TY - UNPB
T1 - Proactive case-finding and risk-stratification in people at risk of chronic liver disease in Greater Manchester:
T2 - a cost-effectiveness analysis
AU - Rogers, Gabriel
AU - Landi, Stephanie
AU - Purssell, Huw
AU - Momoh, Tonia
AU - Yates, Sol
AU - Street, Oliver
AU - Hanley, Karen Piper
AU - Hanley, Neil
AU - Athwal, Varinder
AU - Payne, Katherine
PY - 2025/6/2
Y1 - 2025/6/2
N2 - Background: We urgently need innovative strategies to combat a growing epidemic of chronic liver disease (CLD). ID-LIVER was a collaborative project aiming to improve detection of reversible-stage CLD in a region with high prevalence of critical risk factors. Objective: To determine the cost-effectiveness of ways to identify people with significant CLD, including proactive case-finding in the community (supplementing reactive referrals
from primary care) and/or risk-stratification (using FIB-4 or ID-LIVER-ML -- a novel machine-learning risk-stratification tool).
AB - Background: We urgently need innovative strategies to combat a growing epidemic of chronic liver disease (CLD). ID-LIVER was a collaborative project aiming to improve detection of reversible-stage CLD in a region with high prevalence of critical risk factors. Objective: To determine the cost-effectiveness of ways to identify people with significant CLD, including proactive case-finding in the community (supplementing reactive referrals
from primary care) and/or risk-stratification (using FIB-4 or ID-LIVER-ML -- a novel machine-learning risk-stratification tool).
UR - https://doi.org/10.1101/2025.06.01.25328671
U2 - 10.1101/2025.06.01.25328671
DO - 10.1101/2025.06.01.25328671
M3 - Preprint
SP - 1
EP - 27
BT - Proactive case-finding and risk-stratification in people at risk of chronic liver disease in Greater Manchester:
ER -