1. Spleen stiffness measurement by vibration-controlled transient elastography at 100 Hz for non-invasive predicted diagnosis of clinically significant portal hypertension in patients with compensated advanced chronic liver disease: a modelling study.
- Author
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Jachs M, Odriozola A, Turon F, Moga L, Téllez L, Fischer P, Saltini D, Kwanten WJ, Grasso M, Llop E, Mendoza YP, Armandi A, Thalhammer J, Pardo C, Colecchia A, Ravaioli F, Maasoumy B, Laleman W, Presa J, Schattenberg JM, Berzigotti A, Calleja JL, Calvaruso V, Francque S, Schepis F, Procopet B, Albillos A, Rautou PE, García-Pagán JC, Puente Á, Fortea JI, Reiberger T, and Mandorfer M
- Abstract
Background: In patients with compensated advanced chronic liver disease (cACLD), risk of clinically significant portal hypertension (CSPH) can be estimated by applying non-invasive tests such as liver stiffness measurement (LSM), platelet count, and, in some cases, BMI. We aimed to assess the diagnostic utility of spleen stiffness measurement (SSM) at 100 Hz as a standalone non-invasive test for CSPH and to evaluate its incremental value compared with the ANTICIPATE±NASH model in patients with cACLD., Methods: For this modelling study, patients were recruited from 16 expert centres in Europe. Patients who underwent characterisation by hepatic venous pressure gradient (HVPG) and non-invasive tests (ie, LSM, platelet count, and SSM at 100 Hz) at one of the participating centres between Jan 1, 2020, and Dec 31, 2023, were considered for inclusion. Only patients aged 18 years or older with Child-Pugh class A cACLD, shown by LSM 10 kPa or more or F3 or F4 fibrosis on liver histology, were included. The overall cohort was split into the derivation cohort (patients recruited between Jan 1, 2020, and Dec 31, 2022) and the temporal validation cohort (patients recruited between Jan 1, 2023, and Dec 31, 2023). The ANTICIPATE±NASH model was applied to assess individual CSPH probability and SSM was investigated as a standalone non-invasive test for CPSH; in combination with platelet count and BMI; and in a full model of SSM, LSM, platelet count, and BMI (ie, the Non-Invasive CSPH Estimated Risk [NICER] model). All models were binary logistic regression models. The primary outcome was CSPH. We evaluated the discriminative utility of the models by calculating the area under the receiver operating characteristics curve (AUC) and creating calibration plots and calibration of intercept, slope, and integrated calibration index., Findings: 407 patients with cACLD were included, 202 (50%) in the derivation cohort and 205 (50%) in the validation cohort. Median age was 60·0 years (IQR 55·0-66·8); 275 (68%) of 407 patients were male and 132 (32%) were female. 164 (40%) of 407 patients had metabolic dysfunction-associated steatotic liver disease (MASLD), 133 (33%) had MASLD with increased alcohol intake or alcohol-related liver disease, 75 (18%) had viral hepatitis (61 [81%] of whom had sustained virologic response of hepatitis C virus or suppression of hepatitis B virus DNA), and 35 (9%) had other chronic liver diseases. 241 (59%) patients had CSPH. Median SSM was 45·0 kPa (32·1-65·4) and LSM was 21·4 kPa (14·1-31·6). SSM and LSM had similar AUCs for prediction of CSPH in the derivation cohort (0·779 [95% CI 0·717-0·842] vs 0·781 [0·718-0·844]; p=0·97) and in the validation cohort (0·830 [0·772-0·887] vs 0·804 [0·743-0·864]; p=0·50). The SSM-based model comprising platelet count and BMI had a similar AUC as the ANTICIPATE±NASH model in both the derivation cohort (0·849 [0·794-0·903] vs 0·849 [0·794-0·903]; p=0·999) and in the validation cohort (0·873 [0·819-0·922] vs 0·863 [0·810-0·916]; p=0·75). The NICER model had a significantly higher AUC for prediction of CSPH than the ANTICIPATE±NASH model in the derivation cohort (0·889 [0·843-0·934] vs 0·849 [0·794-0·903]; p=0·022) and in the validation cohort (0·906 [0·864-0·946] vs 0·863 [0·810-0·916]; p=0·012)., Interpretation: The addition of SSM to LSM, BMI, and platelet count outperformed the ANTICIPATE±NASH model for CSPH risk stratification in our cohort of contemporary patients with cACLD. SSM improves the non-invasive diagnosis of CSPH, supporting its implementation into clinical practice., Funding: Echosens., Competing Interests: Declaration of interests MJ has been a speaker and consultant for Gilead. FT has been a speaker for W L Gore & Associates. LT has been a speaker, consultant, or advisory board member for AbbVie, Eisai, Gilead, Janssen, and W L Gore & Associates and has received travel support from AbbVie, Janssen, Roche, and Gilead. WJK has been a speaker for the panNASH initiative; has received travel grants from Ipsen and Norgine; and is a co-inventor and patent holder for the use of lipopigment imaging for disease (filed by Massachusetts General Hospital and Massachusetts Institute of Technology; US 20190307390). AC has been a speaker and consultant for Jazz Pharmaceuticals. BM received grants and research support from Abbott, Fujirebio, Ewimed, and Roche and personal fees from Abbott, AbbVie, BMS, Janssen, Luvos, Merck, MSD, Roche, Fujirebio, Norgine, Gilead, and Astellas. WL has been a consultant for Cook Medical, Boston Scientific, CSL Behring, and MRM Health. JP has been a speaker, consultant, or advisory board member for AbbVie, Gilead, Advanz, MSD, Roche, AstraZeneca, Eisai, Orphalan, and Sobi. JMS has been a consultant and advisory board member for AbbVie; has received honoraria from Apollo Endoscopy, Boehringer Ingelheim, Gilead, Advanz Sciences, Intercept Pharmaceuticals, Ipsen, Inventiva Pharma, Madrigal Pharmaceuticals, MSD, Northsea Therapeutics, Novartis, Novo Nordisk, Pfizer, Roche, AstraZeneca, Eisai, OrphalanSanofi, and Siemens Healthineers; has received research funding from Boehringer Ingelheim and Siemens Healthcare; has received speaker honoraria from Boehringer Ingelheim, Echosens, MedPublico, Novo Nordisk, Madrigal Pharmaceuticals, and Histoindex; and holds stockholder options in AGED diagnostics and Sobi JHepta Bio. AB has been a speaker or consultant for Boehringer Ingelheim, GE HealthCare, Hologic, and W L Gore & Associates. VC has been a speaker, consultant, or advisory board member for Advanz, Ipsen, AbbVie, Echosens, Gilead, and Roche and has received grants and research support from Advanz and MSD. SF has been a speaker or consultant for W L Gore & Associates, Cook Medical, and Echosens and has received grants and research support from W L Gore & Associates and Cook Medical. FS has been a speaker or consultant for W L Gore & Associates, Cook Medical, and Echosens and has received grants and research support from W L Gore & Associates and Cook Medical. BP has been a speaker for AbbVie and Echosens. AAl has received fellowship funding from United European Gastroenterology. P-ER has received research funding from Terrafirma and has been a speaker or consultant for Abbelight, AbbVie, Hemostod, Mursla, Genfit, Boehringer Ingelheim, and Tillots Pharma. JCG is an advisory board member for W L Gore & Associates and Cook and has received grant support from Mallinckrodt, CSL Vifor, and AstraZeneca. JIF has been a speaker for Grifols and has received travel support from Gilead. TR has been a speaker, consultant, or advisory board member for AbbVie, Bayer, Boehringer Ingelheim, Gilead, Intercept, MSD, Siemens, and W L Gore & Associates; has received grants and research support from AbbVie, Boehringer Ingelheim, Gilead, Intercept, MSD, Myr Pharmaceuticals, Pliant, Philips, Siemens, and W L Gore & Associates; and has received travel support from AbbVie, Boehringer Ingelheim, Gilead, and Roche. MM received a research grant from Echosens for the coordination of this study; has been a speaker, consultant, or advisory board member for AbbVie, Echosens, Gilead, Ipsen, and W L Gore & Associates and has received travel support from AbbVie and Gilead. All other authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)
- Published
- 2024
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