Validation of the accuracy of the FAST™ score for detecting patients with at-risk nonalcoholic steatohepatitis (NASH) in a North American cohort and comparison to other non-invasive algorithms

Management of patients with NASH who are at elevated risk of progressing to complications of cirrhosis (at-risk NASH) would be enhanced by an accurate, noninvasive diagnostic test. The new FAST™ score, a combination of FibroScan® parameters liver stiffness measurement (LSM) and controlled attenuatio...

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Veröffentlicht in:PloS one 2022-01, Vol.17 (4), p.e0266859
Hauptverfasser: Woreta, Tinsay A, Van Natta, Mark L, Lazo, Mariana, Krishnan, Arunkumar, Neuschwander-Tetri, Brent A, Loomba, Rohit, Mae Diehl, Anna, Abdelmalek, Manal F, Chalasani, Naga, Gawrieh, Samer, Dasarathy, Srinivasan, Vuppalanchi, Raj, Siddiqui, Mohammad S, Kowdley, Kris V, McCullough, Arthur, Terrault, Norah A, Behling, Cynthia, Kleiner, David E, Fishbein, Mark, Hertel, Paula, Wilson, Laura A, Mitchell, Emily P, Miriel, Laura A, Clark, Jeanne M, Tonascia, James, Sanyal, Arun J
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creator Woreta, Tinsay A
Van Natta, Mark L
Lazo, Mariana
Krishnan, Arunkumar
Neuschwander-Tetri, Brent A
Loomba, Rohit
Mae Diehl, Anna
Abdelmalek, Manal F
Chalasani, Naga
Gawrieh, Samer
Dasarathy, Srinivasan
Vuppalanchi, Raj
Siddiqui, Mohammad S
Kowdley, Kris V
McCullough, Arthur
Terrault, Norah A
Behling, Cynthia
Kleiner, David E
Fishbein, Mark
Hertel, Paula
Wilson, Laura A
Mitchell, Emily P
Miriel, Laura A
Clark, Jeanne M
Tonascia, James
Sanyal, Arun J
description Management of patients with NASH who are at elevated risk of progressing to complications of cirrhosis (at-risk NASH) would be enhanced by an accurate, noninvasive diagnostic test. The new FAST™ score, a combination of FibroScan® parameters liver stiffness measurement (LSM) and controlled attenuation parameter (CAP) and aspartate aminotransferase (AST), has shown good diagnostic accuracy for at-risk NASH (area-under-the-Receiver-Operating-Characteristic [AUROC] = 0.80) in European cohorts. We aimed to validate the FAST™ score in a North American cohort and show how its diagnostic accuracy might vary by patient mix. We also compared the diagnostic performance of FAST™ to other non-invasive algorithms for the diagnosis of at-risk NASH. We studied adults with biopsy-proven non-alcoholic fatty liver disease (NAFLD) from the multicenter NASH Clinical Research Network (CRN) Adult Database 2 (DB2) cohort study. At-risk-NASH was histologically defined as definite NASH with a NAFLD Activity Score (NAS) ≥ 4 with at least 1 point in each category and a fibrosis stage ≥ 2. We used the Echosens® formula for FAST™ from LSM (kPa), CAP (dB/m), and AST (U/L), and the FAST™-based Rule-Out (FAST™ ≤ 0.35, sensitivity = 90%) and Rule-In (FAST™ ≥ 0.67, specificity = 90%) zones. We determined the following diagnostic performance measures: AUROC, sensitivity (Se), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV); these were calculated for the total sample and by subgroups of patients and by FibroScan® exam features. We also compared the at-risk NASH diagnostic performance of FAST™ to other non-invasive algorithms: NAFLD fibrosis score (NFS), Fibrosis-4 (FIB-4) index, and AST to platelet ratio index (APRI). The NASH CRN population of 585 patients was 62% female, 79% white, 14% Hispanic, and 73% obese; the mean age was 51 years. The mean (SD) AST and ALT were 50 (37) U/L and 66 (45) U/L, respectively. 214 (37%) had at-risk NASH. The AUROC of FAST™ for at-risk NASH in the NASH CRN study population was 0.81 (95% CI: 0.77, 0.84. Using FAST™-based cut-offs, 35% of patients were ruled-out with corresponding NPV = 0.90 and 27% of patients were ruled-in with corresponding PPV = 0.69. The diagnostic accuracy of FAST™ was higher in non-whites vs. whites (AUROC: 0.91 vs 0.78; p = 0.001), and in patients with a normal BMI vs. BMI > 35 kg/m2 (AUROC: 0.94 vs 0.78, p = 0.008). No differences were observed by other patient characteristics or FibroScan® exam f
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The new FAST™ score, a combination of FibroScan® parameters liver stiffness measurement (LSM) and controlled attenuation parameter (CAP) and aspartate aminotransferase (AST), has shown good diagnostic accuracy for at-risk NASH (area-under-the-Receiver-Operating-Characteristic [AUROC] = 0.80) in European cohorts. We aimed to validate the FAST™ score in a North American cohort and show how its diagnostic accuracy might vary by patient mix. We also compared the diagnostic performance of FAST™ to other non-invasive algorithms for the diagnosis of at-risk NASH. We studied adults with biopsy-proven non-alcoholic fatty liver disease (NAFLD) from the multicenter NASH Clinical Research Network (CRN) Adult Database 2 (DB2) cohort study. At-risk-NASH was histologically defined as definite NASH with a NAFLD Activity Score (NAS) ≥ 4 with at least 1 point in each category and a fibrosis stage ≥ 2. We used the Echosens® formula for FAST™ from LSM (kPa), CAP (dB/m), and AST (U/L), and the FAST™-based Rule-Out (FAST™ ≤ 0.35, sensitivity = 90%) and Rule-In (FAST™ ≥ 0.67, specificity = 90%) zones. We determined the following diagnostic performance measures: AUROC, sensitivity (Se), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV); these were calculated for the total sample and by subgroups of patients and by FibroScan® exam features. We also compared the at-risk NASH diagnostic performance of FAST™ to other non-invasive algorithms: NAFLD fibrosis score (NFS), Fibrosis-4 (FIB-4) index, and AST to platelet ratio index (APRI). The NASH CRN population of 585 patients was 62% female, 79% white, 14% Hispanic, and 73% obese; the mean age was 51 years. The mean (SD) AST and ALT were 50 (37) U/L and 66 (45) U/L, respectively. 214 (37%) had at-risk NASH. The AUROC of FAST™ for at-risk NASH in the NASH CRN study population was 0.81 (95% CI: 0.77, 0.84. Using FAST™-based cut-offs, 35% of patients were ruled-out with corresponding NPV = 0.90 and 27% of patients were ruled-in with corresponding PPV = 0.69. The diagnostic accuracy of FAST™ was higher in non-whites vs. whites (AUROC: 0.91 vs 0.78; p = 0.001), and in patients with a normal BMI vs. BMI &gt; 35 kg/m2 (AUROC: 0.94 vs 0.78, p = 0.008). No differences were observed by other patient characteristics or FibroScan® exam features. The FAST™ score had higher diagnostic accuracy than other non-invasive algorithms for the diagnosis of at-risk NASH (AUROC for NFS, FIB-4, and APRI 0.67, 0.73, 0.74, respectively). We validated the FAST™ score for the diagnosis of at-risk NASH in a large, multi-racial population in North America, with a prevalence of at-risk NASH of 37%. Diagnostic performance varies by subgroups of NASH patients defined by race and obesity. FAST™ performed better than other non-invasive algorithms for the diagnosis of at-risk NASH.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0266859</identifier><identifier>PMID: 35427375</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Accuracy ; Adult ; Algorithms ; Aspartate aminotransferase ; Biology and Life Sciences ; Biopsy ; Cirrhosis ; Cohort Studies ; Complications ; Diagnosis ; Diagnostic systems ; Fatty liver ; Female ; Fibrosis ; Humans ; Laboratories ; Liver ; Liver - diagnostic imaging ; Liver - pathology ; Liver cirrhosis ; Liver Cirrhosis - diagnostic imaging ; Liver Cirrhosis - etiology ; Liver diseases ; Male ; Medical diagnosis ; Medicine ; Medicine and Health Sciences ; Middle Aged ; Mortality ; Non-alcoholic Fatty Liver Disease - complications ; Non-alcoholic Fatty Liver Disease - diagnosis ; Obesity ; Obesity - complications ; Parameters ; Patients ; Population studies ; Public health ; Risk ; Sensitivity ; Severity of Illness Index ; Stiffness ; Subgroups</subject><ispartof>PloS one, 2022-01, Vol.17 (4), p.e0266859</ispartof><rights>2022 Woreta et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2022 Woreta et al 2022 Woreta et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c526t-7c16e2aa1357feb8a306136ea0411dafae06c2f8a2348e19d57b317cda2fb55d3</citedby><cites>FETCH-LOGICAL-c526t-7c16e2aa1357feb8a306136ea0411dafae06c2f8a2348e19d57b317cda2fb55d3</cites><orcidid>0000-0002-2056-4909 ; 0000-0002-9452-7377 ; 0000-0003-2379-765X ; 0000-0001-7292-4518 ; 0000-0002-3597-3748 ; 0000-0003-0637-1577</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9012361/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9012361/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35427375$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Strnad, Pavel</contributor><creatorcontrib>Woreta, Tinsay A</creatorcontrib><creatorcontrib>Van Natta, Mark L</creatorcontrib><creatorcontrib>Lazo, Mariana</creatorcontrib><creatorcontrib>Krishnan, Arunkumar</creatorcontrib><creatorcontrib>Neuschwander-Tetri, Brent A</creatorcontrib><creatorcontrib>Loomba, Rohit</creatorcontrib><creatorcontrib>Mae Diehl, Anna</creatorcontrib><creatorcontrib>Abdelmalek, Manal F</creatorcontrib><creatorcontrib>Chalasani, Naga</creatorcontrib><creatorcontrib>Gawrieh, Samer</creatorcontrib><creatorcontrib>Dasarathy, Srinivasan</creatorcontrib><creatorcontrib>Vuppalanchi, Raj</creatorcontrib><creatorcontrib>Siddiqui, Mohammad S</creatorcontrib><creatorcontrib>Kowdley, Kris V</creatorcontrib><creatorcontrib>McCullough, Arthur</creatorcontrib><creatorcontrib>Terrault, Norah A</creatorcontrib><creatorcontrib>Behling, Cynthia</creatorcontrib><creatorcontrib>Kleiner, David E</creatorcontrib><creatorcontrib>Fishbein, Mark</creatorcontrib><creatorcontrib>Hertel, Paula</creatorcontrib><creatorcontrib>Wilson, Laura A</creatorcontrib><creatorcontrib>Mitchell, Emily P</creatorcontrib><creatorcontrib>Miriel, Laura A</creatorcontrib><creatorcontrib>Clark, Jeanne M</creatorcontrib><creatorcontrib>Tonascia, James</creatorcontrib><creatorcontrib>Sanyal, Arun J</creatorcontrib><creatorcontrib>NASH Clinical Research Network</creatorcontrib><creatorcontrib>for the NASH Clinical Research Network</creatorcontrib><title>Validation of the accuracy of the FAST™ score for detecting patients with at-risk nonalcoholic steatohepatitis (NASH) in a North American cohort and comparison to other non-invasive algorithms</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Management of patients with NASH who are at elevated risk of progressing to complications of cirrhosis (at-risk NASH) would be enhanced by an accurate, noninvasive diagnostic test. The new FAST™ score, a combination of FibroScan® parameters liver stiffness measurement (LSM) and controlled attenuation parameter (CAP) and aspartate aminotransferase (AST), has shown good diagnostic accuracy for at-risk NASH (area-under-the-Receiver-Operating-Characteristic [AUROC] = 0.80) in European cohorts. We aimed to validate the FAST™ score in a North American cohort and show how its diagnostic accuracy might vary by patient mix. We also compared the diagnostic performance of FAST™ to other non-invasive algorithms for the diagnosis of at-risk NASH. We studied adults with biopsy-proven non-alcoholic fatty liver disease (NAFLD) from the multicenter NASH Clinical Research Network (CRN) Adult Database 2 (DB2) cohort study. At-risk-NASH was histologically defined as definite NASH with a NAFLD Activity Score (NAS) ≥ 4 with at least 1 point in each category and a fibrosis stage ≥ 2. We used the Echosens® formula for FAST™ from LSM (kPa), CAP (dB/m), and AST (U/L), and the FAST™-based Rule-Out (FAST™ ≤ 0.35, sensitivity = 90%) and Rule-In (FAST™ ≥ 0.67, specificity = 90%) zones. We determined the following diagnostic performance measures: AUROC, sensitivity (Se), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV); these were calculated for the total sample and by subgroups of patients and by FibroScan® exam features. We also compared the at-risk NASH diagnostic performance of FAST™ to other non-invasive algorithms: NAFLD fibrosis score (NFS), Fibrosis-4 (FIB-4) index, and AST to platelet ratio index (APRI). The NASH CRN population of 585 patients was 62% female, 79% white, 14% Hispanic, and 73% obese; the mean age was 51 years. The mean (SD) AST and ALT were 50 (37) U/L and 66 (45) U/L, respectively. 214 (37%) had at-risk NASH. The AUROC of FAST™ for at-risk NASH in the NASH CRN study population was 0.81 (95% CI: 0.77, 0.84. Using FAST™-based cut-offs, 35% of patients were ruled-out with corresponding NPV = 0.90 and 27% of patients were ruled-in with corresponding PPV = 0.69. The diagnostic accuracy of FAST™ was higher in non-whites vs. whites (AUROC: 0.91 vs 0.78; p = 0.001), and in patients with a normal BMI vs. BMI &gt; 35 kg/m2 (AUROC: 0.94 vs 0.78, p = 0.008). No differences were observed by other patient characteristics or FibroScan® exam features. The FAST™ score had higher diagnostic accuracy than other non-invasive algorithms for the diagnosis of at-risk NASH (AUROC for NFS, FIB-4, and APRI 0.67, 0.73, 0.74, respectively). We validated the FAST™ score for the diagnosis of at-risk NASH in a large, multi-racial population in North America, with a prevalence of at-risk NASH of 37%. Diagnostic performance varies by subgroups of NASH patients defined by race and obesity. FAST™ performed better than other non-invasive algorithms for the diagnosis of at-risk NASH.</description><subject>Accuracy</subject><subject>Adult</subject><subject>Algorithms</subject><subject>Aspartate aminotransferase</subject><subject>Biology and Life Sciences</subject><subject>Biopsy</subject><subject>Cirrhosis</subject><subject>Cohort Studies</subject><subject>Complications</subject><subject>Diagnosis</subject><subject>Diagnostic systems</subject><subject>Fatty liver</subject><subject>Female</subject><subject>Fibrosis</subject><subject>Humans</subject><subject>Laboratories</subject><subject>Liver</subject><subject>Liver - diagnostic imaging</subject><subject>Liver - pathology</subject><subject>Liver cirrhosis</subject><subject>Liver Cirrhosis - diagnostic imaging</subject><subject>Liver Cirrhosis - etiology</subject><subject>Liver diseases</subject><subject>Male</subject><subject>Medical diagnosis</subject><subject>Medicine</subject><subject>Medicine and Health Sciences</subject><subject>Middle Aged</subject><subject>Mortality</subject><subject>Non-alcoholic Fatty Liver Disease - complications</subject><subject>Non-alcoholic Fatty Liver Disease - diagnosis</subject><subject>Obesity</subject><subject>Obesity - complications</subject><subject>Parameters</subject><subject>Patients</subject><subject>Population studies</subject><subject>Public health</subject><subject>Risk</subject><subject>Sensitivity</subject><subject>Severity of Illness 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of the accuracy of the FAST™ score for detecting patients with at-risk nonalcoholic steatohepatitis (NASH) in a North American cohort and comparison to other non-invasive algorithms</title><author>Woreta, Tinsay A ; Van Natta, Mark L ; Lazo, Mariana ; Krishnan, Arunkumar ; Neuschwander-Tetri, Brent A ; Loomba, Rohit ; Mae Diehl, Anna ; Abdelmalek, Manal F ; Chalasani, Naga ; Gawrieh, Samer ; Dasarathy, Srinivasan ; Vuppalanchi, Raj ; Siddiqui, Mohammad S ; Kowdley, Kris V ; McCullough, Arthur ; Terrault, Norah A ; Behling, Cynthia ; Kleiner, David E ; Fishbein, Mark ; Hertel, Paula ; Wilson, Laura A ; Mitchell, Emily P ; Miriel, Laura A ; Clark, Jeanne M ; Tonascia, James ; Sanyal, Arun J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c526t-7c16e2aa1357feb8a306136ea0411dafae06c2f8a2348e19d57b317cda2fb55d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Accuracy</topic><topic>Adult</topic><topic>Algorithms</topic><topic>Aspartate aminotransferase</topic><topic>Biology and Life Sciences</topic><topic>Biopsy</topic><topic>Cirrhosis</topic><topic>Cohort Studies</topic><topic>Complications</topic><topic>Diagnosis</topic><topic>Diagnostic systems</topic><topic>Fatty liver</topic><topic>Female</topic><topic>Fibrosis</topic><topic>Humans</topic><topic>Laboratories</topic><topic>Liver</topic><topic>Liver - diagnostic imaging</topic><topic>Liver - pathology</topic><topic>Liver cirrhosis</topic><topic>Liver Cirrhosis - diagnostic imaging</topic><topic>Liver Cirrhosis - etiology</topic><topic>Liver diseases</topic><topic>Male</topic><topic>Medical diagnosis</topic><topic>Medicine</topic><topic>Medicine and Health Sciences</topic><topic>Middle Aged</topic><topic>Mortality</topic><topic>Non-alcoholic Fatty Liver Disease - complications</topic><topic>Non-alcoholic Fatty Liver Disease - diagnosis</topic><topic>Obesity</topic><topic>Obesity - complications</topic><topic>Parameters</topic><topic>Patients</topic><topic>Population studies</topic><topic>Public health</topic><topic>Risk</topic><topic>Sensitivity</topic><topic>Severity of Illness Index</topic><topic>Stiffness</topic><topic>Subgroups</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Woreta, Tinsay A</creatorcontrib><creatorcontrib>Van Natta, Mark L</creatorcontrib><creatorcontrib>Lazo, Mariana</creatorcontrib><creatorcontrib>Krishnan, Arunkumar</creatorcontrib><creatorcontrib>Neuschwander-Tetri, Brent A</creatorcontrib><creatorcontrib>Loomba, Rohit</creatorcontrib><creatorcontrib>Mae Diehl, 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Brent A</au><au>Loomba, Rohit</au><au>Mae Diehl, Anna</au><au>Abdelmalek, Manal F</au><au>Chalasani, Naga</au><au>Gawrieh, Samer</au><au>Dasarathy, Srinivasan</au><au>Vuppalanchi, Raj</au><au>Siddiqui, Mohammad S</au><au>Kowdley, Kris V</au><au>McCullough, Arthur</au><au>Terrault, Norah A</au><au>Behling, Cynthia</au><au>Kleiner, David E</au><au>Fishbein, Mark</au><au>Hertel, Paula</au><au>Wilson, Laura A</au><au>Mitchell, Emily P</au><au>Miriel, Laura A</au><au>Clark, Jeanne M</au><au>Tonascia, James</au><au>Sanyal, Arun J</au><au>Strnad, Pavel</au><aucorp>NASH Clinical Research Network</aucorp><aucorp>for the NASH Clinical Research Network</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Validation of the accuracy of the FAST™ score for detecting patients with at-risk nonalcoholic steatohepatitis (NASH) in a North American cohort and comparison to other non-invasive algorithms</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2022-01-01</date><risdate>2022</risdate><volume>17</volume><issue>4</issue><spage>e0266859</spage><pages>e0266859-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Management of patients with NASH who are at elevated risk of progressing to complications of cirrhosis (at-risk NASH) would be enhanced by an accurate, noninvasive diagnostic test. The new FAST™ score, a combination of FibroScan® parameters liver stiffness measurement (LSM) and controlled attenuation parameter (CAP) and aspartate aminotransferase (AST), has shown good diagnostic accuracy for at-risk NASH (area-under-the-Receiver-Operating-Characteristic [AUROC] = 0.80) in European cohorts. We aimed to validate the FAST™ score in a North American cohort and show how its diagnostic accuracy might vary by patient mix. We also compared the diagnostic performance of FAST™ to other non-invasive algorithms for the diagnosis of at-risk NASH. We studied adults with biopsy-proven non-alcoholic fatty liver disease (NAFLD) from the multicenter NASH Clinical Research Network (CRN) Adult Database 2 (DB2) cohort study. At-risk-NASH was histologically defined as definite NASH with a NAFLD Activity Score (NAS) ≥ 4 with at least 1 point in each category and a fibrosis stage ≥ 2. We used the Echosens® formula for FAST™ from LSM (kPa), CAP (dB/m), and AST (U/L), and the FAST™-based Rule-Out (FAST™ ≤ 0.35, sensitivity = 90%) and Rule-In (FAST™ ≥ 0.67, specificity = 90%) zones. We determined the following diagnostic performance measures: AUROC, sensitivity (Se), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV); these were calculated for the total sample and by subgroups of patients and by FibroScan® exam features. We also compared the at-risk NASH diagnostic performance of FAST™ to other non-invasive algorithms: NAFLD fibrosis score (NFS), Fibrosis-4 (FIB-4) index, and AST to platelet ratio index (APRI). The NASH CRN population of 585 patients was 62% female, 79% white, 14% Hispanic, and 73% obese; the mean age was 51 years. The mean (SD) AST and ALT were 50 (37) U/L and 66 (45) U/L, respectively. 214 (37%) had at-risk NASH. The AUROC of FAST™ for at-risk NASH in the NASH CRN study population was 0.81 (95% CI: 0.77, 0.84. Using FAST™-based cut-offs, 35% of patients were ruled-out with corresponding NPV = 0.90 and 27% of patients were ruled-in with corresponding PPV = 0.69. The diagnostic accuracy of FAST™ was higher in non-whites vs. whites (AUROC: 0.91 vs 0.78; p = 0.001), and in patients with a normal BMI vs. BMI &gt; 35 kg/m2 (AUROC: 0.94 vs 0.78, p = 0.008). No differences were observed by other patient characteristics or FibroScan® exam features. The FAST™ score had higher diagnostic accuracy than other non-invasive algorithms for the diagnosis of at-risk NASH (AUROC for NFS, FIB-4, and APRI 0.67, 0.73, 0.74, respectively). We validated the FAST™ score for the diagnosis of at-risk NASH in a large, multi-racial population in North America, with a prevalence of at-risk NASH of 37%. Diagnostic performance varies by subgroups of NASH patients defined by race and obesity. FAST™ performed better than other non-invasive algorithms for the diagnosis of at-risk NASH.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>35427375</pmid><doi>10.1371/journal.pone.0266859</doi><orcidid>https://orcid.org/0000-0002-2056-4909</orcidid><orcidid>https://orcid.org/0000-0002-9452-7377</orcidid><orcidid>https://orcid.org/0000-0003-2379-765X</orcidid><orcidid>https://orcid.org/0000-0001-7292-4518</orcidid><orcidid>https://orcid.org/0000-0002-3597-3748</orcidid><orcidid>https://orcid.org/0000-0003-0637-1577</orcidid><oa>free_for_read</oa></addata></record>
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subjects Accuracy
Adult
Algorithms
Aspartate aminotransferase
Biology and Life Sciences
Biopsy
Cirrhosis
Cohort Studies
Complications
Diagnosis
Diagnostic systems
Fatty liver
Female
Fibrosis
Humans
Laboratories
Liver
Liver - diagnostic imaging
Liver - pathology
Liver cirrhosis
Liver Cirrhosis - diagnostic imaging
Liver Cirrhosis - etiology
Liver diseases
Male
Medical diagnosis
Medicine
Medicine and Health Sciences
Middle Aged
Mortality
Non-alcoholic Fatty Liver Disease - complications
Non-alcoholic Fatty Liver Disease - diagnosis
Obesity
Obesity - complications
Parameters
Patients
Population studies
Public health
Risk
Sensitivity
Severity of Illness Index
Stiffness
Subgroups
title Validation of the accuracy of the FAST™ score for detecting patients with at-risk nonalcoholic steatohepatitis (NASH) in a North American cohort and comparison to other non-invasive algorithms
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