Surasak Saokaew1,2,3, Shada Kanchanasuwan4, Piyaporn Apisarnthanarak5, Aphinya Charoensak5, Phunchai Charatcharoenwitthaya6, Pochamana Phisalprapa7, Nathorn Chaiyakunapruk2,3,8,9. 1. Center of Health Outcomes Research and Therapeutic Safety (Cohorts), School of Pharmaceutical Sciences, University of Phayao, Phayao, Thailand. 2. School of Pharmacy, Monash University Malaysia, Selangor, Malaysia. 3. Center of Pharmaceutical Outcomes Research (CPOR), Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Naresuan University, Phitsanulok, Thailand. 4. Clinical and Administrative Pharmacy, The University of Georgia College of Pharmacy, Athens, GA, USA. 5. Department of Radiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand. 6. Division of Gastroenterology, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand. 7. Division of Ambulatory Medicine, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand. 8. School of Pharmacy, University of Wisconsin, Madison, WI, USA. 9. School of Population Health, University of Queensland, Brisbane, Qld, Australia.
Abstract
BACKGROUND & AIMS: 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). METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
BACKGROUND & AIMS: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). METHODS: 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. RESULTS: 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. CONCLUSIONS: 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: Weerachai Srivanichakorn; Ian F Godsland; Chaiwat Washirasaksiri; Pochamana Phisalprapa; Phunchai Charatcharoenwitthaya; Pornpoj Pramyothin; Tullaya Sitasuwan; Lukana Preechasuk; Robert Elkeles; K George Mm Alberti; Desmond G Johnston; Nick S Oliver Journal: J Diabetes Investig Date: 2018-11-30 Impact factor: 4.232