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Limitations of Noninvasive Tests-Based Population-Level Risk Stratification Strategy for Nonalcoholic Fatty Liver Disease

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Abstract

Background

Nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) are highly prevalent but underdiagnosed.

Aims

We used an electronic health record data network to test a population-level risk stratification strategy using noninvasive tests (NITs) of liver fibrosis.

Methods

Data were obtained from PCORnet® sites in the East, Midwest, Southwest, and Southeast United States from patients aged \(\ge\) 18 with or without ICD-10-CM diagnosis codes for NAFLD, NASH, and NASH-cirrhosis between 9/1/2017 and 8/31/2020. Average and standard deviations (SD) for Fibrosis-4 index (FIB-4), NAFLD fibrosis score (NFS), and Hepatic Steatosis Index (HSI) were estimated by site for each patient cohort. Sample-wide estimates were calculated as weighted averages across study sites.

Results

Of 11,875,959 patients, 0.8% and 0.1% were coded with NAFLD and NASH, respectively. NAFLD diagnosis rates in White, Black, and Hispanic patients were 0.93%, 0.50%, and 1.25%, respectively, and for NASH 0.19%, 0.04%, and 0.16%, respectively. Among undiagnosed patients, insufficient EHR data for estimating NITs ranged from 68% (FIB-4) to 76% (NFS). Predicted prevalence of NAFLD by HSI was 60%, with estimated prevalence of advanced fibrosis of 13% by NFS and 7% by FIB-4. Approximately, 15% and 23% of patients were classified in the intermediate range by FIB-4 and NFS, respectively. Among NAFLD-cirrhosis patients, a third had FIB-4 scores in the low or intermediate range.

Conclusions

We identified several potential barriers to a population-level NIT-based screening strategy. HSI-based NAFLD screening appears unrealistic. Further research is needed to define merits of NFS- versus FIB-4-based strategies, which may identify different high-risk groups.

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Data availability

The data for this study reside behind institutional firewalls of each participating center and aggregate queries were run using the common data model. Individual patient data are not available. All aggregate data generated or analyzed during this study are included in this published article.

Abbreviations

NAFLD:

Nonalcoholic fatty liver disease

NASH:

Nonalcoholic steatohepatitis

T2DM:

Type 2 diabetes mellitus

NIT:

Noninvasive tests

FIB-4:

Fibrosis-4 index

ALT:

Alanine aminotransferase

AST:

Aspartate aminotransferase

TE:

Transient elastography

US:

United States

EHR:

Electronic health records

CDM:

Common data model

BT:

Below threshold

ICD-10:

International Classification of Diseases, 10th Revision

SD:

Standard deviation

NFS:

NAFLD fibrosis score

HSI:

Hepatitis steatosis index

BMI:

Body mass index

GERD:

Gastroesophageal reflux disease

MASLD:

Metabolic dysfunction-associated steatotic liver disease

MASH:

Metabolic dysfunction-associated steatohepatitis

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Acknowledgments

This work was supported by Pfizer. Authors from Pfizer provided input into the development of the project. However, investigators from collaborating academic institutions were responsible for the final study design, data analysis, and drafting of the manuscript. The PCORnet® Study reported in this publication was conducted using PCORnet®, the National Patient-Centered Clinical Research Network. PCORnet® has been developed with funding from the Patient-Centered Outcomes Research Institute® (PCORI®) to the PaTH PCORnet Clinical Research Network (RI-CRN-2020-006). The statements presented in this article are solely the responsibility of the authors and do not necessarily represent the views of other organizations participating in, collaborating with, or funding PCORnet® or of the Patient-Centered Outcomes Research Institute® (PCORI®).

Author information

Authors and Affiliations

  1. Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh School of Medicine, Suite 201, Kaufmann Medical Building, 3471 Fifth Ave, Pittsburgh, PA, 15213, USA

    Jaideep Behari

  2. Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15206, USA

    Allison Bradley, Michael J. Becich, Nickie Cappella, Richard Morgan & Jonathan C. Silverstein

  3. US Medical Affairs, Pfizer Inc, New York, NY, 10017, USA

    Kevin Townsend, Fady Ntanios, Mohammad Ateya & Rozelle Hegeman-Dingle

  4. Division of General Internal Medicine, Penn State College of Medicine, Hershey, PA, 17033, USA

    Cynthia H. Chuang

  5. Department of Biomedical Informatics, Wexner Medical Center, The Ohio State University, Columbus, OH, 43201, USA

    Soledad A. Fernandez

  6. Department of General Internal Medicine, Johns Hopkins University, Baltimore, MD, 21205, USA

    Daniel E. Ford

  7. Department of Population Health Sciences, Geisinger Health System, Danville, PA, 17822, USA

    H. Lester Kirchner

  8. Department of Medicine, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, 19140, USA

    Anuradha Paranjape

  9. Department of Anesthesiology, University of Michigan, Ann Arbor, MI, 48105, USA

    David A. Williams

  10. Division of Endocrinology, Diabetes and Metabolism, University of Florida, Gainesville, FL, 32608, USA

    W. Troy Donahoo

  11. Baylor University Medical Center, Dallas, TX, 75246, USA

    Sumeet K. Asrani

  12. Pfizer Health Economics and Outcomes Research, Tadworth, UK

    Euan McLeod

  13. Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA

    Kathleen McTigue

Authors
  1. Jaideep Behari
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  2. Allison Bradley
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  3. Kevin Townsend
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  4. Michael J. Becich
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  14. W. Troy Donahoo
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Contributions

Conception and design: JB, AB, KT, KM. Administrative support: All authors. Provision of study materials or patients: All authors. Collection and assembly of data: AB, MJB, NC, CHC, SAF, DEF, HLK, RM, AP, JCS, DAW, WTD, SA, FN, MA, RHD, EM, KM. Data analysis and interpretation: JB, AB, KT, MJB, NC, CHC, SAF, DEF, HLK, RM, AP, JCS, DAW, WTD, SA, FN, MA, RHD, EM, KM. Manuscript writing: All authors. Final approval of manuscript: All authors. Registration Number: Not applicable.

Corresponding author

Correspondence to Jaideep Behari.

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Conflict of interest

JB: Funding support from National Center for Advancing Translational Sciences (NICATS) (4UH3TR003289), National Cancer Institute (NCI) 1R01CA255809, and National Institute on Alcohol Abuse and Alcoholism (NIAAA) (5U01AA026978). He has received grant support from General Electric, Gilead Sciences, AstraZeneca, Endra Life Sciences, financial support from Pfizer, Inc., in connection with this research and the development of this manuscript. His institution has had research contracts with Intercept, Pfizer, Galectin, Exact Sciences, Inventiva, Enanta, Shire, Gilead, Allergan, Celgene, Galmed, Rhythm, Madrigal, and Genentech. AB: None. KT: Employee and shareholder of Pfizer Inc. MJB:Grant support from Center for Disease Control (CDC), National Institute for Occupational Safety and Health (NIOSH), National Institute of Health (NIH) (NICATS and National Heart, Lung, and Blood Institute (NHLBI)), Patient-Centered Outcomes Research Institute (PCORI) (PaTH) and industry support from Owkin, Inc. MJB also is founder and has equity in SpIntellx, Inc. NC: None. CHC: none. SAF: none. DEF: none. DEF: none. HLK: none. RM: none. AP: none. JCS: Research grant contracts with Target Pharma Inc and Grifols. DAW: Consultant for Community Health Focus, Inc. and Swing Therapeutics, Inc. WTD: none. SKA: none. FN: Employee and shareholder of Pfizer Inc. MA: Employee and shareholder of Pfizer Inc. RHD: Employee and shareholder of Pfizer Inc. EM: Employee and shareholder of Pfizer Inc. KM: Grant support from NIH, PCORI, the American Heart Association, Eli Lilly, financial support from Pfizer, Inc., in connection with this research and the development of this manuscript and Janssen Pharmaceuticals.

Ethical approval

The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee(s) and with the Helsinki Declaration (as revised in 2013). Publication of this case report and accompanying images was waived from patient consent according to the University of Pittsburgh Human Research Protection Office, Johns Hopkins Medicine Institutional Review Boards, The Ohio State University Office of Responsible Research, University of Michigan Medical School Institutional Review Board (IRBMED), Geisinger Institutional Review Board, Institutional Review Board, Temple University Office of Research Integrity and Compliance, Pennsylvania State University Human Research Protection Program, University of Florida Institutional Review Board, and the Baylor University Human Research Protection Program.

Informed consent

The institutional review board at each participating site approved the study or deemed it eligible for waiver of informed consent as follows: University of Pittsburgh Human Research Protection Office The existing IRB protocol [STUDY19080151] in the University of Pittsburgh’s Human Research Protection Office provides regulatory oversight for specific uses of the PCORnet Common Data Model, including “ensuring that the Pittsburgh PaTH sited can provide high quality research data to support IRB authorized studies.” The PCORnet IRB was granted expedited approval, waiver of HIPAA authorization, and waiver of the consent process. The study described in this manuscript involved a data-only query and did not require an additional IRB application to the Human Research Protection Office as it falls under the existing “Use of PaTH Federated Research Network” IRB and is considered no greater than minimal risk. Johns Hopkins Medicine Institutional Review Boards The existing IRB protocol [IRB00051881: “PaTH Clinical Data Research Network (CDRN) Health Systems Database for Analysis of De-Identified Data,”] specifies, “A waiver of consent was granted based on the following criteria: (1) the research involves no more than minimal risk to subjects; (2) the waiver will not adversely affect the rights and welfare of the subjects; (3) the research could not be practicably carried out without the waiver; and (4) the IRB will advise you if it is appropriate for participants to be provided with additional pertinent information after participation.” The Ohio State University Office of Responsible Research The Ohio State University Office of Responsible Research maintains an approved protocol for PCORnet [Study: 2019H0123, “PCORI/PCORnet at Ohio State—Use of PaTH Federated Research Network”] that allows “researchers to request and access aggregate, de-identified and coded limited datasets without project specific IRB protocol approval or determination of exemption, and identifiable datasets inclusive of protected health information (PHI) with appropriate project-specific IRB review and approval.” There is a Waiver of Consent for the PCORnet IRB. University of Michigan Medical School Institutional Review Board (IRBMED) “The IRBMED determined that the proposed research repository does not meet the definition of ‘research involving human subjects’ under the Common Rule or FDA regulations. As such, no IRB oversight is required.” Geisinger Institutional Review Board The Geisinger Institutional Review Board has approved IRB #: 2015–180,“Clinical Data Analysis,” which applied to this study and states that “the proposal does not appear to involve ‘human subjects’ as defined in 45 CFR 46. 102(f); and therefore, is not subject to oversight by the Institutional Review Board.” Institutional Review Board, Temple University Office of Research Integrity and Compliance Protocol #24007–0005 for “PCORI Clinical Data Research Network (CDRN) Health Systems Database for Analysis of De-Identified Data” applied to this study and has been determined by the IRB to be “not human subjects research.” There was no requirement for IRB oversight or patient consent. Pennsylvania State University Human Research Protection Program STUDY0000643, “PaTH towards a Learning Health System for the Mid- Atlantic Region-PCORI Clinical Data Research Network (CDRN) Health Systems Database for Analysis of De-Identified Data,” covers the research activities of this study and states “The Human Subjects Protection Office determined that the proposed activity, as described in the above-referenced submission, does not meet the definition of human subject research as defined in 45 CFR 46.102(d) and/or (f). Institutional Review Board (IRB) review and approval is not required.” University of Florida Institutional Review Board Per IRB# IRB202003203, “This study is approved as exempt because it poses minimal risk and is approved under the following exempt category/categories: (4)(iii) Secondary research for which consent is not required: Secondary research uses of identifiable private information or identifiable biospecimens, if at least one of the following criteria is met: (iii) The research involves only information collection and analysis involving the investigator's use of identifiable health information when that use is regulated under 45 CFR parts 160 and 164, subparts A and E, for the purposes of “health care operations” or “research” as those terms are defined at 45 CFR 164.501 or for “public health activities and purposes” as described under 45 CFR 164.512(b).” Baylor University Human Research Protection Program IRB 021-130 “Non-Alcoholic Steatohepatitis (NASH) Risk Stratification Reference Number: 360000” was granted expedited review and approval “as it involves no greater than minimal risk to the subjects and fits into the following category from the 1998 approved list: Category 5: Research involving materials (data, documents, records, or specimens) that have been collected, or will be collected solely for nonresearch purposes (such as medical treatment or diagnosis).” Additionally, “The IRB has waived the requirement for informed consent based on 45 CFR 46.116 (f). The IRB has 1) waived the requirement for authorization based on 45 CFR 164.512 (i) (2) (ii) and 2) determined the use of existing protected health information is necessary to do the research.”

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Behari, J., Bradley, A., Townsend, K. et al. Limitations of Noninvasive Tests-Based Population-Level Risk Stratification Strategy for Nonalcoholic Fatty Liver Disease. Dig Dis Sci 69, 370–383 (2024). https://doi.org/10.1007/s10620-023-08186-8

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