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2011. 6.13. 소화기내과 김경엽 Gastroenterology 2011;140:1952-1960.

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Presentation on theme: "2011. 6.13. 소화기내과 김경엽 Gastroenterology 2011;140:1952-1960."— Presentation transcript:

1 2011. 6.13. 소화기내과 김경엽 Gastroenterology 2011;140:1952-1960

2 Background

3 Model for End Stage Liver Disease (MELD) –To predict mortality in patients undergoing transjugular intrahepatic portosystemic shunt (TIPS) procedures –Organ allocation in the United States MELD score = 11.2 x log e (INR) + 9.57 x log e (creatinine, mg/dL) + 3.78 x log e (bilirubin, mg/dL) + 6.43 The MELD system –15% reduction in mortality among wait-list registrants An updated MELD based on data from patients awaiting liver transplantation should improve mortality prediction and allocation efficiency

4 The addition of serum sodium (Na) improves survival prediction of the MELD score Scientific Registry of Transplant Recipients (SRTR) MELD –Derived and validated using SRTR data from 2001-2006 –Re-estimated coefficients of the MELD variables –Eliminated upper and low bounds for each variable –Update of the MELD coefficients –Improved concordance of model prediction across all subsets of MELD scores

5 Objectives

6 Based on the latest data -> optimized the MELD coefficients, including re-examination of the lower and upper bounds for individual variables Whether inclusion of Na concentration still adds value when it is considered in the context of the optimized model Compared the performance of the final optimized model with that of existing models, including the current MELD score, the MELDNa score, and the SRTR MELD score Main outcomes measure was ability to predict 90-day mortality of patients on the liver transplantation wait list

7 Materials and Methods

8 Patient Data Data were obtained from the Organ Procurement and Transplantation Network through the Standard Transplant Analysis and Research file All patients newly registered on the liver transplant waiting list Jan. 1, 2005 – Dec. 31, 2008 All adults with cirrhosis listed for a first liver transplantation

9 Exclusion –Age younger than 18 years –Previous liver transplantation –Status 1 for acute liver failure –Primary (ie, heatocellular carcinoma or cholangiocarcinoma) or metastatic hepatic malignancies Predictor variables –Bilirubin, creatinine, INR, Na Main outcomes variable –Death on the waiting list within 90 days of listing

10 Statistical Analysis 4 consecutive years of Organ Procurement and Transplantation Network data –Model derivation dataset (2005-2006) –Model validation dataset (2007-2008) Cox regression models evaluating mortality within 90 days based on the MELD variables

11 MELD score = 11.2 x log e (INR) + 9.57 x log e (creatinine, mg/dL) + 3.78 x log e (bilirubin, mg/dL) + 6.43 MELDNa score = MELD – Na – [0.025 x MELD x (140 – Na)] + 140 –Na: 125 – 140 mEq/L SRTR MELD score = 1.266 x log e (1 + creatinine) + 0.939 log e (1 + bilirubin) + 1. 658 log e (1 + INR)

12 Results

13 Patient characteristics Total 28,131 registrants on the waiting list for liver transplantation –14,190 in the model development set (2005-2006) –13,941 in the model validation set (2007-2008)

14 No clinically important differences in baseline characteristics between the derivation and validation cohorts

15 In the model derivation dataset (n=14,190) –7% died and 30% received a transplant within 90 days –64% remained on the waiting list 90 days after listing –20 (0.14%) withdrew from the list within 90 days In the model validation dataset (n=13,941) –7% died and 29% received a transplant within 90 days –64% remained on the waiting list 90 days after listing –38 (0.27%) withdrew from the list within 90 days

16 Optimizing the MELD Score Smoothing splines were used to determine the functional relationship between bilirubin, creatinine, and INR and the risk of death in the Cox model

17 A linear relationship in the Cox model with risk of death for a wide range of bilirubin values. The significance of bilirubin below the level of 1 mg/dL is questionable. Figure 1. The relation between risk of 90-day mortality and individual Model for End Stage Liver Disease (MELD) variables

18 0.8 Figure 1. The relation between risk of 90-day mortality and individual Model for End Stage Liver Disease (MELD) variables

19 Current MELD –Creatinine: 1.0 – 4.0 mg/dL ReFit MELD –Creatinine: 0.8 – 3.0 mg/dL This change would affect 2.2% of patients, who had serum creatinine > 3.0 mg/dL, but less than the previous bound of 4.0 mg/dL

20 Figure 1. The relation between risk of 90-day mortality and individual Model for End Stage Liver Disease (MELD) variables A new upper bound of 3.0 for INR

21 Current MELD –INR: 1.0 – ReFit MELD –INR: 1.0 – 3.0 This change would affect 3.6% of patients on the wait list

22 MELD score = 11.2 x log e (INR) + 9.57 x log e (creatinine, mg/dL) + 3.78 x log e (bilirubin, mg/dL) + 6.43 ReFit MELD score = 10.671 x log e (INR c ) + 8.485 x log e (creatinine c, mg/dL) + 4.082 x log e (bilirubin c, mg/dL) + 7.432 bilirubin c = bilirubin bounded below by 1 mg/dL c creatinine c = creatinine capped by 0.8 mg/dL below and 3 mg/dL above patients receiving renal replacement therapy = Cr 3 mg/dL INR c = INR bounded by 1 below and 3 above

23 Incorporation of Na: ReFit MELDNa 125

24 Significant interaction between sodium and bilirubin –Serum bilirubin ↑ -> impact of Na on mortaliry ↓ –This interaction was most pronounced when serum bilirubin was between 1 and 20 mg/dL

25 Validation of ReFit MELD and ReFit MELDNa in comparison with existing models

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29 Projected Impact of Utilizing ReFit MELDNa for Liver Allocation n=459 n=3,357 n=459n=10,125

30 Thus, implementation of the new score will affect 3.3% (459 of 13,941) of all wait-list registrants and 12.0% (459 of 3816) of all transplantations The 90-day Kaplan-Meier probability of mortality in the group than would be missed by the existing MELD but picked up by the refit MELDNa (left uper quadrant) was 15.6% compared to 7.2% in those who would have been favored by the existing MELD (log rank test P <.01) 324 deaths under the existing MELD vs. 295 under refit MELDNa within 90 days (P <.01)

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