Predicting survival among patients listed for liver transplantation: an assessment of serial MELD measurements.
We examined whether consideration of repeated model for end-stage liver disease (MELD) measurements for patients listed for liver transplantation improves predictive value beyond current MELD alone. Clinical data were extracted for all adult primary liver transplantation candidates from our institution who were listed with the United Network for Organ Sharing (UNOS) between 1990 and 1999. Serum creatinine, bilirubin, and international normalized ratio (INR) were obtained from an institutional laboratory database. Cox models were constructed using current MELD, change in MELD (Delta), and number of MELD scores to predict survival on the waiting list. Eight hundred and sixty-one patients met inclusion criteria, 639 underwent transplantation, and 80 died while waiting. A one-unit increment in current MELD imparted significant hazard ratios ranging from 1.12 to 1.19 in all models. Delta MELD was predictive of mortality univariately, but less predictive when current MELD was included, and not predictive when considered with both current and number of MELD scores. Overall, current MELD is the single most important determinant of mortality risk on the waiting list. Delta MELD is predictive of death only within 4 d of the event; however, part of this correlates with the dying process itself, thus limiting Delta MELD's utility in survival prediction models.
Division of Gastroenterology and Hepatology, Mayo Clinic and Foundation, Rochester, MN, USA.
Kiran
K
Bambha
W Ray
WR
Kim
Walter K
WK
Kremers
Terry M
TM
Therneau
Patrick S
PS
Kamath
Russell
R
Wiesner
Charles B
CB
Rosen
Jeff
J
Thostenson
Joanne T
JT
Benson
E Rolland
ER
Dickson
D000328:Adult; D001663:Bilirubin / Q000097:blood; D003404:Creatinine / Q000097:blood; D005260:Female; D006801:Humans; D008107:Liver Diseases / Q000145:classification / Q000601:surgery; D016031:Liver Transplantation / Q000401:mortality / Q000502:physiology*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D015588:Observer Variation; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D012044:Regression Analysis; D012189:Retrospective Studies; D016019:Survival Analysis; D013997:Time Factors; D014850:Waiting Lists
D003404:Creatinine; D001663:Bilirubin