Optimized CAP cut-offs for metabolic dysfunction associated steatotic liver disease in patients living with obesity: a large biopsy-based prospective study

Controlled Attenuation Parameter (CAP) quantifies hepatic steatosis non-invasively, but current cut-offs limit diagnostic precision, especially in obese populations. We aimed to validate CAP against liver biopsy and propose optimized thresholds tailored for obesity. In this single-centre, cross-sectional, biopsy-validated study, 798 adults undergoing laparoscopic cholecystectomy (n = 629) or sleeve gastrectomy (n = 169) between 2019 and 2024 were included. All underwent Fibro Scan and wedge liver biopsy. Histology was scored by two blinded pathologists. Diagnostic accuracy of CAP was assessed using AUROC, sensitivity, specificity, predictive values, calibration, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA). Newly derived cut-offs were benchmarked against existing ones. Histology revealed S0 in 72.7%, S1 in 19.7%, S2 in 7.0%, and S3 in 0.6%. Standard CAP cut-offs showed suboptimal specificity (49.7% for ≥S1, 55.8% for ≥S2). Newly derived thresholds of 290 dB/m (≥ S1) and 317 dB/m (≥ S2) improved specificity (74.4% and 82.5%) while maintaining good sensitivity (62.7% and 71.7%). NRI and DCA demonstrated superior alignment and higher net benefit compared with all published thresholds. Optimized CAP cut-offs (290 and 317 dB/m) provide better diagnostic precision and clinical utility than current thresholds strengthening MASLD screening and clinical trial eligibility, particularly in obese populations.

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Publication Details

Journal
Scientific Reports
Published
2026-04-20
DOI
https://doi.org/10.1038/s41598-026-47209-y
Primary Topic
Liver Disease Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00

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article

Optimized CAP cut-offs for metabolic dysfunction associated steatotic liver disease in patients living with obesity: a large biopsy-based prospective study

Ahmed Farahat, Helmy Ezzat, ayman hassan, Ahmed Mehrez Gad et al.
Scientific Reports
Liver Disease Diagnosis and Treatment
article

Optimized CAP cut-offs for metabolic dysfunction associated steatotic liver disease in patients living with obesity: a large biopsy-based prospective study

Ahmed Farahat, Helmy Ezzat, ayman hassan, Ahmed Mehrez Gad, Rokia Masoud, Khaled Zalata, Riham Soliman, Ebrahim Abdel Halim, Nabiel Mikhail, Gamal Shiha, Mohamed Elbasiony, Mohamed El Emam, Ahmed Helmy
article en

Abstract

Controlled Attenuation Parameter (CAP) quantifies hepatic steatosis non-invasively, but current cut-offs limit diagnostic precision, especially in obese populations. We aimed to validate CAP against liver biopsy and propose optimized thresholds tailored for obesity. In this single-centre, cross-sectional, biopsy-validated study, 798 adults undergoing laparoscopic cholecystectomy (n = 629) or sleeve gastrectomy (n = 169) between 2019 and 2024 were included. All underwent Fibro Scan and wedge liver biopsy. Histology was scored by two blinded pathologists. Diagnostic accuracy of CAP was assessed using AUROC, sensitivity, specificity, predictive values, calibration, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA). Newly derived cut-offs were benchmarked against existing ones. Histology revealed S0 in 72.7%, S1 in 19.7%, S2 in 7.0%, and S3 in 0.6%. Standard CAP cut-offs showed suboptimal specificity (49.7% for ≥S1, 55.8% for ≥S2). Newly derived thresholds of 290 dB/m (≥ S1) and 317 dB/m (≥ S2) improved specificity (74.4% and 82.5%) while maintaining good sensitivity (62.7% and 71.7%). NRI and DCA demonstrated superior alignment and higher net benefit compared with all published thresholds. Optimized CAP cut-offs (290 and 317 dB/m) provide better diagnostic precision and clinical utility than current thresholds strengthening MASLD screening and clinical trial eligibility, particularly in obese populations.

Scientific ReportsVol. 16(1)
Damietta University (EG), Mansoura University (EG), Higher Technological Institute (EG), Mansoura University Hospital (EG), Higher Institute of Engineering (EG), Delta University for Science and Technology (EG), Assiut University (EG)
Science and Technology Development Fund, Mansoura University
Zero hunger
Openalex Percentile: Top 19%
Liver Disease Diagnosis and Treatment
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