Sarcopenia, adiposity and large discordance between cystatin C and creatinine-based estimated glomerular filtration rate in patients with cancer
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View abstract on PubMed
Summary
This summary is machine-generated.Sarcopenia and high adiposity in cancer patients are linked to significant differences in kidney function estimates. Body composition analysis from CT scans can improve the interpretation of estimated glomerular filtration rate (eGFR).
Area Of Science
- Nephrology
- Oncology
- Radiology
- Body Composition Analysis
Background
- Estimated glomerular filtration rate based on creatinine (eGFRCRE) may overestimate kidney function in sarcopenic patients.
- Estimated glomerular filtration rate based on cystatin C (eGFRCYS) may underestimate kidney function in obese patients.
- Body composition influences the accuracy of kidney function estimates in cancer patients.
Purpose Of The Study
- To evaluate the relationship between body composition (sarcopenia, adiposity) and discordance between eGFRCRE and eGFRCYS in adult cancer patients.
- To determine if CT scan-derived body composition data can explain discrepancies in kidney function estimation.
Main Methods
- Cross-sectional study of cancer patients with simultaneous eGFRCRE and eGFRCYS measurements and abdominal CT scans.
- Deep-learning pipeline used to measure muscle and adipose tissue areas from CT scans.
- CT-defined sarcopenia and high adiposity were assessed, and eGFR discordance (>30% and >50% difference) was analyzed using logistic regression.
Main Results
- Over half of the patients (58.7%) had CT-defined sarcopenia, and 25% had high adiposity.
- Nearly half of patients (48%) showed >30% eGFR discordance, and 22.4% showed >50% discordance.
- Both CT-defined sarcopenia and high adiposity were independently associated with significant eGFR discordance (aORs ranging from 1.90 to 2.34).
Conclusions
- CT-defined sarcopenia and high adiposity are independently associated with large discrepancies in estimated glomerular filtration rate.
- Integrating body composition data from routine CT scans can enhance the interpretation of GFR estimates in cancer patients.
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