85.296 in men and 90.993 and 76.904 in women, respectively, with AUCs of 0.755 and 0.752 in men and 0.595 and 0.588 in women, respectively. Furthermore, in the UKB database, CCR- and SI-defined sarcopenia were associated with a higher risk of pan-cancer and CVD incidence, as well as an increased risk of mortality from major diseases. In addition, CCR- and SI- defined sarcopenia in the NHANES database were positively associated with pan-cancer prevalence in women, and CCR-defined sarcopenia was dominantly correlated with an increased risk of mortality from major diseases in men. It is notable that CCR- and SI-defined sarcopenia were more strongly associated with the risks of major chronic diseases compared to EWGSOP2-defined sarcopenia. Conclusions: CCR and SI are both negatively associated with the incidence and mortality risks of major chronic diseases in the general population and may serve as surrogate markers for sarcopenia. Considering serum Cr and CysC commonly assessed in clinical practice, the application of Cr and CysC-derived CCR and SI may facilitate the early detection of sarcopenia and the prevention of chronic diseases in the general population. Citation Format: Fangfang Song, Huijun Zhou, Fubin Liu, Yu Peng, Peng Wang, Jianxiao Gong, Jiale Gu, Ailing Qin. Association of serum creatinine- and cystatin c-based diagnostic indices for sarcopenia with major chronic diseases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2346.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-2346
Primary Topic
Nutrition and Health in Aging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 2346: Association of serum creatinine- and cystatin c-based diagnostic indices for sarcopenia with major chronic diseases

Huijun Zhou, Jicheng Gong, Peng Wang, Fangfang Song et al.
Cancer Research
Nutrition and Health in Aging
article

Abstract 2346: Association of serum creatinine- and cystatin c-based diagnostic indices for sarcopenia with major chronic diseases

Huijun Zhou, Jicheng Gong, Peng Wang, Fangfang Song, Peng Yu, Fubin Liu, Jiale Gu, A. Qin
article en

Abstract

Abstract Background: Sarcopenia is a risk factor for chronic non-communicable diseases. The serum creatinine (Cr)/cystatin C (CysC) ratio (CCR) and the sarcopenia index (SI) have attracted attention as a surrogate marker for sarcopenia but have not been adequately studied in the general population. We aimed to explore the relationships of CCR and SI with major chronic diseases [cancer, cardiovascular disease (CVD), respiratory disease], investigate the validity of CCR and SI as predictors of sarcopenia and propose statistical cut-off values. Methods: We utilized two large-scale cohorts: the UK Biobank (UKB) and the National Health and Nutrition Examination Survey (NHANES). Serum creatinine and cystatin C levels were measured at baseline to calculate the CCR and SI. Cox regression models were applied to evaluate the impact of CCR and SI on major chronic diseases' incidence and mortality risks. Diagnostic value was analyzed through receiver operating characteristic (ROC) curves. The Youden index was calculated to determine the optimal cut-off points. Sarcopenia was then defined separately utilizing CCR, SI, and the European Working Group of Sarcopenia in Older People 2 criteria. Results: CCR and SI had negative associations with incidence and mortality risks of major chronic diseases as well as all-cause mortality. For the UK general population, the optimal cut-off values of CCR and SI for sarcopenia were 95.246 and 82.018 in men and 79.326 and 68.516 in women, respectively, with areas under the ROC curves (AUCs) of 0.717 and 0.709 in men, and 0.693 and 0.682 in women, respectively. For the USA general population, the optimal cut-off values of CCR and SI for sarcopenia were 94.521 and 85.296 in men and 90.993 and 76.904 in women, respectively, with AUCs of 0.755 and 0.752 in men and 0.595 and 0.588 in women, respectively. Furthermore, in the UKB database, CCR- and SI-defined sarcopenia were associated with a higher risk of pan-cancer and CVD incidence, as well as an increased risk of mortality from major diseases. In addition, CCR- and SI- defined sarcopenia in the NHANES database were positively associated with pan-cancer prevalence in women, and CCR-defined sarcopenia was dominantly correlated with an increased risk of mortality from major diseases in men. It is notable that CCR- and SI-defined sarcopenia were more strongly associated with the risks of major chronic diseases compared to EWGSOP2-defined sarcopenia. Conclusions: CCR and SI are both negatively associated with the incidence and mortality risks of major chronic diseases in the general population and may serve as surrogate markers for sarcopenia. Considering serum Cr and CysC commonly assessed in clinical practice, the application of Cr and CysC-derived CCR and SI may facilitate the early detection of sarcopenia and the prevention of chronic diseases in the general population. Citation Format: Fangfang Song, Huijun Zhou, Fubin Liu, Yu Peng, Peng Wang, Jianxiao Gong, Jiale Gu, Ailing Qin. Association of serum creatinine- and cystatin c-based diagnostic indices for sarcopenia with major chronic diseases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2346.

Cancer ResearchVol. 85(8_Supplement_1)
Tianjin Medical University Cancer Institute and Hospital (CN)
Openalex Percentile: Top 90%
Nutrition and Health in Aging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.