Application of a biochemical and clinical model to predict individual survival in patients with end-stage liver disease.
OBJECTIVE
To investigate the capability of a biochemical and clinical model, BioCliM, in predicting the survival of cirrhotic patients.


METHODS
We prospectively evaluated the survival of 172 cirrhotic patients. The model was constructed using clinical (ascites, encephalopathy and variceal bleeding) and biochemical (serum creatinine and serum total bilirubin) variables that were selected from a Cox proportional hazards model. It was applied to estimate 12-, 52- and 104-wk survival. The model's calibration using the Hosmer-Lemeshow statistic was computed at 104 wk in a validation dataset. Finally, the model's validity was tested among an independent set of 85 patients who were stratified into 2 risk groups (low risk <or= 8 and high risk > 8).


RESULTS
In the validation cohort, all measures of fit, discrimination and calibration were improved when the biochemical and clinical model was used. The proposed model had better predictive values (c-statistic: 0.90, 0.91, 0.91) than the Model for End-stage Liver Disease (MELD) and Child-Pugh (CP) scores for 12-, 52- and 104-wk mortality, respectively. In addition, the Hosmer-Lemeshow (H-L) statistic revealed that the biochemical and clinical model (H-L, 4.69) is better calibrated than MELD (H-L, 17.06) and CP (H-L, 14.23). There were no significant differences between the observed and expected survival curves in the stratified risk groups (low risk, P = 0.61; high risk, P = 0.77).


CONCLUSIONS
Our data suggest that the proposed model is able to accurately predict survival in cirrhotic patients.
Gomez
Eduardo Vilar
EV
National Institute of Gastroenterology, Vedado, Havana, Cuba. vilar@infomed.sld.cu
Bertot
Luis Calzadilla
LC
Oramas
Bienvenido Gra
BG
Soler
Enrique Arus
EA
Navarro
Raimundo Llanio
RL
Elias
Javier Diaz
JD
Jiménez
Oscar Villa
OV
Abreu Vazquez
Maria del Rosario
Mdel R
D000328:Adult; D000368:Aged; D005260:Female; D006801:Humans; D017093:Liver Failure / Q000175:diagnosis / Q000401:mortality*; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D015999:Multivariate Analysis; D011379:Prognosis; D016016:Proportional Hazards Models; D011446:Prospective Studies; D015203:Reproducibility of Results; D012307:Risk Factors; D055815:Young Adult