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93


Does MELD-GRAIL-Na Correct Racial Disparities In Survival Without A Liver Transplant? [Meeting Abstract]

VanDerwerken, Doug; Wood, Nicholas; Segev, Dorry; Gentry, Sommer
ISI:000739470700067
ISSN: 1600-6135
CID: 5133582

Characterizing the early impact of the Kidney Accelerated Placement Project on hard-to-place kidneys [Meeting Abstract]

Motter, Jennifer; Kernodle, Amber; Gentry, Sommer; Levan, Macey; Wood, Nicholas; Segev, Dorry; Garonzik-Wang, Jacqueline; Massie, Allan
ISI:000739470700152
ISSN: 1600-6135
CID: 5133672

Increased Logistical Complexity In Circle-Based Organ Allocation [Meeting Abstract]

Wood, Nicholas; VanDerwerken, Douglas; Segev, Dorry; Gentry, Sommer
ISI:000739470700198
ISSN: 1600-6135
CID: 5133692

Opportunities for Improved Efficiency in Kidney Distribution: A Comparison of Center-Specified UNet Donor Criteria to Actual Kidney Acceptance Practices [Meeting Abstract]

Zeiser, Laura; Gentry, Sommer; Segev, Dorry; Massie, Allan
ISI:000739470700207
ISSN: 1600-6135
CID: 5133702

Designing Continuous Distribution for Liver Allocation. [Meeting Abstract]

Mankowski, M.; Wood, N.; Segev, D.; Gentry, S.
ISI:000842606302312
ISSN: 1600-6135
CID: 5486642

MELD 3.0: The Model for End-Stage Liver Disease Updated for the Modern Era

Kim, W Ray; Mannalithara, Ajitha; Heimbach, Julie K; Kamath, Patrick S; Asrani, Sumeet K; Biggins, Scott W; Wood, Nicholas L; Gentry, Sommer E; Kwong, Allison J
BACKGROUND & AIMS:The Model for End-Stage Liver Disease (MELD) has been established as a reliable indicator of short-term survival in patients with end-stage liver disease. The current version (MELDNa), consisting of the international normalized ratio and serum bilirubin, creatinine, and sodium, has been used to determine organ allocation priorities for liver transplantation in the United States. The objective was to optimize MELD further by taking into account additional variables and updating coefficients with contemporary data. METHODS:All candidates registered on the liver transplant wait list in the US national registry from January 2016 through December 2018 were included. Uni- and multivariable Cox models were developed to predict survival up to 90 days after wait list registration. Model fit was tested using the concordance statistic (C-statistic) and reclassification, and the Liver Simulated Allocation Model was used to estimate the impact of replacing MELDNa with the new model. RESULTS:The final multivariable model was characterized by (1) additional variables of female sex and serum albumin, (2) interactions between bilirubin and sodium and between albumin and creatinine, and (3) an upper bound for creatinine at 3.0 mg/dL. The final model (MELD 3.0) had better discrimination than MELDNa (C-statistic, 0.869 vs 0.862; P < .01). Importantly, MELD 3.0 correctly reclassified a net of 8.8% of decedents to a higher MELD tier, affording them a meaningfully higher chance of transplantation, particularly in women. In the Liver Simulated Allocation Model analysis, MELD 3.0 resulted in fewer wait list deaths compared to MELDNa (7788 vs 7850; P = .02). CONCLUSION:MELD 3.0 affords more accurate mortality prediction in general than MELDNa and addresses determinants of wait list outcomes, including the sex disparity.
PMCID:8608337
PMID: 34481845
ISSN: 1528-0012
CID: 5139432

Correcting the sex disparity in MELD-Na

Wood, Nicholas L; VanDerwerken, Douglas; Segev, Dorry L; Gentry, Sommer E
MELD-Na appears to disadvantage women awaiting liver transplant by underestimating their mortality rate. Fixing this problem involves: (1) estimating the magnitude of this disadvantage separately for each MELD-Na, (2) designing a correction for each MELD-Na, and (3) evaluating corrections to MELD-Na using simulated allocation. Using Kaplan-Meier modeling, we calculated 90-day without-transplant survival for men and women, separately at each MELD-Na. For most scores between 15 and 35, without-transplant survival was higher for men by 0-5 percentage points. We tested two proposed corrections to MELD-Na (MELD-Na-MDRD and MELD-GRAIL-Na), and one correction we developed (MELD-Na-Shift) to target the differences we quantified in survival across the MELD-Na spectrum. In terms of without-transplant survival, MELD-Na-MDRD overcorrected sex differences while MELD-GRAIL-Na and MELD-Na-Shift eliminated them. Estimating the impact of implementing these corrections with the liver simulated allocation model, we found that MELD-Na-Shift alone eliminated sex disparity in transplant rates (p = 0.4044) and mortality rates (p = 0.7070); transplant rates and mortality rates were overcorrected by MELD-Na-MDRD (p = 0.0025, p = 0.0006) and MELD-GRAIL-Na (p = 0.0079, p = 0.0005). We designed a corrected MELD-Na that eliminates sex disparities in without-transplant survival, but allocation changes directing smaller livers to shorter candidates may also be needed to equalize women's access to liver transplant.
PMID: 34174151
ISSN: 1600-6143
CID: 5127342

MELD is MELD is MELD? Transplant center-level variation in waitlist mortality for candidates with the same biological MELD

Ishaque, Tanveen; Kernodle, Amber B; Motter, Jennifer D; Jackson, Kyle R; Chiang, Teresa P; Getsin, Samantha; Boyarsky, Brian J; Garonzik-Wang, Jacqueline; Gentry, Sommer E; Segev, Dorry L; Massie, Allan B
Recently, model for end-stage liver disease (MELD)-based liver allocation in the United States has been questioned based on concerns that waitlist mortality for a given biologic MELD (bMELD), calculated using laboratory values alone, might be higher at certain centers in certain locations across the country. Therefore, we aimed to quantify the center-level variation in bMELD-predicted mortality risk. Using Scientific Registry of Transplant Recipients (SRTR) data from January 2015 to December 2019, we modeled mortality risk in 33 260 adult, first-time waitlisted candidates from 120 centers using multilevel Poisson regression, adjusting for sex, and time-varying age and bMELD. We calculated a "MELD correction factor" using each center's random intercept and bMELD coefficient. A MELD correction factor of +1 means that center's candidates have a higher-than-average bMELD-predicted mortality risk equivalent to 1 bMELD point. We found that the "MELD correction factor" median (IQR) was 0.03 (-0.47, 0.52), indicating almost no center-level variation. The number of centers with "MELD correction factors" within ±0.5 points, and between ±0.5-± 1, ±1.0-±1.5, and ±1.5-±2.0 points was 62, 41, 13, and 4, respectively. No centers had waitlisted candidates with a higher-than-average bMELD-predicted mortality risk beyond ±2 bMELD points. Given that bMELD similarly predicts waitlist mortality at centers across the country, our results support continued MELD-based prioritization of waitlisted candidates irrespective of center.
PMID: 33870635
ISSN: 1600-6143
CID: 5127132

Liver simulated allocation model does not effectively predict organ offer decisions for pediatric liver transplant candidates

Wood, Nicholas L; Mogul, Douglas B; Perito, Emily R; VanDerwerken, Douglas; Mazariegos, George V; Hsu, Evelyn K; Segev, Dorry L; Gentry, Sommer E
The SRTR maintains the liver-simulated allocation model (LSAM), a tool for estimating the impact of changes to liver allocation policy. Integral to LSAM is a model that predicts the decision to accept or decline a liver for transplant. LSAM implicitly assumes these decisions are made identically for adult and pediatric liver transplant (LT) candidates, which has not been previously validated. We applied LSAM's decision-making models to SRTR offer data from 2013 to 2016 to determine its efficacy for adult (≥18) and pediatric (<18) LT candidates, and pediatric subpopulations-teenagers (≥12 to <18), children (≥2 to <12), and infants (<2)-using the area under the receiver operating characteristic (ROC) curve (AUC). For nonstatus 1A candidates, all pediatric subgroups had higher rates of offer acceptance than adults. For non-1A candidates, LSAM's model performed substantially worse for pediatric candidates than adults (AUC 0.815 vs. 0.922); model performance decreased with age (AUC 0.898, 0.806, 0.783 for teenagers, children, and infants, respectively). For status 1A candidates, LSAM also performed worse for pediatric than adult candidates (AUC 0.711 vs. 0.779), especially for infants (AUC 0.618). To ensure pediatric candidates are not unpredictably or negatively impacted by allocation policy changes, we must explicitly account for pediatric-specific decision making in LSAM.
PMID: 33891805
ISSN: 1600-6143
CID: 5127152

The Precise Relationship Between Model for End-Stage Liver Disease and Survival Without a Liver Transplant

VanDerwerken, Douglas N; Wood, Nicholas L; Segev, Dorry L; Gentry, Sommer E
BACKGROUND AND AIMS:Scores from the Model for End-Stage Liver Disease (MELD), which are used to prioritize candidates for deceased donor livers, are widely acknowledged to be negatively correlated with the 90-day survival rate without a liver transplant. However, inconsistent and outdated estimates of survival probabilities by MELD preclude useful applications of the MELD score. APPROACH AND RESULTS:Using data from all prevalent liver waitlist candidates from 2016 to 2019, we estimated 3-day, 7-day, 14-day, 30-day, and 90-day without-transplant survival probabilities (with confidence intervals) for each MELD score and status 1A. We used an adjusted Kaplan-Meier model to avoid unrealistic assumptions and multiple observations per person instead of just the observation at listing. We found that 90-day without-transplant survival has improved over the last decade, with survival rates increasing >10% (in absolute terms) for some MELD scores. We demonstrated that MELD correctly prioritizes candidates in terms of without-transplant survival probability but that status 1A candidates' short-term without-transplant survival is higher than that of MELD 40 candidates and lower than that of MELD 39 candidates. Our primary result is the updated survival functions themselves. CONCLUSIONS:We calculated without-transplant survival probabilities for each MELD score (and status 1A). The survival function is an invaluable tool for many applications in liver transplantation: awarding of exception points, calculating the relative demand for deceased donor livers in different geographic areas, calibrating the pediatric end-stage liver disease score, and deciding whether to accept an offered liver.
PMID: 33655565
ISSN: 1527-3350
CID: 5127012