title: Clinical risk scoring for predicting non-alcoholic fatty liver disease in metabolic syndrome patients (NAFLD-MS score).
abstract: Non-alcoholic fatty liver disease (NAFLD) can progress from simple steatosis to hepatocellular carcinoma. None of tools have been developed specifically for high-risk patients. This study aimed to develop a simple risk scoring to predict NAFLD in patients with metabolic syndrome (MetS).
  
  
  
  A total of 509 patients with MetS were recruited. All were diagnosed by clinicians with ultrasonography-confirmed whether they were patients with NAFLD. Patients were randomly divided into derivation (n=400) and validation (n=109) cohort. To develop the risk score, clinical risk indicators measured at the time of recruitment were built by logistic regression. Regression coefficients were transformed into item scores and added up to a total score. A risk scoring scheme was developed from clinical predictors: BMI ≥25, AST/ALT ≥1, ALT ≥40, type 2 diabetes mellitus and central obesity. The scoring scheme was applied in validation cohort to test the performance.
  
  
  
  The scheme explained, by area under the receiver operating characteristic curve (AuROC), 76.8% of being NAFLD with good calibration (Hosmer-Lemeshow χ2=4.35; P=.629). The positive likelihood ratio of NAFLD in patients with low risk (scores below 3) and high risk (scores 5 and over) were 2.32 (95% CI: 1.90-2.82) and 7.77 (95% CI: 2.47-24.47) respectively. When applied in validation cohort, the score showed good performance with AuROC 76.7%, and illustrated 84%, and 100% certainty in low- and high-risk groups respectively.
  
  
  
  A simple and non-invasive scoring scheme of five predictors provides good prediction indices for NAFLD in MetS patients. This scheme may help clinicians in order to take further appropriate action.
authors.affiliation: Center of Health Outcomes Research and Therapeutic Safety (Cohorts), School of Pharmaceutical Sciences, University of Phayao, Phayao, Thailand.|School of Pharmacy, Monash University Malaysia, Selangor, Malaysia.|Center of Pharmaceutical Outcomes Research (CPOR), Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Naresuan University, Phitsanulok, Thailand.
authors.forename: Surasak
authors.initials: S
authors.lastname: Saokaew
authors.affiliation: Clinical and Administrative Pharmacy, The University of Georgia College of Pharmacy, Athens, GA, USA.
authors.forename: Shada
authors.initials: S
authors.lastname: Kanchanasuwan
authors.affiliation: Department of Radiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
authors.forename: Piyaporn
authors.initials: P
authors.lastname: Apisarnthanarak
authors.affiliation: Department of Radiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
authors.forename: Aphinya
authors.initials: A
authors.lastname: Charoensak
authors.affiliation: Division of Gastroenterology, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
authors.forename: Phunchai
authors.initials: P
authors.lastname: Charatcharoenwitthaya
authors.affiliation: Division of Ambulatory Medicine, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
authors.forename: Pochamana
authors.identifier: 0000-0003-1995-4405
authors.initials: P
authors.lastname: Phisalprapa
authors.affiliation: School of Pharmacy, Monash University Malaysia, Selangor, Malaysia.|Center of Pharmaceutical Outcomes Research (CPOR), Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Naresuan University, Phitsanulok, Thailand.|School of Pharmacy, University of Wisconsin, Madison, WI, USA.|School of Population Health, University of Queensland, Brisbane, Qld, Australia.
authors.forename: Nathorn
authors.identifier: 0000-0001-6213-722X
authors.initials: N
authors.lastname: Chaiyakunapruk
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000410:Alanine Transaminase / Q000097:blood; D019540:Area Under Curve; D001219:Aspartate Aminotransferases / Q000097:blood; D015415:Biomarkers / Q000097:blood; D015992:Body Mass Index; D003661:Decision Support Techniques; D003924:Diabetes Mellitus, Type 2 / Q000150:complications / Q000175:diagnosis; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood / Q000150:complications* / Q000175:diagnosis; D008875:Middle Aged; D015999:Multivariate Analysis; D065626:Non-alcoholic Fatty Liver Disease / Q000000981:diagnostic imaging / Q000209:etiology*; D056128:Obesity, Abdominal / Q000150:complications / Q000175:diagnosis; D016017:Odds Ratio; D011237:Predictive Value of Tests; D012372:ROC Curve; D015203:Reproducibility of Results; D018570:Risk Assessment; D012307:Risk Factors
chemical_list: D015415:Biomarkers; D001219:Aspartate Aminotransferases; D000410:Alanine Transaminase
keywords: metabolic syndrome; non-alcoholic fatty liver disease; prediction; risk scoring