Diagnostic Accuracy of Noninvasive Fibrosis Models to Detect Change in Fibrosis Stage

Yamada, Goro; Vuppalanchi, Raj; Natta, Mark Van; Loomba, Rohit; Guy, Cynthia D.; Brandman, Danielle; Tonascia, James; Chalasani, Naga; Sanyal, Arun J.; Allende, Daniela S.; Dasarathy, Srinivasan; McCullough, Arthur J.; Penumatsa, Revathi; Dasarathy, Jaividhya; Lavine, Joel E.; Abdelmalek, Manal F.; Bashir, Mustafa R.; Buie, Stephanie; Diehl, Anna Mae; Kigongo, Christopher; Kopping, Mariko; Malik, David; Piercy, Dawn; Cummings, Oscar W.; Gawrieh, Samer; Ragozzino, Linda; Sandrasegaran, Kumar; Brunt, Elizabeth M.; Cattoor, Theresa; Carpenter, Danielle; Freebersyser, Janet; King, Debra; Lai, Jinping; Neuschwander‐Tetri, Brent A.; Siegner, Joan; Stewart, Susan D.; Torretta, Susan; Wriston, Kristina; Gonzalez, Maria Cardona; Davila, Jodie; Jhaveri, Manan; Kowdley, Kris V.; Mukhtar, Nizar A.; Ness, Erik; Poitevin, Michelle; Quist, Brook; Soo, Sherilynn; Ang, Brandon; Behling, Cynthia; Bhatt, Archana; Middleton, Michael S.; Sirlin, Claude B.; Akhter, Maheen F.; Bass, Nathan M.; Gill, Ryan M.; Hameed, Bilal; Maher, Jacqueline; Terrault, Norah A.; Ungermann, Ashley; Yeh, Matthew M.; Boyett, Sherry; Contos, Melissa J.; Kirwin, S.; Luketic, Velimir A.; Puri, Puneet; Schlosser, Jolene; Siddiqui, Mohammad Shadab; Yost-Schomer, Leslie; Fowler, Kathryn J.; Kleiner, David E.; Doo, Edward; Hall, Sherry; Hoofnagle, Jay H.; Lee, Jessica J.; Robuck, Patricia R.; Sherker, Averell H.; Torrance, Rebecca; Belt, Patricia; Clark, Jeanne M.; Dodge, J A; Donithan, Michele; Hallinan, Erin; Isaacson, Milana; Lazo, Mariana; Meinert, Jill; Miriel, Laura; Smith, J. P.; Smith, Michael L.; Sternberg, Alice L.; Natta, Mark L. Van; Wagoner, Annette; Wilson, Laura; Yates, Katherine P.

doi:10.1016/j.cgh.2018.12.031

Cited by 169 publications

(158 citation statements)

References 15 publications

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“…Several diagnostic approaches have been suggested, in particular an algorithm with a focus on primary care providers and diabetologists has been proposed by Bril and Cusi, and more recently by Castera et al. As previously discussed, the sensitivity of non‐invasive tests (NITs) is limited for the diagnosis of steatohepatitis or the early stages of fibrosis. Overall, the specificity and negative predictive value of NITs is good for advanced fibrosis while the sensitivity and positive predictive value are less strong.…”

Section: The Challenge Of Diagnosing Nash In Patients With T2dmmentioning

confidence: 99%

“…Overall, the specificity and negative predictive value of NITs is good for advanced fibrosis while the sensitivity and positive predictive value are less strong. For instance, in a recent study by Siddiqi et al in 1,904 patients enrolled in the NIDDK NASH Clinical Research Network recruited from 2004 through 2018, FIB‐4 and the NAFLD fibrosis score (NFS) outperformed other non‐invasive models for detecting advanced fibrosis, although their area under the curve (AUC) was only 0.80 for FIB‐4 and 0.78 for NFS. Similar results were reported by Anstee et al, using baseline data from the STELLAR Trials in 3,202 patients with evaluable biopsies.…”

Section: The Challenge Of Diagnosing Nash In Patients With T2dmmentioning

confidence: 99%

“…Several diagnostic approaches have been suggested, 7,8,18 in particular an algorithm with a focus on primary care providers and diabetologists has been proposed by Bril and Cusi 6 , and more recently by Castera et al 19 . As previously discussed, [6][7][8][18][19][20] FibroScan). The investigators found that a threshold with a high degree of sensitivity had an unacceptably low degree of specificity, and vice versa.…”

Section: The Challeng E Of D Iag Nos Ing Na S H In Patients With T2dmmentioning

confidence: 99%

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A diabetologist’s perspective of non‐alcoholic steatohepatitis (NASH): Knowledge gaps and future directions

Cusi

2020

Liver International

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There is a close link between steatohepatitis (NASH) and Type 2 diabetes (T2DM). Recently, the American Diabetes Association (ADA) recommended screening for NASH and advanced fibrosis in patients with diabetes and hepatic steatosis or elevated plasma alanine aminotransferase (ALT). This is because as many as ~30% to 40% may have NASH and ~10% to 15% advanced fibrosis. The role of hyperglycemia and the natural history of NASH in diabetes remain poorly understood, as well as which diagnostic algorithm or interventions are most cost‐effective. There is significant clinical inertia and most patients today are still not receiving adequate lifestyle intervention or pharmacological treatment with diabetes agents known to be effective against NASH. Lifestyle intervention improves steatohepatitis in proportion to the magnitude of weight loss, but this trend is not as consistent for regression of fibrosis. This limited success supports the need for concomitant pharmacological therapy. Pioglitazone has been shown to consistently induce resolution of NASH in both patients with or without diabetes in a total of 498 participants in five randomized controlled trials (RCTs), but with modest effects on liver fibrosis. Proof‐of‐concept studies suggest a potential role for GLP‐1RAs and SGLT2 inhibitors. Combination therapy is on the horizon. Treating diabetes and NASH with a combination of pioglitazone, GLP‐1RAs or SGLT2i, could be a cost‐effective strategy to treat both diseases while reducing their high cardiovascular risk. Future combination therapies will likely combine existing diabetes agents with novel NASH‐spechfic drugs under development. This review highlights current knowledge gaps and proposes future directions for the treatment of NASH in diabetes.

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Section: The Challenge Of Diagnosing Nash In Patients With T2dmmentioning

confidence: 99%

Section: The Challenge Of Diagnosing Nash In Patients With T2dmmentioning

confidence: 99%

Section: The Challeng E Of D Iag Nos Ing Na S H In Patients With T2dmmentioning

confidence: 99%

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A diabetologist’s perspective of non‐alcoholic steatohepatitis (NASH): Knowledge gaps and future directions

Cusi

2020

Liver International

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“…Furthermore, a significant proportion of patients fall within an indeterminate zone, consequently such scores are primarily used in the clinic to exclude a diagnosis of advanced liver fibrosis . Whilst having limited diagnostic value, scores such as FIB‐4 and NAFLD fibrosis score have shown some prognostic value …”

Section: Non‐invasive Assessment Of Liver Fibrosismentioning

confidence: 99%

Collagen biology and non‐invasive biomarkers of liver fibrosis

Karsdal

Daniels

Nielsen

et al. 2020

Liver International

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121

113

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There is an unmet need for high‐quality liquid biomarkers that can safely and reproducibly predict the stage of fibrosis and the outcomes of chronic liver disease (CLD). The requirement for such markers has intensified because of the high global prevalence of diseases such as non‐alcoholic fatty liver disease (NAFLD). In particular, there is a need for diagnostic and prognostic tools, as well as predictive biomarkers that reflect the efficacy of interventions, as described by the BEST criteria (Biomarkers, EndpointS, and other Tools Resource). This review covers the various liver collagens, their functional role in tissue homeostasis and delineates the common nomenclature for biomarkers based on BEST criteria. It addresses the common confounders affecting serological biomarkers, and describes defined collagen epitope biomarkers that originate from the dynamic processes of extracellular matrix (ECM) remodelling during liver injury.

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“…Changes in FIB‐4, NAFLD fibrosis score, and FibroTest/FibroSure were not associated with change in fibrosis. Recent data from the NASH Clinical Research Network suggest that incorporation of these scores with baseline fibrosis stage (determined by liver biopsy) may be useful to predict the development of advanced fibrosis but not progression of any fibrosis stage or resolution of fibrosis …”

Section: The 20% Rule (Fig 1)mentioning

confidence: 99%

The 20% Rule of NASH Progression: The Natural History of Advanced Fibrosis and Cirrhosis Caused by NASH

Loomba

Adams

2019

Hepatology

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Diagnostic Accuracy of Noninvasive Fibrosis Models to Detect Change in Fibrosis Stage

Cited by 169 publications

References 15 publications

A diabetologist’s perspective of non‐alcoholic steatohepatitis (NASH): Knowledge gaps and future directions

A diabetologist’s perspective of non‐alcoholic steatohepatitis (NASH): Knowledge gaps and future directions

Collagen biology and non‐invasive biomarkers of liver fibrosis

The 20% Rule of NASH Progression: The Natural History of Advanced Fibrosis and Cirrhosis Caused by NASH

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