Revising model for end-stage liver disease from calendar-time cross-sections with correction for selection bias

Hans de Ferrante (Corresponding author), Marieke van Rosmalen, Bart M.L. Smeulders, Serge Vogelaar, Frits C.R. Spieksma

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Abstract

Background: Eurotransplant liver transplant candidates are prioritized by Model for End-stage Liver Disease (MELD), a 90-day waitlist survival risk score based on the INR, creatinine and bilirubin. Several studies revised the original MELD score, UNOS-MELD, with transplant candidate data by modelling 90-day waitlist mortality from waitlist registration, censoring patients at delisting or transplantation. This approach ignores biomarkers reported after registration, and ignores informative censoring by transplantation and delisting. Methods: We study how MELD revision is affected by revision from calendar-time cross-sections and correction for informative censoring with inverse probability censoring weighting (IPCW). For this, we revised UNOS-MELD on patients with chronic liver cirrhosis on the Eurotransplant waitlist between 2007 and 2019 (n = 13,274) with Cox models with as endpoints 90-day survival (a) from registration and (b) from weekly drawn calendar-time cross-sections. We refer to the revised score from cross-section with IPCW as DynReMELD, and compare DynReMELD to UNOS-MELD and ReMELD, a prior revision of UNOS-MELD for Eurotransplant, in geographical validation. Results: Revising MELD from calendar-time cross-sections leads to significantly different MELD coefficients. IPCW increases estimates of absolute 90-day waitlist mortality risks by approximately 10 percentage points. DynReMELD has improved discrimination over UNOS-MELD (delta c-index: 0.0040, p < 0.001) and ReMELD (delta c-index: 0.0015, p < 0.01), with differences comparable in magnitude to the addition of an extra biomarker to MELD (delta c-index: ± 0.0030). Conclusion: Correcting for selection bias by transplantation/delisting does not improve discrimination of revised MELD scores, but substantially increases estimated absolute 90-day mortality risks. Revision from cross-section uses waitlist data more efficiently, and improves discrimination compared to revision of MELD exclusively based on information available at listing.

Original languageEnglish
Article number51
Number of pages10
JournalBMC Medical Research Methodology
Volume24
DOIs
Publication statusPublished - Feb 2024

Funding

The research of H.C. de Ferrante and F.C.R. Spieksma was partly funded by the Netherlands Organization for Scientific Research (NWO) through Gravitation grant NETWORKS 024.002.003. The funding bodies played no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

FundersFunder number
Nederlandse Organisatie voor Wetenschappelijk OnderzoekNETWORKS 024.002.003
Nederlandse Organisatie voor Wetenschappelijk Onderzoek

    Keywords

    • MELD
    • Liver Allocation
    • Severity of Illness Index
    • Liver Transplantation
    • Humans
    • Risk Factors
    • End Stage Liver Disease/surgery
    • Selection Bias
    • Waiting Lists
    • Dependent censoring
    • Inverse probability censoring weighting
    • Chronic liver cirrhosis
    • Partly conditional models
    • Informative censoring
    • Landmarking
    • Liver allocation
    • Eurotransplant
    • Urgency-based liver allocation

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