Indra Neil Guha1, Rebecca Harris2, Sarah Berhane3, Audrey Dillon4, Lisa Coffey5, Martin W James2, Alessandro Cucchetti6, David J Harman2, Guruprasad P Aithal2, Omar Elshaarawy7, Imad Waked7, Stephen Stewart5, Philip J Johnson4. 1. NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust And University Of Nottingham, Nottingham, United Kingdom. Electronic address: neil.guha@nottingham.ac.uk. 2. NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust And University Of Nottingham, Nottingham, United Kingdom. 3. Department of Statistics, University of Liverpool, Liverpool, United Kingdom. 4. Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, United Kingdom. 5. Centre for Liver Disease, Mater Misericordiae University Hospital, Dublin, Ireland. 6. Department of Medical and Surgical Sciences, Alma Mater Studiorum, University of Bologna, Morgagni-Pierantoni Hospital, Forlì, Italy. 7. Hepatology & Gastroenterology Department, National Liver Institute, Menoufia University, Al Minufya, Egypt.
Abstract
BACKGROUND & AIMS: It is important to rapidly identify patients with advanced liver disease. Routine tests to assess liver function and fibrosis provide data that can be used to determine patients' prognoses. We tested the validated the ability of combined data from the ALBI and FIB-4 scoring systems to identify patients with compensated cirrhosis at highest risk for decompensation. METHODS: We collected data from 145 patients with compensated cirrhosis (91% Child A cirrhosis and median MELD scores below 8) from a cohort in Nottingham, United Kingdom, followed for a median 4.59 years (development cohort). We collected baseline clinical features and recorded decompensation events. We used these data to develop a model based on liver function (assessed by the ALBI score) and extent of fibrosis (assessed by the FIB-4 index) to determine risk of decompensation. We validated the model in 2 independent external cohorts (1 in Dublin, Ireland and 1 in Menoufia, Egypt) comprising 234 patients. RESULTS: In the development cohort, 19.3% of the patients developed decompensated cirrhosis. Using a combination of ALBI and FIB-4 scores, we developed a model that identified patients at low vs high risk of decompensation (hazard ratio [HR] for decompensation in patients with high risk score was 7.10). When we tested the scoring system in the validation cohorts, the HR for decompensation in patients with a high-risk score was 12.54 in the Ireland cohort and 5.10 in the Egypt cohort. CONCLUSION: We developed scoring system, based on a combination of ALBI and FIB-4 scores, that identifies patients at risk for liver decompensation. We validated the scoring system in 2 independent international cohorts (Europe and the Middle East), so it appears to apply to diverse populations.
BACKGROUND & AIMS: It is important to rapidly identify patients with advanced liver disease. Routine tests to assess liver function and fibrosis provide data that can be used to determine patients' prognoses. We tested the validated the ability of combined data from the ALBI and FIB-4 scoring systems to identify patients with compensated cirrhosis at highest risk for decompensation. METHODS: We collected data from 145 patients with compensated cirrhosis (91% Child A cirrhosis and median MELD scores below 8) from a cohort in Nottingham, United Kingdom, followed for a median 4.59 years (development cohort). We collected baseline clinical features and recorded decompensation events. We used these data to develop a model based on liver function (assessed by the ALBI score) and extent of fibrosis (assessed by the FIB-4 index) to determine risk of decompensation. We validated the model in 2 independent external cohorts (1 in Dublin, Ireland and 1 in Menoufia, Egypt) comprising 234 patients. RESULTS: In the development cohort, 19.3% of the patients developed decompensated cirrhosis. Using a combination of ALBI and FIB-4 scores, we developed a model that identified patients at low vs high risk of decompensation (hazard ratio [HR] for decompensation in patients with high risk score was 7.10). When we tested the scoring system in the validation cohorts, the HR for decompensation in patients with a high-risk score was 12.54 in the Ireland cohort and 5.10 in the Egypt cohort. CONCLUSION: We developed scoring system, based on a combination of ALBI and FIB-4 scores, that identifies patients at risk for liver decompensation. We validated the scoring system in 2 independent international cohorts (Europe and the Middle East), so it appears to apply to diverse populations.
Authors: Tongqi Qian; Naoto Fujiwara; Bhuvaneswari Koneru; Atsushi Ono; Naoto Kubota; Arun K Jajoriya; Matthew G Tung; Emilie Crouchet; Won-Min Song; Cesia Ammi Marquez; Gayatri Panda; Ayaka Hoshida; Indu Raman; Quan-Zhen Li; Cheryl Lewis; Adam Yopp; Nicole E Rich; Amit G Singal; Shigeki Nakagawa; Nicolas Goossens; Takaaki Higashi; Anna P Koh; C Billie Bian; Hiroki Hoshida; Parissa Tabrizian; Ganesh Gunasekaran; Sander Florman; Myron E Schwarz; Spiros P Hiotis; Takashi Nakahara; Hiroshi Aikata; Eisuke Murakami; Toru Beppu; Hideo Baba; Sangeeta Bhatia; Masahiro Kobayashi; Hiromitsu Kumada; Austin J Fobar; Neehar D Parikh; Jorge A Marrero; Steve Hategekimana Rwema; Venugopalan Nair; Manishkumar Patel; Seunghee Kim-Schulze; Kathleen Corey; Jacqueline G O'Leary; Goran B Klintmalm; David L Thomas; Mohammed Dibas; Gerardo Rodriguez; Bin Zhang; Scott L Friedman; Thomas F Baumert; Bryan C Fuchs; Kazuaki Chayama; Shijia Zhu; Raymond T Chung; Yujin Hoshida Journal: Gastroenterology Date: 2021-12-22 Impact factor: 33.883
Authors: Hamish Innes; Alex J Walker; Jennifer Benselin; Jane I Grove; Vincent Pedergnana; M Azim Ansari; Shang-Kuan Lin; John McLauchlan; Sharon J Hutchinson; Eleanor Barnes; William L Irving; Indra Neil Guha Journal: Clin Transl Gastroenterol Date: 2022-02-09 Impact factor: 4.396