UNLABELLED: Biopsy is still the gold standard for the diagnosis of nonalcoholic steatohepatitis but the definition may vary among pathologists, a drawback especially in evaluation of biopsies for clinical trials. We previously developed a scoring system (steatosis, activity, fibrosis [SAF]) allowing the use of an algorithm (fatty liver inhibition of progression [FLIP]) for the classification of liver injury in morbid obesity. The aim of this study was to determine whether the use of the SAF score and FLIP algorithm can decrease interobserver variations among pathologists. In a first session, pathologists categorized 40 liver biopsies of patients with nonalcoholic fatty liver disease (NAFLD) according to their own experience. In a second reading session, each pathologist reclassified the same slides by using the FLIP algorithm and SAF score, blinded to their first evaluation. The experiment was repeated with two different groups of pathologists at varying levels of training in liver pathology. The percentage of biopsy interpretation concordant with reference evaluation increased from 77% to 97% in Group 1 and from 42% to 75% in Group 2 after the use of the SAF score and FLIP algorithm. The strength of concordance in classification increased in Group 1 from moderate (κ = 0.54) to substantial (κ = 0.66) and from fair (κ = 0.35) to substantial (κ = 0.61) in Group 2 with application of the algorithm. With regard to the SAF score, concordance was substantial in Group 1 for steatosis (κ = 0.61), activity (κ = 0.75), and almost perfect for fibrosis (κ = 0.83 after pooling 1a, 1b, and 1c together into a single score F1). Similar trends were observed in Group 2 (κ = 0.54 for S, κ = 0.68 for A, and κ = 0.72 for F). CONCLUSION: The FLIP algorithm based on the SAF score should decrease interobserver variations among pathologists and are likely to be implemented in pathology practice.
UNLABELLED: Biopsy is still the gold standard for the diagnosis of nonalcoholic steatohepatitis but the definition may vary among pathologists, a drawback especially in evaluation of biopsies for clinical trials. We previously developed a scoring system (steatosis, activity, fibrosis [SAF]) allowing the use of an algorithm (fatty liver inhibition of progression [FLIP]) for the classification of liver injury in morbid obesity. The aim of this study was to determine whether the use of the SAF score and FLIP algorithm can decrease interobserver variations among pathologists. In a first session, pathologists categorized 40 liver biopsies of patients with nonalcoholic fatty liver disease (NAFLD) according to their own experience. In a second reading session, each pathologist reclassified the same slides by using the FLIP algorithm and SAF score, blinded to their first evaluation. The experiment was repeated with two different groups of pathologists at varying levels of training in liver pathology. The percentage of biopsy interpretation concordant with reference evaluation increased from 77% to 97% in Group 1 and from 42% to 75% in Group 2 after the use of the SAF score and FLIP algorithm. The strength of concordance in classification increased in Group 1 from moderate (κ = 0.54) to substantial (κ = 0.66) and from fair (κ = 0.35) to substantial (κ = 0.61) in Group 2 with application of the algorithm. With regard to the SAF score, concordance was substantial in Group 1 for steatosis (κ = 0.61), activity (κ = 0.75), and almost perfect for fibrosis (κ = 0.83 after pooling 1a, 1b, and 1c together into a single score F1). Similar trends were observed in Group 2 (κ = 0.54 for S, κ = 0.68 for A, and κ = 0.72 for F). CONCLUSION: The FLIP algorithm based on the SAF score should decrease interobserver variations among pathologists and are likely to be implemented in pathology practice.
Authors: Paul Angulo; David E Kleiner; Sanne Dam-Larsen; Leon A Adams; Einar S Bjornsson; Phunchai Charatcharoenwitthaya; Peter R Mills; Jill C Keach; Heather D Lafferty; Alisha Stahler; Svanhildur Haflidadottir; Flemming Bendtsen Journal: Gastroenterology Date: 2015-04-29 Impact factor: 22.682
Authors: Mohammed Eslam; Shiv K Sarin; Vincent Wai-Sun Wong; Jian-Gao Fan; Takumi Kawaguchi; Sang Hoon Ahn; Ming-Hua Zheng; Gamal Shiha; Yusuf Yilmaz; Rino Gani; Shahinul Alam; Yock Young Dan; Jia-Horng Kao; Saeed Hamid; Ian Homer Cua; Wah-Kheong Chan; Diana Payawal; Soek-Siam Tan; Tawesak Tanwandee; Leon A Adams; Manoj Kumar; Masao Omata; Jacob George Journal: Hepatol Int Date: 2020-10-01 Impact factor: 6.047
Authors: Y A Patel; E J Gifford; L M Glass; R McNeil; M J Turner; B Han; D Provenzale; S S Choi; C A Moylan; C M Hunt Journal: Aliment Pharmacol Ther Date: 2017-11-08 Impact factor: 8.171