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Prognostic Abilities and Quality Assessment of Models for the Prediction of 90-Day Mortality in Liver Transplant Waiting List Patients

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Background Model of end-stage liver disease (MELD)-score and diverse variants are widely used for prognosis on liver transplant waiting-lists. Methods 818 consecutive patients on the liver transplant waiting-list included to… Click to show full abstract

Background Model of end-stage liver disease (MELD)-score and diverse variants are widely used for prognosis on liver transplant waiting-lists. Methods 818 consecutive patients on the liver transplant waiting-list included to calculate the MELD, MESO Index, MELD-Na, UKELD, iMELD, refitMELD, refitMELD-Na, upMELD and PELD-scores. Prognostic abilities for 90-day mortality were investigated applying Receiver-operating-characteristic-curve analysis. Independent risk factors for 90-day mortality were identified with multivariable binary logistic regression modelling. Methodological quality of the underlying development studies was assessed with a systematic assessment tool. Results 74 patients (9%) died on the liver transplant waiting list within 90 days after listing. All but one scores, refitMELD-Na, had acceptable prognostic performance with areas under the ROC-curves (AUROCs)>0.700. The iMELD performed best (AUROC = 0.798). In pediatric cases, the PELD-score just failed to reach the acceptable threshold with an AUROC = 0.699. All scores reached a mean quality score of 72.3%. Highest quality scores could be achieved by the UKELD and PELD-scores. Studies specifically lack statistical validity and model evaluation. Conclusions Inferior quality assessment of prognostic models does not necessarily imply inferior prognostic abilities. The iMELD might be a more reliable tool representing urgency of transplantation than the MELD-score. PELD-score is assumedly not accurate enough to allow graft allocation decision in pediatric liver transplantation.

Keywords: quality; prognostic abilities; waiting list; liver transplant; day mortality; transplant waiting

Journal Title: PLoS ONE
Year Published: 2017

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