Predicting chance of liver transplantation for pediatric wait-list candidates

Xun Luo, Douglas B. Mogul, Allan B. Massie, Tanveen Ishaque, John F.P. Bridges, Dorry L. Segev

Research output: Contribution to journalArticle

Abstract

Information about wait-list time has been reported as one of the single most frequently asked questions by individuals awaiting a transplant but data regarding wait-list time have not been processed in a useful way for pediatric candidates. To predict chance of receiving a DDLT, we identified 6471 pediatric (<18 years), non status-1A, liver-only transplant candidates between 2006 and 2017 from the SRTR. Cox regression with shared frailty for DSA level effect was used to model the association of blood type, weight, allocation PELD and MELD, and DSA with chance of DDLT. Jackknife technique was used for validation. Median (interquartile range) wait-list time was 100 (34-309) days. Non-O Blood type, higher PELD/MELD score at listing, and DSA were associated with increased chance of DDLT, while age 1-5 years and 10-18 years was associated with lower chance of DDLT (P < 0.001 for all variables). Our model accurately predicted chance of transplant (C-statistic = 0.68) and was able to predict DDLT at specific follow-up times (eg, 3 months). This model can serve as the basis for an online tool that would provide useful information for pediatric wait-list candidates.

Original languageEnglish (US)
Pages (from-to)e13542
JournalPediatric transplantation
Volume23
Issue number7
DOIs
StatePublished - Nov 1 2019

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Liver Transplantation
Pediatrics
Transplants
Weights and Measures
Liver

Keywords

  • calculator
  • deceased donor liver transplant
  • pediatric
  • prediction

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health
  • Transplantation

Cite this

Predicting chance of liver transplantation for pediatric wait-list candidates. / Luo, Xun; Mogul, Douglas B.; Massie, Allan B.; Ishaque, Tanveen; Bridges, John F.P.; Segev, Dorry L.

In: Pediatric transplantation, Vol. 23, No. 7, 01.11.2019, p. e13542.

Research output: Contribution to journalArticle

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AU - Segev, Dorry L.

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