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Cirrhosis, LiverNCT06531200

Building of Prognosis Model for Patients With Cirrhosis Based on Sarcopenia Assessed by Deep Learning

An observational study of Cirrhosis, Liver and Sarcopenia, run by Peking University People's Hospital.

Unknown status

Status not confirmed. The sponsor has not verified this record for over two years, so it may be out of date.

Official record
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Trial summary

The goal of this observational study is to develop and validate a fully automated imaging deep learning platform for the evaluation of sarcopenia in liver cirrhosis. Based on this model, a new prognostic model for liver cirrhosis incorporating imaging biomarkers such as sarcopenia will be constructed, and its… Read more about this study

Who is it for?
Ages 18 years and older
Conditions the study is for
Cirrhosis, Liver, Sarcopenia
How many people
1,000 participants
Where
No sites listed yet
Study dates
1 Sep 2024to 31 Dec 2025
Phase
Observational
Are there results?
None posted in the registry

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 18 years and older
  • All sexes
  • No healthy volunteers
  • Adult, Older adult

Study population: This study includes adults diagnosed with liver cirrhosis based on clinical criteria, liver biopsy confirming cirrhosis, or specific laboratory abnormalities (e.g., low platelet count, low serum albumin, high INR, or elevated APRI). Additionally, high-quality L3-level CT images must be available for each patient. Patients are excluded if they have incomplete data, a diagnosis or suspicion of malignancy, severe chronic diseases (such as kidney, respiratory, or cardiovascular conditions), neurological or muscular degenerative diseases, metabolic disorders (like thyroid diseases or tuberculosis), malabsorption conditions, or if they are undergoing treatment with glucocorticoids or immunosuppressants. Pregnant or lactating women are also excluded from the study.

Who may be able to join

  • Age ≥18 years
  • Diagnosis of liver cirrhosis, meeting at least one of the following criteria:
  • Clinical diagnosis: ICD-10-CM codes K74.100 and K74.607 from our hospital's electronic medical record system
  • Liver biopsy pathology or a combination of clinical, laboratory, and imaging examinations confirming liver cirrhosis: Pathological biopsy criteria: fibrosis bridging between lobules leading to lobular structural disarray, nodular regeneration of hepatocytes, formation of pseudo-lobules
  • Laboratory tests: the presence of at least 2 of the following 4 abnormal indicators suggesting liver cirrhosis:
  • a) Platelet count < 100×10^9/L, with no other explainable cause;
Show all 10Show fewer
  • b) Serum albumin < 35g/L, excluding malnutrition or kidney disease as other causes;
  • c) International normalized ratio (INR) > 1.3 or prolonged prothrombin time (PT) (after discontinuation of thrombolytic or anticoagulant drugs for more than 7 days);
  • d)Aspartate aminotransferase to platelet ratio index (APRI) > 2.
  • Availability of high-quality L3-level CT images

Who cannot join

  • Incomplete sociodemographic, laboratory, or imaging data
  • Diagnosed or highly suspected malignancy
  • Severe chronic kidney disease, respiratory insufficiency, cardiovascular diseases, etc.
  • Neurological diseases and muscular degenerative diseases
  • Hyperthyroidism, hypothyroidism, tuberculosis, or any other diseases that may affect basal metabolism
  • Diseases or conditions causing malabsorption of intestinal nutrients, such as inflammatory bowel disease or gastrointestinal surgery
  • Treatment with glucocorticoids or immunosuppressants
  • Pregnancy or lactation

Trial locations and contacts

No sites are listed yet.

Rui Huang, Dr. contact

86 10 66583771

strangehead@163.com

About this study

Official title: Building of Prognosis Model for Patients With Cirrhosis Based on Sarcopenia in Assessment With the Technology of Deep Learning

The goal of this observational study is to develop and validate a fully automated imaging deep learning platform for the evaluation of sarcopenia in liver cirrhosis. Based on this model, a new prognostic model for liver cirrhosis incorporating imaging biomarkers such as sarcopenia will be constructed, and its predictive performance will be validated.

Read the detailed description

The goal of this observational study is to collect clinical and abdominal imaging data of patients with liver cirrhosis. The collected imaging data will be used as a model development set to develop, test, and internally validate a fully automated imaging deep learning platform for the evaluation of sarcopenia in liver cirrhosis. Subsequently, relevant data from patients with liver cirrhosis at other centers will be collected and used as an external validation dataset. The model will be externally validated by abdominal radiology experts. Furthermore, we will include sociodemographic information, clinical data, imaging data, and clinical outcomes of the aforementioned liver cirrhosis patients to predict the prognosis of these patients using the established model. This model will be used to construct a new prognostic model for liver cirrhosis incorporating imaging biomarkers such as sarcopenia, and its predictive performance will be validated.

Keywords
deep learning, prognosis, sarcopenia, myosteatosis
Medical subject headings
Liver Cirrhosis, Sarcopenia

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Liver-related mortality

    Causes of liver disease-related mortality include: Hepatitis B virus infection, hepatitis C virus infection, alcohol-induced or toxic liver disease; complications related to liver cirrhosis: ascites or pleural effusion, esophagogastric variceal bleeding, spontaneous bacterial peritonitis or related infections, hepatic encephalopathy or other neuropsychiatric syndromes based on metabolic disorders, hepatorenal syndrome, hepatopulmonary syndrome; liver failure; hepatocellular carcinoma; death or liver transplantation.

    Measured: As of December 31, 2025

Secondary outcomes (1)

  1. All-cause Mortality

    Deaths caused by all reasons, including but not limited to those related to liver disease

    Measured: As of December 31, 2025

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted31 Jul 2024
  2. Study start1 Sep 2024 (estimated)
  3. Primary completion31 Aug 2025 (estimated)
  4. Study completion31 Dec 2025 (estimated)

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Observational
Observational model
Cohort
Time perspective
Prospective
Enrolment
1,000 participants (estimated)
IDs, dates and publications
ClinicalTrials.gov ID
NCT06531200
Sponsor's protocol ID
2023PHB214-001
Status last verified
Aug 2024
First submitted
28 Jul 2024
Last updated
6 Aug 2024
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No

Publications

  • Huang DQ, Terrault NA, Tacke F, Gluud LL, Arrese M, Bugianesi E, Loomba R. Global epidemiology of cirrhosis - aetiology, trends and predictions. Nat Rev Gastroenterol Hepatol. 2023 Jun;20(6):388-398. doi: 10.1038/s41575-023-00759-2. Epub 2023 Mar 28.

    PubMed 36977794

  • Zeng X, Shi ZW, Yu JJ, Wang LF, Luo YY, Jin SM, Zhang LY, Tan W, Shi PM, Yu H, Zhang CQ, Xie WF. Sarcopenia as a prognostic predictor of liver cirrhosis: a multicentre study in China. J Cachexia Sarcopenia Muscle. 2021 Dec;12(6):1948-1958. doi: 10.1002/jcsm.12797. Epub 2021 Sep 14.

    PubMed 34520115

  • Desai AP, Mohan P, Nokes B, Sheth D, Knapp S, Boustani M, Chalasani N, Fallon MB, Calhoun EA. Increasing Economic Burden in Hospitalized Patients With Cirrhosis: Analysis of a National Database. Clin Transl Gastroenterol. 2019 Jul;10(7):e00062. doi: 10.14309/ctg.0000000000000062.

    PubMed 31343469

  • Cruz-Jentoft AJ, Sayer AA. Sarcopenia. Lancet. 2019 Jun 29;393(10191):2636-2646. doi: 10.1016/S0140-6736(19)31138-9. Epub 2019 Jun 3.

    PubMed 31171417

  • Damluji AA, Alfaraidhy M, AlHajri N, Rohant NN, Kumar M, Al Malouf C, Bahrainy S, Ji Kwak M, Batchelor WB, Forman DE, Rich MW, Kirkpatrick J, Krishnaswami A, Alexander KP, Gerstenblith G, Cawthon P, deFilippi CR, Goyal P. Sarcopenia and Cardiovascular Diseases. Circulation. 2023 May 16;147(20):1534-1553. doi: 10.1161/CIRCULATIONAHA.123.064071. Epub 2023 May 15.

    PubMed 37186680

  • Sinn DH, Kang D, Kang M, Guallar E, Hong YS, Lee KH, Park J, Cho J, Gwak GY. Nonalcoholic fatty liver disease and accelerated loss of skeletal muscle mass: A longitudinal cohort study. Hepatology. 2022 Dec;76(6):1746-1754. doi: 10.1002/hep.32578. Epub 2022 Jun 10.

    PubMed 35588190

  • Han E, Lee YH, Kim BK, Park JY, Kim DY, Ahn SH, Lee BW, Kang ES, Cha BS, Han KH, Kim SU. Sarcopenia is associated with the risk of significant liver fibrosis in metabolically unhealthy subjects with chronic hepatitis B. Aliment Pharmacol Ther. 2018 Aug;48(3):300-312. doi: 10.1111/apt.14843. Epub 2018 Jun 19.

    PubMed 29920701

  • Davuluri G, Welch N, Sekar J, Gangadhariah M, Alsabbagh Alchirazi K, Mohan ML, Kumar A, Kant S, Thapaliya S, Stine M, McMullen MR, McCullough RL, Stark GR, Nagy LE, Naga Prasad SV, Dasarathy S. Activated Protein Phosphatase 2A Disrupts Nutrient Sensing Balance Between Mechanistic Target of Rapamycin Complex 1 and Adenosine Monophosphate-Activated Protein Kinase, Causing Sarcopenia in Alcohol-Associated Liver Disease. Hepatology. 2021 May;73(5):1892-1908. doi: 10.1002/hep.31524. Epub 2021 Apr 20.

    PubMed 32799332

  • Shafaat O, Liu Y, Jackson KR, Motter JD, Boyarsky BJ, Latif MA, Yuan F, Khalil A, King EA, Zaheer A, Summers RM, Segev DL, McAdams-DeMarco M, Weiss CR. Association between Abdominal CT Measurements of Body Composition before Deceased Donor Liver Transplant with Posttransplant Outcomes. Radiology. 2023 Mar;306(3):e212403. doi: 10.1148/radiol.212403. Epub 2022 Oct 25.

    PubMed 36283115

  • Dasarathy S, Merli M. Sarcopenia from mechanism to diagnosis and treatment in liver disease. J Hepatol. 2016 Dec;65(6):1232-1244. doi: 10.1016/j.jhep.2016.07.040. Epub 2016 Aug 8.

    PubMed 27515775

  • Kang SH, Jeong WK, Baik SK, Cha SH, Kim MY. Impact of sarcopenia on prognostic value of cirrhosis: going beyond the hepatic venous pressure gradient and MELD score. J Cachexia Sarcopenia Muscle. 2018 Oct;9(5):860-870. doi: 10.1002/jcsm.12333.

    PubMed 30371017

  • van Vugt JLA, Alferink LJM, Buettner S, Gaspersz MP, Bot D, Darwish Murad S, Feshtali S, van Ooijen PMA, Polak WG, Porte RJ, van Hoek B, van den Berg AP, Metselaar HJ, IJzermans JNM. A model including sarcopenia surpasses the MELD score in predicting waiting list mortality in cirrhotic liver transplant candidates: A competing risk analysis in a national cohort. J Hepatol. 2018 Apr;68(4):707-714. doi: 10.1016/j.jhep.2017.11.030. Epub 2017 Dec 6.

    PubMed 29221886

  • Bhanji RA, Moctezuma-Velazquez C, Duarte-Rojo A, Ebadi M, Ghosh S, Rose C, Montano-Loza AJ. Myosteatosis and sarcopenia are associated with hepatic encephalopathy in patients with cirrhosis. Hepatol Int. 2018 Jul;12(4):377-386. doi: 10.1007/s12072-018-9875-9. Epub 2018 Jun 7.

    PubMed 29881992

  • Tosato M, Marzetti E, Cesari M, Savera G, Miller RR, Bernabei R, Landi F, Calvani R. Measurement of muscle mass in sarcopenia: from imaging to biochemical markers. Aging Clin Exp Res. 2017 Feb;29(1):19-27. doi: 10.1007/s40520-016-0717-0. Epub 2017 Feb 7.

    PubMed 28176249

  • Prado CM, Heymsfield SB. Lean tissue imaging: a new era for nutritional assessment and intervention. JPEN J Parenter Enteral Nutr. 2014 Nov;38(8):940-53. doi: 10.1177/0148607114550189. Epub 2014 Sep 19.

    PubMed 25239112

Questions about this trial

What is this clinical trial studying?

An observational study of Cirrhosis, Liver and Sarcopenia, run by Peking University People's Hospital.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 10 inclusion and 8 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: status not confirmed, as of the sponsor's last update on 6 Aug 2024. Status can change between updates, so confirm with the study contact before making plans.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

Results are not available in the source record.

How can a doctor refer a patient or contact the research team?

Contact Rui Huang, Dr. (86 10 66583771, strangehead@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Liver-related mortality (time frame: As of December 31, 2025). It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT06531200, which also lists 29 linked publications.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 6 Aug 2024.

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