Use of rapid Model for End-Stage Liver Disease (MELD) increases for liver transplant registrant prioritization after MELD-Na and Share 35, an evaluation using data from the United Network for Organ Sharing

• Published in: PloS one 2019-10, Vol.14 (10), p.e0223053-e0223053
• Main Authors: Brock, Guy N, Washburn, Kenneth, Marvin, Michael R
• Format: Article
• Language: English
• Subjects: Accounting; Adult; Biology and Life Sciences; Calibration; Carcinoma; Care and treatment; Decision support systems; Diabetes; End Stage Liver Disease - blood; Hepatocellular carcinoma; Hepatology; Hospital waiting lists; Humans; Incidence; Liver; Liver cancer; Liver cirrhosis; Liver diseases; Liver failure; Liver Transplantation; Liver transplants; Management; Medicine and Health Sciences; Models, Theoretical; Mortality; Multivariate Analysis; Organ transplantation; Patient care; Patient Dropouts; Procurement policy; Registries; Social Sciences; Sodium; Sodium - blood; Studies; Surgeons; Surgery; Tissue and Organ Procurement; Transplantation; Transplants & implants; Waiting Lists
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0223053

The Model for End-Stage Liver Disease (MELD) score has been successfully used to prioritize patients on the United States liver transplant waiting list since its adoption in 2002. The United Network for Organ Sharing (UNOS)/Organ Procurement Transplantation Network (OPTN) allocation policy has evolved over the years, and notable recent changes include Share 35, inclusion of serum sodium in the MELD score, and a 'delay and cap' policy for hepatocellular carcinoma (HCC) patients. We explored the potential of a registrant's change in 30-day MELD scores (ΔMELD30) to improve allocation both before and after these policy changes. Current MELD and ΔMELD30 were evaluated using cause-specific hazards models for waitlist dropout based on US liver transplant registrants added to the waitlist between 06/30/2003 and 6/30/2013. Two composite scores were constructed and then evaluated on UNOS data spanning the current policy era (01/02/2016 to 09/07/2018). Predictive accuracy was evaluated using the C-index for model discrimination and by comparing observed and predicted waitlist dropout probabilities for model calibration. After the change to MELD-Na, increased dropout associated with ΔMELD30 jumps is no longer evident at MELD scores below 30. However, the adoption of Share 35 has potentially resulted in discrepancies in waitlist dropout for patients with sharp MELD increases at higher MELD scores. Use of the ΔMELD30 to add additional points or serve as a potential tiebreaker for patients with rapid deterioration may extend the benefit of Share 35 to better include those in most critical need.