Prediction Models for LDLT Outcomes

NCT07383194 | Not Yet Recruiting DMC

• 1 other identifier: PREDICTLDLT
• Study Type: observational
• Target: 3,000
• Locations: 1 country
• Sites: 1

Brief Summary

Rationale: Living donor liver transplantation (LDLT) has emerged as an important option for patients with end-stage liver disease. To facilitate international and meaningful comparisons, our institution participates in the International LDLT Registry. Several models to predict outcomes post-LDLT have been developed to council and justify the major surgery that the living liver donors undergo. However, most proposed models are at high risk of bias and demonstrate suboptimal discriminative ability. This study aims to externally validate the most promising prediction models and subsequently, develop a new, clinically applicable prediction model for LDLT outcomes, using the International LDLT Registry. Objective(s): The main objective of this study is to develop a new, clinically applicable prediction model for LDLT outcomes, using the International LDLT Registry. The secondary objective is to externally validate the most promising existing prediction models for LDLT outcomes, using the International LDLT Registry. Study type: This is an observational, multicenter cohort study using prospectively collected data from the International LDLT Registry. Registry data will be analyzed retrospectively for the purposes of external model validation and prediction model development. Study population: The study population consists of living liver donors and their corresponding recipients recorded in the International LDLT registry. Methods: For external validation, parameters will be entered in the existing prediction models resulting in the predicted risks. Model discrimination will be measured using the area under the curve (AUC) and by the discrimination slope. The DeLong test will be used to test for difference between the AUC of the different prediction models. Calibration will be evaluated by comparing the observed with the predicted rate of events and graphically represented by calibration plots. For the development of a new prediction model, the outcome of interest is early graft failure, defined as graft loss within 90 days after transplantation. A multivariable logistic regression model will be developed to estimate the individual risk of early graft failure. Internal validation will be performed using bootstrapping, and model performance will be assessed in terms of discrimination and calibration. Model performance will also be tested in subgroups.

Conditions

Living Donor Liver Transplantation

Keywords

Liver Transplantation; Living Donor; Graft Survival; Mortality; Prediction Algorithms

Outcome Measures

Primary Outcomes (1)

• LDLT prediction model

  The primary outcome is a new, clinically applicable prediction model for LDLT outcomes.

  From initiation of LDLT-screening until 1 year post-donation

Secondary Outcomes (1)

• External validity existing prediction models

  From initiation of LDLT-screening until 1 year post-donation

Study Arms (1)

Living liver donors and recipients

The study population consists of living liver donors and their corresponding recipients recorded in the International LDLT registry.

Procedure: Living donor liver transplantation

Interventions

Living donor liver transplantation PROCEDURE

Donors who underwent living donor hepatectomy and recipients who underwent living donor liver transplantation.

Also known as: Live donor liver transplantation, Living donor hepatectomy

Living liver donors and recipients

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The study population consists of living liver donors and their corresponding recipients recorded in the International LDLT registry.

You may qualify if:

• \- All LDLT donor-recipient pairs registered in the International LDLT Registry from September 1, 2023 to present.

You may not qualify if:

• Two stage LDLT
• Dual grafts LDLT

Sponsors & Collaborators

• Erasmus Medical Center: lead

Study Sites (1)

Erasmus Medical Center

Rotterdam, South Holland, 3015 GD, Netherlands

Location

Related Publications (6)

• Haller MC, Aschauer C, Wallisch C, Leffondre K, van Smeden M, Oberbauer R, Heinze G. Prediction models for living organ transplantation are poorly developed, reported, and validated: a systematic review. J Clin Epidemiol. 2022 May;145:126-135. doi: 10.1016/j.jclinepi.2022.01.025. Epub 2022 Feb 4.

  PMID: 35124188 BACKGROUND

• Li Z, Centonze L, Raptis D, Marquez KAH, Rammohan A, Gunasekaran V, Hong S, Chen IC, Kim J, Hsu SC, Kirimker EO, Akamatsu N, Shaked O, Finotti M, Yeow M, Genedy L, Dutkowski P, Nadalin S, Boehnert MU, Polak WG, Bonney GK, Mathur A, Samstein B, Emond JC, Testa G, Olthoff KM, Heimbach JK, Taner T, Wong TCL, Hasegawa K, Balci D, Cattral M, Sapisochin G, Selzner N, Jeng LB, Joh JW, Chen CL, Suh KS, Di Sandro S, Rela M, Broering D, Clavien PA. Early graft failure after adult living donor liver transplantation: A multicenter risk analysis and development of the early allograft failure in living donor liver transplantation (EAGLE-LDLT) model. Liver Transpl. 2026 Jan 21. doi: 10.1097/LVT.0000000000000816. Online ahead of print.

  PMID: 41564353 BACKGROUND

• Li Z, Raptis D, Rammohan A, Gunasekaran V, Hong S, Chen IC, Kim J, Hervera Marquez KA, Hsu SC, Kirimker EO, Akamatsu N, Shaked O, Finotti M, Yeow M, Genedy L, Braun J, Yebyo H, Dutkowski P, Nadalin S, Boehnert MU, Polak WG, Bonney GK, Mathur A, Samstein B, Emond JC, Testa G, Olthoff KM, Rosen CB, Heimbach JK, Taner T, Wong TC, Lo CM, Hasegawa K, Balci D, Cattral M, Sapisochin G, Selzner N, Jeng LB, Joh JW, Chen CL, Suh KS, Rela M, Broering D, Clavien PA. Validation of a Pretransplant Risk Prediction Model for Early Allograft Dysfunction After Living-donor Liver Transplantation. Transplantation. 2025 Aug 1;109(8):1383-1392. doi: 10.1097/TP.0000000000005331. Epub 2025 Jan 28.

  PMID: 39883022 BACKGROUND

• Babu R, Sethi P, Surendran S, Dhar P, Gopalakrishnan U, Balakrishnan D, Menon RN, Sivasankarapillai Thankamonyamma B, Othiyil Vayoth S, Thillai M. A New Score to Predict Recipient Mortality from Preoperative Donor and Recipient Characteristics in Living Donor Liver Transplantation (DORMAT Score). Ann Transplant. 2017 Aug 18;22:499-506. doi: 10.12659/aot.904350.

  PMID: 28819092 BACKGROUND

• Giglio MC, Dolce P, Yilmaz S, Tokat Y, Acarli K, Kilic M, Zeytunlu M, Unek T, Karam V, Adam R, Polak WG, Fondevila C, Nadalin S, Troisi RI; European Liver and Intestine Transplant Association (ELITA). Development of a model to predict the risk of early graft failure after adult-to-adult living donor liver transplantation: An ELTR study. Liver Transpl. 2024 Aug 1;30(8):835-847. doi: 10.1097/LVT.0000000000000312. Epub 2023 Dec 12.

  PMID: 38079264 BACKGROUND

• Goldberg DS, French B, Abt PL, Olthoff K, Shaked A. Superior survival using living donors and donor-recipient matching using a novel living donor risk index. Hepatology. 2014 Nov;60(5):1717-26. doi: 10.1002/hep.27307. Epub 2014 Oct 2.

  PMID: 25042283 BACKGROUND

Related Links

• Related Info

Study Officials

• Robert C. Minnee, MD, PhD, MSc

  Erasmus Medical Center

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Hayo W. ter Burg, MD, MSc

CONTACT

+316 83233210; h.terburg@erasmusmc.nl

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator, Hepato-Pancreato-Biliary/Transplant Surgeon, Epidemiologist

Study Record Dates

• First Submitted: January 15, 2026
• First Posted: February 3, 2026
• Study Start: March 10, 2026
• Primary Completion (Estimated): July 1, 2026
• Study Completion (Estimated): July 2, 2027
• Last Updated: February 3, 2026

Record last verified: 2026-01

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ANALYTIC CODE
• Time Frame: (Underlying) data will be made available alongside with the publication. It will be available for 10 years. Access to the data and images is approved by the head of department and principal investigator. This access is temporarily. To whom and when access is approved is registered. Access to the registry can be requested by contacting the International LDLT registry (LDLTregistry.org).
• Access Criteria: The PI will verify the authenticity of the requesting researcher and will check whether the intended methodology is suitable and will approve the request before providing access to the data. Other researchers could express their interest in the dataset through countersigned DTA. After meeting the sharing and reuse conditions as described above and approval of the PI, data access will be provided through the data repository.

Locations

NL (1)