@article{discovery10192883,
            note = {This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.},
          volume = {81},
           pages = {590--599},
           month = {October},
          number = {4},
         journal = {Journal of Hepatology},
       publisher = {Elsevier BV},
            year = {2024},
           title = {Agile scores in MASLD and ALD: External validation and their utility in clinical algorithms},
        keywords = {Non-invasive test, fibroscan, elastography, compensated advanced
chronic liver disease, diagnostic accuracy},
            issn = {0168-8278},
          author = {Papatheodoridi, Margarita and De Ledinghen, Victor and Lupsor-Platon, Monica and Bronte, Fabrizio and Boursier, Jerome and Elshaarawy, Omar and Marra, Fabio and Thiele, Maja and Markakis, Georgios and Payance, Audrey and Brodkin, Edgar and Castera, Laurent and Papatheodoridis, George and Krag, Aleksander and Arena, Umberto and Mueller, Sebastian and Cales, Paul and Calvaruso, Vincenza and Delamarre, Adele and Pinzani, Massimo and Tsochatzis, Emmanuel A},
        abstract = {Background \& Aims:
Agile scores, including liver stiffness measurements (LSM) and routine clinical/laboratory biomarkers, have been developed for advanced fibrosis (F{$\ge$}3) and cirrhosis (F4), respectively, in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). We independently validated the diagnostic accuracy of these scores in MASLD, alcohol-related liver disease (ALD) and chronic hepatitis B or C (CHB/C) and assessed them in clinical algorithms with FIB-4 and LSM.
//
Methods:
We included 4,243 patients (MASLD: 912, ALD: 386, CHB: 597, CHC: 2,348) with LSM, liver biopsy and laboratory tests within 6 months. FIB-4, Agile 3+ and Agile 4 scores were calculated.
//
Results:
For F{$\ge$}3, the diagnostic accuracy of Agile 3+ and LSM were similar in MASLD (AUC: 0.86 vs. 0.86, p = 0.831) and ALD (0.92 vs. 0.94, p = 0.123). For cirrhosis, Agile 4 was similar to LSM in MASLD (0.89 vs. 0.90, p = 0.412) and ALD (0.94 vs. 0.95, p = 0.513). Agile 3+/4 performed worse than LSM in CHB/C. Using predefined dual thresholds of 90\% sensitivity/specificity, correct classification rates in MASLD were 66\% vs. 61\% using Agile 3+ vs. LS dual cut-offs and 71\% vs. 67\% in ALD, respectively. When using Agile 3+ or LSM as a second step after FIB-4 {\ensuremath{>}}1.3, correct classification rates were higher with Agile 3+ than LSM, both for MASLD (75\% vs. 71\%) and ALD (76\% vs. 72\%), with fewer indeterminate results. Positive agreement of LSM and Agile 3+/4 significantly increased the specificity of a diagnosis of advanced fibrosis/cirrhosis.
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Conclusion:
Agile 3+ and Agile 4 have equal diagnostic accuracy with LSM in both MASLD and ALD but result in fewer indeterminate results. Sequential use of FIB-4 and Agile 3+/4 or concurrent Agile 3+/4 and LSM can be used to further optimize F{$\ge$}3 diagnosis.},
             url = {http://dx.doi.org/10.1016/j.jhep.2024.05.021}
}