Living Donor Liver TransplantationPREDICTLDLTNCT07383194
Prediction Models for LDLT Outcomes
An observational study of Living Donor Liver Transplantation, run by Erasmus Medical Center at 1 site in Netherlands.
Trial 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. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Living Donor Liver Transplantation
- What is being tested?
- Living donor liver transplantation
- Type of treatment
- Surgery or procedure
- How many people
- 3,000 participants
- Where
- 1 siteNetherlands
- Study dates
- 10 Mar 2026to 2 Jul 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: The study population consists of living liver donors and their corresponding recipients recorded in the International LDLT registry.
Who may be able to join
- All LDLT donor-recipient pairs registered in the International LDLT Registry from September 1, 2023 to present.
Who cannot join
- Two stage LDLT
- Dual grafts LDLT
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Netherlands1 site
Erasmus Medical Center
Rotterdam, South Holland, 3015 GD
Hayo W. ter Burg, MD, +316 83233210, h.terburg@erasmusmc.nl
About this study
Official title: A Clinically Applicable Prediction Model for Living Donor Liver Transplantation Outcomes Using the International LDLT Registry
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.
Read more
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.
Read the detailed description
Research questions:
- Can a new preoperative prediction model based on donor- and recipient-related variables be developed using the International LDLT Registry to reliably predict LDLT outcomes?
- How do the most promising existing prediction models for LDLT outcomes perform when externally validated in the International LDLT Registry?
Sample size calculation:
Sample size for prediction model development was estimated using an events-per-parameter (EPP/EPV) approach. Based on previous research, the anticipated event rate for early graft failure was set at 17.5%. We prespecified 20 model parameters (including dummy variables for categorical predictors and any interaction terms) and targeted 15 events per parameter to reduce overfitting. This yields a minimum of 300 events, corresponding to a total sample size of approximately 1,715 patients.
Statistical Analysis:
Statistical analyses will be carried out using RStudio 2024.09.1, GraphPad Prism 10.6.1, and Microsoft Excel version 16.90.2. P <0.05 indicates statistical significance.
Normality will be tested using the Shapiro-Wilk test. Baseline characteristics will be divided based on the presence of early graft failure. Homogeneity of variances will be tested using the F-test. These results will be presented in a table.
For external validation of existing prediction models, parameters will be entered in the prediction models resulting in the predicted risks. Model discrimination will be measured using the 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 (binary outcome). A multivariable logistic regression model will be developed to estimate the individual risk of early graft failure. Candidate predictors will be selected a priori based on clinical relevance, biological plausibility, and availability before transplantation, informed by existing literature and expert opinion. To reduce the risk of overfitting, the number of model parameters will be limited to approximately 20, in accordance with an events-per-parameter approach. Data-driven predictor selection procedures will be avoided. 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 the following subgroups: recipient sex, recipient continent of residence, indication for liver transplantation, actual donor hepatectomy performed, and approach to donor hepatectomy.
- Conditions
- Living Donor Liver Transplantation
- Being tested
- Living donor liver transplantation
- Keywords
- Liver Transplantation, Living Donor, Graft Survival, Mortality, Prediction Algorithms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Living donor liver transplantationProcedure or surgery
Also called Live donor liver transplantation, Living donor hepatectomy
Donors who underwent living donor hepatectomy and recipients who underwent living donor liver transplantation.
| Study group | Role | What they receive |
|---|---|---|
| Living liver donors and recipients | The study population consists of living liver donors and their corresponding recipients recorded in the International LDLT registry. Receives: Procedure: Living donor liver transplantation |
What is being measured
The primary outcome is the main question the study is designed to answer.
LDLT prediction model
The primary outcome is a new, clinically applicable prediction model for LDLT outcomes.
Measured: From initiation of LDLT-screening until 1 year post-donation
Secondary outcomes (1)
External validity existing prediction models
The secondary outcome is the external validity of the most promising existing prediction models for LDLT outcomes extracted from the literature. This is assessed using the area under the curve from a receiver operating characteristic curve.
Measured: From initiation of LDLT-screening until 1 year post-donation
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted3 Feb 2026
- Study start10 Mar 2026 (estimated)
- Primary completion1 Jul 2026 (estimated)
- Study completion2 Jul 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (6)Papers the sponsor has linked to this study.
- Other trials for Living Donor Liver TransplantationStudies of the same condition, open and under way.
- More trials run by Erasmus Medical CenterThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 3,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Erasmus Medical Center
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Robert Minnee, Erasmus Medical Center
- Investigators
- Robert C. Minnee, MD, PhD, MSc, Principal investigator, Erasmus Medical Center
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07383194
- Sponsor's protocol ID
- PREDICTLDLT
- Acronym
- PREDICTLDLT
- Status last verified
- Jan 2026
- First submitted
- 15 Jan 2026
- Last updated
- 3 Feb 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Study protocol, data management plan, data analysis plan, script to assess data, scripts to analyze data, scripts to generate tables and figures in the publication.
Publications
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.
PubMed 35124188Li 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 Jul 1;32(7):1027-1039. doi: 10.1097/LVT.0000000000000816. Epub 2026 Feb 10.
PubMed 41564353Li 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.
PubMed 39883022Babu 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.
PubMed 28819092Giglio 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.
PubMed 38079264Goldberg 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.
PubMed 25042283
Study at a glance
From the registry record, last updated by the sponsor on 3 Feb 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Clinically Applicable Prediction Model for Living Donor Liver Transplantation Outcomes Using the International LDLT Registry
- ClinicalTrials.gov ID
- NCT07383194
- Acronym / sponsor ID
- PREDICTLDLT / PREDICTLDLT
- Conditions
- Living Donor Liver Transplantation
- Keywords
- Liver Transplantation, Living Donor, Graft Survival, Mortality, Prediction Algorithms
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 3,000 participants (estimated)
- Lead sponsor
- Erasmus Medical CenterUniversity, hospital or other
- Study start
- 10 Mar 2026 (estimated)
- Primary completion
- 1 Jul 2026 (estimated)
- Study completion
- 2 Jul 2027 (estimated)
- First posted
- 3 Feb 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
Research questions:
- Can a new preoperative prediction model based on donor- and recipient-related variables be developed using the International LDLT Registry to reliably predict LDLT outcomes?
- How do the most promising existing prediction models for LDLT outcomes perform when externally validated in the International LDLT Registry?
Sample size calculation:
Sample size for prediction model development was estimated using an events-per-parameter (EPP/EPV) approach. Based on previous research, the anticipated event rate for early graft failure was set at 17.5%. We prespecified 20 model parameters (including dummy variables for categorical predictors and any interaction terms) and targeted 15 events per parameter to reduce overfitting. This yields a minimum of 300 events, corresponding to a total sample size of approximately 1,715 patients.
Statistical Analysis:
Statistical analyses will be carried out using RStudio 2024.09.1, GraphPad Prism 10.6.1, and Microsoft Excel version 16.90.2. P <0.05 indicates statistical significance.
Normality will be tested using the Shapiro-Wilk test. Baseline characteristics will be divided based on the presence of early graft failure. Homogeneity of variances will be tested using the F-test. These results will be presented in a table.
For external validation of existing prediction models, parameters will be entered in the prediction models resulting in the predicted risks. Model discrimination will be measured using the 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 (binary outcome). A multivariable logistic regression model will be developed to estimate the individual risk of early graft failure. Candidate predictors will be selected a priori based on clinical relevance, biological plausibility, and availability before transplantation, informed by existing literature and expert opinion. To reduce the risk of overfitting, the number of model parameters will be limited to approximately 20, in accordance with an events-per-parameter approach. Data-driven predictor selection procedures will be avoided. 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 the following subgroups: recipient sex, recipient continent of residence, indication for liver transplantation, actual donor hepatectomy performed, and approach to donor hepatectomy.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Living liver donors and recipients | – | Procedure: Living donor liver transplantationThe study population consists of living liver donors and their corresponding recipients recorded in the International LDLT registry. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- The study population consists of living liver donors and their corresponding recipients recorded in the International LDLT registry.
Key inclusion criteria (1 listed)
- All LDLT donor-recipient pairs registered in the International LDLT Registry from September 1, 2023 to present.
Key exclusion criteria (2 listed)
- Two stage LDLT
- Dual grafts LDLT
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Living donor liver transplantationAlso: Live donor liver transplantation, Living donor hepatectomyDonors who underwent living donor hepatectomy and recipients who underwent living donor liver transplantation. | Procedure or surgery | Living liver donors and recipients |
Primary outcome
LDLT prediction model
Time frame: From initiation of LDLT-screening until 1 year post-donation
The primary outcome is a new, clinically applicable prediction model for LDLT outcomes.
1 secondary outcome
External validity existing prediction models
Time frame: From initiation of LDLT-screening until 1 year post-donation
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 3 Feb 2026.
- Background: PubMed 35124188Haller 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.
- Background: PubMed 41564353Li 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 Jul 1;32(7):1027-1039. doi: 10.1097/LVT.0000000000000816. Epub 2026 Feb 10.
- Background: PubMed 39883022Li 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.
- Background: PubMed 28819092Babu 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.
- Background: PubMed 38079264Giglio 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.
- Background: PubMed 25042283Goldberg 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.
- Related InfoLink provided by the sponsor.
- Individual participant dataSharing planned: Yes. Study protocol, data management plan, data analysis plan, script to assess data, scripts to analyze data, scripts to generate tables and figures in the publication.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Robert C. Minnee, MD, PhD, MSc principal investigator
Erasmus Medical Center
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Living Donor Liver Transplantation, run by Erasmus Medical Center at 1 site in Netherlands.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 3 Feb 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Netherlands. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Hayo W. ter Burg, MD, MSc (+316 83233210, h.terburg@erasmusmc.nl), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
LDLT prediction model (time frame: From initiation of LDLT-screening until 1 year post-donation). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07383194, which also lists 6 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 3 Feb 2026.