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Predicting survival after liver transplantation
Date:11/5/2007

e or more comorbidities prior to transplantation. After statistical analysis, the researchers found that coronary disease, diabetes, COPD, connective tissue disease, and renal insufficiency were all independent predictors of poorer post-transplant survival. The researchers then recalibrated the CCI using this information, to create the CCI-OLT. This new index predicted post-transplant survival as well or better than other available models which use recipient characteristics like age, race, BMI, and etiology of liver disease.

Our study shows that comorbidities play an important role in determining post-transplant survival, the authors report. This information will be useful when counseling patients with comorbidities about outcomes after transplantation.

The study was limited by the fact that it was a single center, retrospective cohort study, and the researchers were not able to determine to what extent the comorbidities were manifestations of advanced liver disease. Still, the researchers demonstrated the usefulness of the modified comorbidity index for predicting post-liver-transplant. In the future, they conclude, the addition of comorbidities to multivariable models may be useful in developing new allocation algorithms which incorporate the likelihood of post-transplant survival.

An accompanying editorial, by Richard Freeman of the New England Medical Center, lauds the authors for their novel approach, though he cautioned that it remains to be seen if these results can be replicated. He writes that it is also somewhat disappointing that the CCI-OLT index was no better at predicting outcome than most of the other models already published.

Still, he reports, the mathematical model present by Volk and colleagues, can help estimate ahead of time what might be correct choices for patients when the call comes in the middle of the night.


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Contact: Amy Molnar
amolnar@wiley.com
John Wiley & Sons, Inc.
Source:Eurekalert

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