Controlled attenuation parameter-insulin resistance (CIR) score to predict non-alcoholic steatohepatitis

The diagnosis of non-alcoholic steatohepatitis (NASH) requires liver biopsy. Patients with NASH are at risk of progression to advanced fibrosis and hepatocellular carcinoma. A reliable non-invasive tool for the detection of NASH is needed. We aimed at developing a tool to diagnose NASH based on a pr...

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Authors: Macías Sánchez, Juan, Parra-Membrives, Pablo, Sosa-Moreno, Francisco, Rincón, Pilar, Martínez-Baena, Darío, Fernández-Fuertes, Marta, Lorente-Herce, José M., Martínez, Rafael, Jiménez-Riera, Granada, Corma-Gómez, Anaïs, González-Serna, Alejandro, Pineda, Juan A., Real, Luis Miguel
Format: article
Status:Published version
Publication Date:2022
Country:España
Institution:Consejo Superior de Investigaciones Científicas (CSIC)
Repository:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/305154
Online Access:http://hdl.handle.net/10261/305154
https://api.elsevier.com/content/abstract/scopus_id/85144327158
Access Level:Open access
Keyword:Non-alcoholic fatty liver disease
Non-alcoholic steatohepatitis
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spelling Controlled attenuation parameter-insulin resistance (CIR) score to predict non-alcoholic steatohepatitisMacías Sánchez, JuanParra-Membrives, PabloSosa-Moreno, FranciscoRincón, PilarMartínez-Baena, DaríoFernández-Fuertes, MartaLorente-Herce, José M.Martínez, RafaelJiménez-Riera, GranadaCorma-Gómez, AnaïsGonzález-Serna, AlejandroPineda, Juan A.Real, Luis MiguelNon-alcoholic fatty liver diseaseNon-alcoholic steatohepatitisThe diagnosis of non-alcoholic steatohepatitis (NASH) requires liver biopsy. Patients with NASH are at risk of progression to advanced fibrosis and hepatocellular carcinoma. A reliable non-invasive tool for the detection of NASH is needed. We aimed at developing a tool to diagnose NASH based on a predictive model including routine clinical and transient hepatic elastography (TE) data. All subjects undergoing elective cholecystectomy in our center were invited to participate, if alcohol intake was < 30 g/d for men and < 15 g/d for women. TE with controlled attenuation parameter (CAP) was obtained before surgery. A liver biopsy was taken during surgery. Multivariate logistic regression models to predict NASH were constructed with the first 100 patients, the elaboration group, and the results were validated in the next pre-planned 50 patients. Overall, 155 patients underwent liver biopsy. In the elaboration group, independent predictors of NASH were CAP value [adjusted OR (AOR) 1.024, 95% confidence interval (95% CI) 1.002-1.046, p = 0.030] and HOMA value (AOR 1.847, 95% CI 1.203-2.835, p < 0.001). An index derived from the logistic regression equation to identify NASH was designated as the CAP-insulin resistance (CIR) score. The area under the receiver operating characteristic curve (95%CI) of the CIR score was 0.93 (0.87-0.99). Positive (PPV) and negative predictive values (NPV) of the CIR score were 82% and 91%, respectively. In the validation set, PPV was 83% and NPV was 88%. In conclusion, the CIR score, a simple index based on CAP and HOMA, can reliably identify patients with and without NASH.J.M. is recipient of an intensification grant from Consejería de Salud, Junta de Andalucía (grant number: A1-0060-2021). J.A.P. is recipient of an intensification grant from the Instituto de Salud Carlos III (grant number: I3SNS). A.G.S. is recipient of a Miguel Servet Research Contract from the Instituto de Salud Carlos III (CP18/00146). A.C.G. has received a Río Hortega grant from the Instituto de Salud Carlos III (grant number CM19/00251) and a research extension grant from Acciones para el refuerzo con recursos humanos de la actividad investigadora en las Unidades Clínicas del Servicio Andaluz de Salud 2021, acción B (Clínico-Investigadores) (grant number B-0061-2021).This work has been partially funded by the Instituto de Salud Carlos III (grant no: PI18/00606); co-funded by ERDF "A way to make Europe" and Consejería de Salud de la Junta de Andalucía (PI-0001/2017).Peer reviewedNature Publishing GroupJunta de AndalucíaUniversidad Carlos III de MadridEuropean CommissionConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202320232022info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10261/305154https://api.elsevier.com/content/abstract/scopus_id/85144327158reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)InglésThe underlying dataset has been published as supplementary material of the article in the publisher platform at DOI 10.1038/s41598-022-25931-7https://doi.org/10.1038/s41598-022-25931-7Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3051542026-05-22T06:33:51Z
dc.title.none.fl_str_mv Controlled attenuation parameter-insulin resistance (CIR) score to predict non-alcoholic steatohepatitis
title Controlled attenuation parameter-insulin resistance (CIR) score to predict non-alcoholic steatohepatitis
spellingShingle Controlled attenuation parameter-insulin resistance (CIR) score to predict non-alcoholic steatohepatitis
Macías Sánchez, Juan
Non-alcoholic fatty liver disease
Non-alcoholic steatohepatitis
title_short Controlled attenuation parameter-insulin resistance (CIR) score to predict non-alcoholic steatohepatitis
title_full Controlled attenuation parameter-insulin resistance (CIR) score to predict non-alcoholic steatohepatitis
title_fullStr Controlled attenuation parameter-insulin resistance (CIR) score to predict non-alcoholic steatohepatitis
title_full_unstemmed Controlled attenuation parameter-insulin resistance (CIR) score to predict non-alcoholic steatohepatitis
title_sort Controlled attenuation parameter-insulin resistance (CIR) score to predict non-alcoholic steatohepatitis
dc.creator.none.fl_str_mv Macías Sánchez, Juan
Parra-Membrives, Pablo
Sosa-Moreno, Francisco
Rincón, Pilar
Martínez-Baena, Darío
Fernández-Fuertes, Marta
Lorente-Herce, José M.
Martínez, Rafael
Jiménez-Riera, Granada
Corma-Gómez, Anaïs
González-Serna, Alejandro
Pineda, Juan A.
Real, Luis Miguel
author Macías Sánchez, Juan
author_facet Macías Sánchez, Juan
Parra-Membrives, Pablo
Sosa-Moreno, Francisco
Rincón, Pilar
Martínez-Baena, Darío
Fernández-Fuertes, Marta
Lorente-Herce, José M.
Martínez, Rafael
Jiménez-Riera, Granada
Corma-Gómez, Anaïs
González-Serna, Alejandro
Pineda, Juan A.
Real, Luis Miguel
author_role author
author2 Parra-Membrives, Pablo
Sosa-Moreno, Francisco
Rincón, Pilar
Martínez-Baena, Darío
Fernández-Fuertes, Marta
Lorente-Herce, José M.
Martínez, Rafael
Jiménez-Riera, Granada
Corma-Gómez, Anaïs
González-Serna, Alejandro
Pineda, Juan A.
Real, Luis Miguel
author2_role author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Junta de Andalucía
Universidad Carlos III de Madrid
European Commission
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Non-alcoholic fatty liver disease
Non-alcoholic steatohepatitis
topic Non-alcoholic fatty liver disease
Non-alcoholic steatohepatitis
description The diagnosis of non-alcoholic steatohepatitis (NASH) requires liver biopsy. Patients with NASH are at risk of progression to advanced fibrosis and hepatocellular carcinoma. A reliable non-invasive tool for the detection of NASH is needed. We aimed at developing a tool to diagnose NASH based on a predictive model including routine clinical and transient hepatic elastography (TE) data. All subjects undergoing elective cholecystectomy in our center were invited to participate, if alcohol intake was < 30 g/d for men and < 15 g/d for women. TE with controlled attenuation parameter (CAP) was obtained before surgery. A liver biopsy was taken during surgery. Multivariate logistic regression models to predict NASH were constructed with the first 100 patients, the elaboration group, and the results were validated in the next pre-planned 50 patients. Overall, 155 patients underwent liver biopsy. In the elaboration group, independent predictors of NASH were CAP value [adjusted OR (AOR) 1.024, 95% confidence interval (95% CI) 1.002-1.046, p = 0.030] and HOMA value (AOR 1.847, 95% CI 1.203-2.835, p < 0.001). An index derived from the logistic regression equation to identify NASH was designated as the CAP-insulin resistance (CIR) score. The area under the receiver operating characteristic curve (95%CI) of the CIR score was 0.93 (0.87-0.99). Positive (PPV) and negative predictive values (NPV) of the CIR score were 82% and 91%, respectively. In the validation set, PPV was 83% and NPV was 88%. In conclusion, the CIR score, a simple index based on CAP and HOMA, can reliably identify patients with and without NASH.
publishDate 2022
dc.date.none.fl_str_mv 2022
2023
2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/305154
https://api.elsevier.com/content/abstract/scopus_id/85144327158
url http://hdl.handle.net/10261/305154
https://api.elsevier.com/content/abstract/scopus_id/85144327158
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv The underlying dataset has been published as supplementary material of the article in the publisher platform at DOI 10.1038/s41598-022-25931-7
https://doi.org/10.1038/s41598-022-25931-7
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Nature Publishing Group
publisher.none.fl_str_mv Nature Publishing Group
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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