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A model for calculating the long-term estimated post-transplant survival of deceased donor liver transplant patients.
- Source :
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EBioMedicine [EBioMedicine] 2023 Apr; Vol. 90, pp. 104505. Date of Electronic Publication: 2023 Mar 02. - Publication Year :
- 2023
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Abstract
- Background: The estimated long-term survival (EPTS) score is used for kidney allocation. A comparable prognostic tool to accurately quantify EPTS benefit in deceased donor liver transplant (DDLT) candidates is nonexistent.<br />Methods: Using the Scientific Registry of Transplant Recipients (SRTR) database, we developed, calibrated, and validated a nonlinear regression equation to calculate liver-EPTS (L-EPTS) for 5- and 10-year outcomes in adult DDLT recipients. The population was randomly split (70:30) into two discovery (N = 26,372 and N = 46,329) and validation cohorts (N = 11,288 and N = 19,859) for 5- and 10-year post-transplant outcomes, respectively. Discovery cohorts were used for variable selection, Cox proportional hazard regression modeling, and nonlinear curve fitting. Eight clinical variables were selected to construct the L-EPTS formula, and a five-tiered ranking system was created.<br />Findings: Tier thresholds were defined and the L-EPTS model was calibrated (R <superscript>2</superscript>  = 0.96 [5-year] and 0.99 [10-year]). Patients' median survival probabilities in the discovery cohorts for 5- and 10-year outcomes ranged from 27.94% to 89.22% and 16.27% to 87.97%, respectively. The L-EPTS model was validated via calculation of receiver operating characteristic (ROC) curves using validation cohorts. Area under the ROC curve was 82.4% (5-year) and 86.5% (10-year).<br />Interpretation: L-EPTS has high applicability and clinical utility because it uses easily obtained pre-transplant patients characteristics to accurately discriminate between those who are likely to receive a prolonged survival benefit and those who are not. It is important to evaluate medical urgency alongside survival benefit and placement efficiency when considering the allocation of a scarce resource.<br />Funding: There are no funding sources related to this project.<br />Competing Interests: Declaration of interests No funding was used to support this work. The authors of this manuscript have no conflicts of interest to disclose as described by eBioMedicine.<br /> (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 2352-3964
- Volume :
- 90
- Database :
- MEDLINE
- Journal :
- EBioMedicine
- Publication Type :
- Academic Journal
- Accession number :
- 36870199
- Full Text :
- https://doi.org/10.1016/j.ebiom.2023.104505