Dataset Information

Underreporting of liver transplant waitlist removals due to death or clinical deterioration: results at four major centers.

ABSTRACT: Few studies have evaluated the accuracy of United Network for Organ Sharing (UNOS) or Scientific Registry of Transplant Recipients data among patients listed for liver transplantation. Of particular importance for transplant policy and practice is whether patients' outcomes are coded properly.Using data from four transplant centers, we identified all liver transplant candidates removed from the waitlist from February 27, 2002 to July 24, 2010, with a specific focus the removal code of "other."Among nontransplanted patients at these centers, 2206 patients were removed for death or clinical deterioration. Of these, 8.6% (189 of 2206) were misclassified; they were assigned the UNOS removal code of "other." Among these 189 misclassified patients, 128 became medically unsuitable, 35 died, and 26 became too sick to transplant. Nearly one-half (46.8%) of misclassified patients were removed due to advanced hepatocellular carcinoma. Among true waitlist removals for death, only 35 of 1593 (2.2%) were misclassified. Conversely, of true removals for clinical deterioration, 154 of 612 (25.2%) were misclassified, with significant (P < 0.001) center variation: 4.4% (Baylor), 8.0% (Georgetown), 32.6% (University of Pennsylvania), and 45.0% (Mount Sinai). Extrapolating these data to the entire United States, if "other" patients who truly died or clinically deteriorated were recoded appropriately, there would be an additional 2525 (95% confidence interval, 2046-3102) patients removed from the waitlist due to death (331) or clinical deterioration (2194) since 2002.A substantial proportion of patients truly removed from the waitlist for death or clinical deterioration were misclassified as "other." Thus, analyses using the UNOS or the Scientific Registry of Transplant Recipients database may underestimate the true proportion of patients removed from the waitlist for clinical deterioration.

SUBMITTER: Goldberg D

PROVIDER: S-EPMC3715579 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature

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Underreporting of liver transplant waitlist removals due to death or clinical deterioration: results at four major centers.

Goldberg David D French Benjamin B Trotter James J Shetty Kirti K Schiano Thomas T Reddy K Rajender KR Halpern Scott D SD

Transplantation 20130701 2

<h4>Background</h4>Few studies have evaluated the accuracy of United Network for Organ Sharing (UNOS) or Scientific Registry of Transplant Recipients data among patients listed for liver transplantation. Of particular importance for transplant policy and practice is whether patients' outcomes are coded properly.<h4>Methods</h4>Using data from four transplant centers, we identified all liver transplant candidates removed from the waitlist from February 27, 2002 to July 24, 2010, with a specific f ...[more]

PMID: 23765112

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Project description:Liver allocation in the United States was updated on February 4, 2020, by introducing the acuity circle (AC)-based model. This study evaluated the early effects of the AC-based allocation on waitlist outcomes.MethodsAdult liver transplant (LT) candidates listed between January 1, 2019, and September 30, 2021, were assessed. Two periods were defined according to listing date (pre- and post-AC), and 90-d waitlist outcomes were compared. Median transplant Model for End-stage Liver Disease (MELD) score of each transplant center was calculated, with centers categorized as low- (<25 percentile), mid- (25-75 percentile), and high-MELD (>75 percentile) centers.ResultsA total of 12 421 and 17 078 LT candidates in the pre- and post-AC eras were identified. Overall, the post-AC era was associated with higher cause-specific 90-d hazards of transplant (csHR, 1.32; 95% confidence interval [CI], 1.27-1.38; P < 0.001) and waitlist mortality (cause-specific hazard ratio [csHR], 1.20; 95% CI, 1.09-1.32; P < 0.001). The latter effect was primarily driven by high-MELD centers. Low-MELD centers had a higher proportion of donations after circulatory death (DCDs) used. Compared with low-MELD centers, mid-MELD and high-MELD centers had significantly lower cause-specific hazards of DCD-LT in both eras (mid-MELD: csHR, 0.47; 95% CI, 0.38-0.59 in pre-AC and csHR, 0.56; 95% CI, 0.46-0.67 in post-AC and high-MELD: csHR, 0.11; 95% CI, 0.07-0.17 in pre-AC and csHR, 0.14; 95% CI, 0.10-0.20 in post-AC; all P < 0.001). Using a structural Bayesian time-series model, the AC policy was associated with an increase in the actual monthly DCD-LTs in low-, mid-, and high-MELD centers (actual/predicted: low-MELD: 19/16; mid-MELD: 21/14; high-MELD: 4/3), whereas the increase in monthly donation after brain death-LTs were only present in mid- and high-MELD centers.ConclusionsAlthough AC-based allocation may improve waitlist outcomes, regional variation exists in the drivers of such outcomes between centers.

Project description:BackgroundGeographic disparities in access to deceased donor kidney transplantation persist in the United States under the Kidney Allocation System (KAS) introduced in 2014, and the effect of transplant center practices on the probability of transplantation for wait-listed patients remains unclear.MethodsTo compare probability of transplantation across centers nationally and within donation service areas (DSAs), we conducted a registry study that included all United States incident adult kidney transplant candidates wait listed in 2011 and 2015 (pre-KAS and post-KAS cohorts comprising 32,745 and 34,728 individuals, respectively). For each center, we calculated the probability of deceased donor kidney transplantation within 3 years of wait listing using competing risk regression, with living donor transplantation, death, and waiting list removal as competing events. We examined associations between center-level and DSA-level characteristics and the adjusted probability of transplant.ResultsCandidates received deceased donor kidney transplants within 3 years of wait listing more frequently post-KAS (22%) than pre-KAS (19%). Nationally, the probability of transplant varied 16-fold between centers, ranging from 4.0% to 64.2% in the post-KAS era. Within DSAs, we observed a median 2.3-fold variation between centers, with up to ten-fold and 57.4 percentage point differences. Probability of transplantation was correlated in the post-KAS cohort with center willingness to accept hard-to-place kidneys (r=0.55, P<0.001) and local organ supply (r=0.44, P<0.001).ConclusionsLarge differences in the adjusted probability of deceased donor kidney transplantation persist under KAS, even between centers working with the same local organ supply. Probability of transplantation is significantly associated with organ offer acceptance patterns at transplant centers, underscoring the need for greater understanding of how centers make decisions about organs offered to wait-listed patients and how they relate to disparities in access to transplantation.

Project description:BackgroundEarlier qualification for the kidney transplant waitlist expedites transplant and is therefore associated with improved outcomes. U.S. Organ Procurement and Transplantation Network policies state that "measured or calculated creatinine clearance or glomerular filtration rate less than or equal to 20 mL/min" triggers waitlist time accrual. The choice of qualification method is somewhat arbitrary, and the policy implies that decline in renal function is monotonic.Methods(1) We used survival analysis to quantify temporal differences in waitlist qualification by applying 3 kidney-function-estimating equations (Cockcroft-Gault, Modification of Diet in Renal Disease study, Chronic Kidney Disease Epidemiology Collaboration) to serial creatinine measurements from 3 patient cohorts: 1 of waitlisted patients at a major U.S. academic center and 2 national, multicenter cohorts of chronic kidney disease patients (African American Study of Kidney Disease and Hypertension, Modification of Diet in Renal Disease). (2) Survival analysis assessed whether requiring patients to demonstrate persistently reduced renal function on 2 occasions at least 90 days apart would meaningfully change qualification order.ResultsOn average, time to waitlist qualification would be delayed on the order of 1 to 2 years by using calculated creatinine clearance (per the Cockcroft-Gault equation). Compared with current policy, requiring demonstration of persistently reduced renal function delayed qualification by 0.6 to 2.1 years and caused 40% to 50% of patients to switch the order in which they qualify by 6 months or more.ConclusionsThe kidney transplantation policies should be revised, such that timing of waitlist qualification is more standardized. We suggest that mention of using calculated creatinine clearance be dropped from the Organ Procurement and Transplantation Network policy wording and the units to quantify kidney function be changed to mL/min per 1.73 m2. Some consideration should be given to whether requiring persistently reduced renal function would better identify patients most likely to benefit from earlier waitlist qualification.

Dataset Information

Underreporting of liver transplant waitlist removals due to death or clinical deterioration: results at four major centers.

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Underreporting of liver transplant waitlist removals due to death or clinical deterioration: results at four major centers.

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