Clinical trial NCT04861012: Screening for Metabolic Dysfunction Associated Fatty Liver Disease (MAFLD) at Al-Rajhy Hospital Nutrition Clinic. Assiut, Egypt
Official title: Screening for Metabolic Dysfunction Associated Fatty Liver Disease (MAFLD) at Al-Rajhy Hospital Nutrition Clinic
Study type: INTERVENTIONAL
Overall status: UNKNOWN
Phase: NA
Conditions: Steatohepatitis, Nonalcoholic
Keywords: MAFLD
Lead sponsor: Assiut University
Sponsor class: OTHER
First posted: 2021-04-27
Enrollment: 360
Sex: ALL
Minimum age (years): 18
Maximum age (years): 80
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: NA
Intervention model: SINGLE_GROUP
Primary purpose: SCREENING

Brief summary: Primary outcome Screen for MAFLD among patients attending to the Nutrition clinic in Al Rajhi hospital.

Secondary outcome

* Determining the degrees of fibrosis and steatosis in patients with MAFLD
* Determining the rate of obesity, diabetes mellitus (DM), hypertension (HTN), hyperlipidemia in patients with MAFLD.
* Determining the rate of patients with other associated chronic liver disease (CLD).

Detailed description: Metabolic dysfunction-associated fatty liver disease (MAFLD) formly called non alcoholic fatty liver disease (NAFLD) was defined as the presence of macrovesicular steatosis in ≥5% of hepatocytes in individuals who consume little or no alcohol. NAFLD was divided into two major subtypes: nonalcoholic fatty liver, and Non alcoholic steatohepatitis (NASH).

It is now believed that MAFLD is due to state of systemic metabolic dysfunction and is perceived as standalone disease that warrants positive diagnosis rather than simply a disease of exclusion. MAFLD affects about quarter of the world's population and it is now considered a public health issue.

Real time ultrasound (US) scanning is accepted as the first line imaging investigation in patients with suspected liver disorders. In spite insufficient sensitivity to detect liver inflammation and fibrosis, it demonstrates a good correlation with histological finding of fatty infiltration.

Another tool used for detection of fatty liver is fatty liver index (FLI) which is an algorithm based on waist circumference, body mass index (BMI), triglyceride, and gamma-glutamyl-transferase (GGT). A FLI \< 30 (negative likelihood ratio = 0.2) rules out and a FLI ≥ 60 (positive likelihood ratio = 4.3) rules in fatty liver. FLI had an accuracy of 0.84 (95% confidence interval (CI) 0.81-0.87) in detecting fatty liver.

Haung X, et al, 2015 found that FLI achieves a high sensitivity of 79.89% and a specificity of 71.51% for diagnosis of NAFLD.

TE (transient elastography) is a non-invasive ultrasound-based method that uses shear wave velocity to assess tissue (e.g., liver) stiffness. It has been applied in medical practice under the name FibroScan®.

Based on the physical characteristics (velocity and intensity attenuation) of the shear wave, the acquired data in the examination are processed and displayed on the screen as the liver stiffness measurement (LSM) and controlled attenuation parameter (CAP).

LSM values range from 1.5 to 75 kPa; lower values indicate a more elastic liver. CAP values range from 100 to 400 dB/m, and higher numbers indicate more pronounced steatosis.

A meta-analysis in 2014 has indicated that TE is excellent in diagnosing F ≥ 3 (85% sensitivity, 82% specificity) and F4 (92% sensitivity, 92% specificity), and it has a moderate accuracy for F ≥ 2 in NAFLD patients.

According to various studies, compared to liver biopsy, CAP is useful in the detection of S ≥ 1, S ≥ 2, and S3 (where S0 indicates no steatosis, to S3, which indicates the highest level of steatosis steatosis) because of its good sensitivity and specificity; however, the exact cut-off values remain to be defined.

Sample size estimation:

To assess the prevalence of MAFLD in, a prospective cross-sectional study was conducted. Based on previous studies (24), the expected frequency of MAFLD in Egypt is 37%. For a two-sided 95% confidence interval for a single proportion using the large sample normal approximation that will extend 5 % from the expected proportion, a sample size of 360 participant will be recruited. The sample will be equally represented from urban and rural areas. Sample size estimation was performed by Epi Info statistical package (Dean A, 1990).

Dean A (1990). Epi Info, Version 5.01. US Department of Health and Human Services, Public Health Service, Centers for Disease Control; 1990.

Statistical methods Data management and analysis will be performed using Statistical Package for Social Sciences (SPSS) vs. 25. Numerical data were summarized using means and standard deviations or medians, interquartile ranges and/or ranges, as appropriate. Categorical data were summarized as numbers and percentages. Estimates of the frequency of different grade of severity of NAFLD in the entire sample and will be done using the numbers and percentages. Numerical data were explored for normality using Kolmogrov-Smirnov test and Shapiro-Wilk test. The severity of fatty liver will be related to different serological risk factors of metabolic syndrome and diseases progression.

Chi square or Fisher's tests will be used to compare between the groups with respect to categorical data, as appropriate. Comparisons between two groups for normally distributed numeric variables will be done using the Student's t-test while for non-normally distributed numeric variables, comparisons will be done by Mann-Whitney test. Comparisons between more than 2 groups will be performed by the one analysis of variance (ANOVA) for normally distributed variables and Kruskal-Wallis for non-normally distributed variables, then followed by post hoc if needed. To measure the strength of association between the normally distributed numerical measurements, Pearson's correlation coefficients will be computed. Spearman's correlation coefficients will be calculated for non-normally distributed variables. All tests are two-sided. P-values \< 0.05 is considered significant.

Eligibility criteria: Inclusion Criteria:

* Age: 18-80 years

Exclusion Criteria:

* Pregnant females.
* Patients who will refuse to participate in the study.

Primary outcomes:
measure: Screen for MAFLD among patients attending to the Nutrition clinic in Al Rajhi hospital
timeFrame: baseline
Secondary outcomes:
measure: determining the number of patients diagnosed as MAFLD and degree of fibrosis and steatosis in each one.
timeFrame: baseline
measure: Determining the rate of patients with other associated chronic liver disease(CLD)
timeFrame: baseline
measure: Determining the rate of obesity, DM, HTN, hyperlipidemia in patients with MAFLD
timeFrame: baseline
Other outcomes:
Locations:
Study officials:
affiliation: Assiut University
name: Sherif Kamel, Professor
role: STUDY_DIRECTOR
affiliation: Assiut University
name: Mohammed Medhat, Lecturer
role: STUDY_DIRECTOR
References:
citation: Adams LA, Lymp JF, St Sauver J, Sanderson SO, Lindor KD, Feldstein A, Angulo P. The natural history of nonalcoholic fatty liver disease: a population-based cohort study. Gastroenterology. 2005 Jul;129(1):113-21. doi: 10.1053/j.gastro.2005.04.014.
citation: Matteoni CA, Younossi ZM, Gramlich T, Boparai N, Liu YC, McCullough AJ. Nonalcoholic fatty liver disease: a spectrum of clinical and pathological severity. Gastroenterology. 1999 Jun;116(6):1413-9. doi: 10.1016/s0016-5085(99)70506-8.
citation: Eslam M, Newsome PN, Sarin SK, Anstee QM, Targher G, Romero-Gomez M, Zelber-Sagi S, Wai-Sun Wong V, Dufour JF, Schattenberg JM, Kawaguchi T, Arrese M, Valenti L, Shiha G, Tiribelli C, Yki-Jarvinen H, Fan JG, Gronbaek H, Yilmaz Y, Cortez-Pinto H, Oliveira CP, Bedossa P, Adams LA, Zheng MH, Fouad Y, Chan WK, Mendez-Sanchez N, Ahn SH, Castera L, Bugianesi E, Ratziu V, George J. A new definition for metabolic dysfunction-associated fatty liver disease: An international expert consensus statement. J Hepatol. 2020 Jul;73(1):202-209. doi: 10.1016/j.jhep.2020.03.039. Epub 2020 Apr 8.
citation: Younossi Z, Anstee QM, Marietti M, Hardy T, Henry L, Eslam M, George J, Bugianesi E. Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nat Rev Gastroenterol Hepatol. 2018 Jan;15(1):11-20. doi: 10.1038/nrgastro.2017.109. Epub 2017 Sep 20.
citation: Sarin SK, Kumar M, Eslam M, George J, Al Mahtab M, Akbar SMF, Jia J, Tian Q, Aggarwal R, Muljono DH, Omata M, Ooka Y, Han KH, Lee HW, Jafri W, Butt AS, Chong CH, Lim SG, Pwu RF, Chen DS. Liver diseases in the Asia-Pacific region: a Lancet Gastroenterology & Hepatology Commission. Lancet Gastroenterol Hepatol. 2020 Feb;5(2):167-228. doi: 10.1016/S2468-1253(19)30342-5. Epub 2019 Dec 15.
citation: Hegazy M, Abo-Elfadl S, Mostafa A, Ibrahim M, Rashed L, Salman A. Serum Resistin Level and Its Receptor Gene Expression in Liver Biopsy as Predictors for the Severity of Nonalcoholic Fatty Liver Disease. Euroasian J Hepatogastroenterol. 2014 Jul-Dec;4(2):59-62. doi: 10.5005/jp-journals-10018-1102i. Epub 2014 Jul 28.
citation: Bedogni G, Bellentani S, Miglioli L, Masutti F, Passalacqua M, Castiglione A, Tiribelli C. The Fatty Liver Index: a simple and accurate predictor of hepatic steatosis in the general population. BMC Gastroenterol. 2006 Nov 2;6:33. doi: 10.1186/1471-230X-6-33.
citation: Huang X, Xu M, Chen Y, Peng K, Huang Y, Wang P, Ding L, Lin L, Xu Y, Chen Y, Lu J, Wang W, Bi Y, Ning G. Validation of the Fatty Liver Index for Nonalcoholic Fatty Liver Disease in Middle-Aged and Elderly Chinese. Medicine (Baltimore). 2015 Oct;94(40):e1682. doi: 10.1097/MD.0000000000001682.
citation: Sandrin L, Fourquet B, Hasquenoph JM, Yon S, Fournier C, Mal F, Christidis C, Ziol M, Poulet B, Kazemi F, Beaugrand M, Palau R. Transient elastography: a new noninvasive method for assessment of hepatic fibrosis. Ultrasound Med Biol. 2003 Dec;29(12):1705-13. doi: 10.1016/j.ultrasmedbio.2003.07.001.
citation: Castera L, Forns X, Alberti A. Non-invasive evaluation of liver fibrosis using transient elastography. J Hepatol. 2008 May;48(5):835-47. doi: 10.1016/j.jhep.2008.02.008. Epub 2008 Feb 26.
citation: Afdhal NH. Fibroscan (transient elastography) for the measurement of liver fibrosis. Gastroenterol Hepatol (N Y). 2012 Sep;8(9):605-7. No abstract available.
citation: Sandrin L, Tanter M, Gennisson JL, Catheline S, Fink M. Shear elasticity probe for soft tissues with 1-D transient elastography. IEEE Trans Ultrason Ferroelectr Freq Control. 2002 Apr;49(4):436-46. doi: 10.1109/58.996561.
citation: Gennisson JL, Deffieux T, Fink M, Tanter M. Ultrasound elastography: principles and techniques. Diagn Interv Imaging. 2013 May;94(5):487-95. doi: 10.1016/j.diii.2013.01.022. Epub 2013 Apr 22.
citation: Sasso M, Miette V, Sandrin L, Beaugrand M. The controlled attenuation parameter (CAP): a novel tool for the non-invasive evaluation of steatosis using Fibroscan. Clin Res Hepatol Gastroenterol. 2012 Feb;36(1):13-20. doi: 10.1016/j.clinre.2011.08.001. Epub 2011 Sep 15.
citation: Kwok R, Tse YK, Wong GL, Ha Y, Lee AU, Ngu MC, Chan HL, Wong VW. Systematic review with meta-analysis: non-invasive assessment of non-alcoholic fatty liver disease--the role of transient elastography and plasma cytokeratin-18 fragments. Aliment Pharmacol Ther. 2014 Feb;39(3):254-69. doi: 10.1111/apt.12569. Epub 2013 Dec 5.
citation: Sasso M, Beaugrand M, de Ledinghen V, Douvin C, Marcellin P, Poupon R, Sandrin L, Miette V. Controlled attenuation parameter (CAP): a novel VCTE guided ultrasonic attenuation measurement for the evaluation of hepatic steatosis: preliminary study and validation in a cohort of patients with chronic liver disease from various causes. Ultrasound Med Biol. 2010 Nov;36(11):1825-35. doi: 10.1016/j.ultrasmedbio.2010.07.005. Epub 2010 Sep 27.
citation: Imajo K, Kessoku T, Honda Y, Tomeno W, Ogawa Y, Mawatari H, Fujita K, Yoneda M, Taguri M, Hyogo H, Sumida Y, Ono M, Eguchi Y, Inoue T, Yamanaka T, Wada K, Saito S, Nakajima A. Magnetic Resonance Imaging More Accurately Classifies Steatosis and Fibrosis in Patients With Nonalcoholic Fatty Liver Disease Than Transient Elastography. Gastroenterology. 2016 Mar;150(3):626-637.e7. doi: 10.1053/j.gastro.2015.11.048. Epub 2015 Dec 8.
citation: Myers RP, Pollett A, Kirsch R, Pomier-Layrargues G, Beaton M, Levstik M, Duarte-Rojo A, Wong D, Crotty P, Elkashab M. Controlled Attenuation Parameter (CAP): a noninvasive method for the detection of hepatic steatosis based on transient elastography. Liver Int. 2012 Jul;32(6):902-10. doi: 10.1111/j.1478-3231.2012.02781.x. Epub 2012 Mar 21.
citation: de Ledinghen V, Vergniol J, Foucher J, Merrouche W, le Bail B. Non-invasive diagnosis of liver steatosis using controlled attenuation parameter (CAP) and transient elastography. Liver Int. 2012 Jul;32(6):911-8. doi: 10.1111/j.1478-3231.2012.02820.x.
citation: Kumar M, Rastogi A, Singh T, Behari C, Gupta E, Garg H, Kumar R, Bhatia V, Sarin SK. Controlled attenuation parameter for non-invasive assessment of hepatic steatosis: does etiology affect performance? J Gastroenterol Hepatol. 2013 Jul;28(7):1194-201. doi: 10.1111/jgh.12134.
citation: Shen F, Zheng RD, Mi YQ, Wang XY, Pan Q, Chen GY, Cao HX, Chen ML, Xu L, Chen JN, Cao Y, Zhang RN, Xu LM, Fan JG. Controlled attenuation parameter for non-invasive assessment of hepatic steatosis in Chinese patients. World J Gastroenterol. 2014 Apr 28;20(16):4702-11. doi: 10.3748/wjg.v20.i16.4702.
citation: Chan WK, Nik Mustapha NR, Mahadeva S. Controlled attenuation parameter for the detection and quantification of hepatic steatosis in nonalcoholic fatty liver disease. J Gastroenterol Hepatol. 2014;29(7):1470-6. doi: 10.1111/jgh.12557.
citation: Lupsor-Platon M, Feier D, Stefanescu H, Tamas A, Botan E, Sparchez Z, Maniu A, Badea R. Diagnostic accuracy of controlled attenuation parameter measured by transient elastography for the non-invasive assessment of liver steatosis: a prospective study. J Gastrointestin Liver Dis. 2015 Mar;24(1):35-42. doi: 10.15403/jgld.2014.1121.mlp.