Impact of Computed Tomography–Derived Body Composition Analysis on the Performance of GFR Estimating Equations in Patients with Cancer

Key Points eGFR based on creatinine had large bias and poor accuracy in patients with sarcopenia regardless of their obesity status. Body composition analysis can identify patients in need of more accurate GFR assessment. eGFR based on creatinine and cystatin C or measured GFR should be considered when clinically relevant decisions are needed. Background Sarcopenia and obesity are common in patients with cancer and may reduce the accuracy of eGFR equations. We evaluated the performance of recommended eGFR equations based on creatinine or cystatin C and novel GFR markers β 2 -microglobulin (B2M) and β -trace protein (BTP) according to body composition derived from computed tomography (CT). Methods Prospective cohort study of adult patients with solid tumors recruited between May 2015 and October 2017 who had a CT scan within 90 days of measured GFR (mGFR) using plasma clearance of 51 Cr-EDTA. eGFR was calculated with the CKD-Epidemiology Collaboration equations using creatinine (eGFR CR ); cystatin C (eGFR CYS ); creatinine and cystatin (eGFR CR-CYS ); creatinine and B2M (eGFR CR-B2M ), cystatin, B2M, and BTP (eGFR CYS-B2M-BTP ); or creatinine, cystatin, B2M, and BTP (eGFR CR-CYS-B2M-BTP ). Bias was assessed as the median of the differences between mGFR and eGFR. Accuracy was assessed as the percentage of estimates that differed by more than 30% from the mGFR (1−P 30 ). 1−P 30 <10%, 10%–20%, and >20% are considered optimal, acceptable, and poor accuracy, respectively. Skeletal muscle index was quantified on CT and calculated by dividing the skeletal muscle cross-sectional area by the patient's height squared. Results Of 465 patients included, 157 (34%) met criteria for sarcopenia. Bias varied by magnitude of skeletal muscle index. In patients with sarcopenia, the accuracy of eGFR CR and eGFR CYS was poor (1−P 30 42.0% [95% CI, 34.4 to 49.6] and 20.4% [95% CI, 14.0 to 26.8], respectively). eGFR CR-CYS had acceptable accuracy (1−P 30 : 14.0 [8.3, 19.1] %), whereas eGFR CYS-B2M-BTP and eGFR CR-CYS-B2M-BTP had optimal accuracy (1−P 30 : 7.0 [3.2, 10.8] % and 8.3 [3.8, 12.3] %, respectively). Obesity did not significantly affect bias or accuracy. Conclusions GFR estimates based on eGFR CR and eGFR CYS are not sufficiently accurate in patients with cancer and sarcopenia. Body composition analysis can identify patients in need of more accurate GFR assessment. Podcast This article contains a podcast at https://dts.podtrac.com/redirect.mp3//www.asn-online.org/media/podcast/JASN/2025_12_10_KTS_December2025.mp3