Developing a prognostic model for 90-day mortality after liver transplantation based on pretransplant recipient factors.
BACKGROUND
Current statistical prognostic models for mortality after liver transplantation do not have good discriminatory ability. Furthermore, the methodology used to develop these models is often flawed. The objective of this paper is to develop a prognostic model for 90-day mortality after liver transplantation based on pretransplant recipient factors, employing a rigorous model development method.


METHODS
We used data on 4,829 patient that were prospectively collected for the UK & Ireland Liver Transplant Audit. Switching regression was employed to impute missing values combined with a bootstrapping approach for variable selection.


RESULTS
In all, 452 patients (9.4%) died within 90 days of their transplantation. The final prognostic model was well calibrated and discriminated moderately well between patients who did and who did not die (c-statistic 0.65, 95% CI [0.63, 0.68]). Although discrimination was not excellent overall, the results showed that those patients with a "low" chance of dying within 90 days of their transplant and those with a "high" chance of dying could be differentiated from patients with a "intermediate" chance.


CONCLUSIONS
Our model can provide transplant candidates with predictions of their early posttransplantation prospects before any donor information is known, which is essential information for patients with end-stage liver disease for whom liver transplantation is a treatment option.
Lewsey
James D
JD
Health Services Research Unit, London School of Hygiene and Tropical Medicine, London, UK. james.lewsey@lshtm.ac.uk
Dawwas
Muhammad
M
Copley
Lynn P
LP
Gimson
Alexander
A
Van der Meulen
Jan H P
JH
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005006:Ethnicity; D005260:Female; D006801:Humans; D008107:Liver Diseases / Q000145:classification* / Q000601:surgery*; D016031:Liver Transplantation / Q000401:mortality*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011379:Prognosis; D016019:Survival Analysis