Pediatric Liver Transplant CenterVolume and the Likelihood ofTransplantationAbbas Rana, MDa,b, Zachary Pallister, MDa, Karim Halazun, MDc, Ronald Cotton, MDa, Jacfranz Guiteau, MDa,Courtney C. Nalty, MSPHa,d, Christine A. O’Mahony, MDa,b, John A. Goss, MDa,b

abstractBACKGROUND: Low case volume has been associated with poorer surgical outcomes in a multitudeof surgical procedures. We studied the association among low case volume, outcomes, and thelikelihood of pediatric liver transplantation.

METHODS: We studied a cohort of 6628 candidates listed in the Organ Procurement andTransplantation Network for primary pediatric liver transplantation between 2002 and 2012;4532 of the candidates went on to transplantation. Candidates were divided into groupsaccording to the average volume of yearly transplants performed in the listing center over10 years: .15, 10 to 15, 5 to 9, and ,5. We used univariate and multivariate Cox regressionanalyses with bootstrapping on transplant recipient data and identified independent recipientand donor risk factors for wait-list and posttransplant mortality.

RESULTS: 38.5% of the candidates were listed in low-volume centers, those in which ,5transplants were performed annually. These candidates had severely reduced likelihood oftransplantation with only 41% receiving a transplant. For the remaining candidates, listed athigher volume centers, the transplant rate was 85% (P , .001). Being listed at a low-volumecenter was a significant risk factor in multivariate Cox regression analysis for both wait-listmortality (hazard ratio, 3.27; confidence interval, 2.53–4.23) and posttransplant mortality(hazard ratio, 2.21; confidence interval, 1.43–3.40).

CONCLUSIONS: 38.5% of pediatric transplant candidates are listed in low-volume transplantcenters and have lower likelihood of transplantation and poorer outcomes. If further studiessubstantiated these findings, we would advocate consolidating pediatric liver transplantationin higher volume centers.

WHAT’S KNOWN ON THIS SUBJECT: Low casevolume has traditionally been associated withpoor outcomes in complex surgical procedures,including pediatric liver transplantation.

WHAT THIS STUDY ADDS: This retrospectiveanalysis supports the association between lowcase volume and poorer outcomes in pediatricliver transplantation, and, in addition, shows thatcandidates listed in low-volume centers haveseverely limited access to transplantation.

aMichael E. DeBakey Department of Surgery, Division of Abdominal Transplantation and Division of HepatobiliarySurgery, Baylor College of Medicine, Houston, Texas; bDepartment of Surgery, Texas Children’s Hospital, Houston,Texas; cDepartment of Surgery, Division of Transplantation, Emory University School of Medicine, Atlanta, Georgia;and dDepartment of Biostatistics, Baylor College of Medicine, Houston, Texas

Drs Rana and Goss participated in conceptualization of the study and data analysis, drafted theinitial manuscript, and reviewed and revised the final manuscript; Drs Pallister, Halazun, O’Mahony,and Goss and Ms Nalty reviewed and revised the final manuscript; and all authors approved thefinal manuscript as submitted.

www.pediatrics.org/cgi/doi/10.1542/peds.2014-3016

DOI: 10.1542/peds.2014-3016

Accepted for publication Apr 3, 2015

Address Correspondence to Abbas Rana, MD, Michael E. DeBakey Department of Surgery, Division ofAbdominal Transplantation and Division of Hepatobiliary Surgery, Baylor College of Medicine, OneBaylor Plaza, MS:BCM390, Houston, TX 77030; E-mail: abbas.rana@bcm.edu

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Traditionally, research has shown anassociation between low case volumeand poor outcomes in a multitude ofsurgical procedures,1–5 such ashysterectomy,6 pancreatectomy,5,7

esophagectomy,5 pelvic exenteration,5

and coronary artery bypasssurgery.2,8,9 Studies have also shownthis relationship in several pediatricprocedures of varying complexity,such as cardiac surgery,10,11

pyloromyotomy,12

appendectomy,13,14 and inguinalhernia repairs.13,14

In the field of transplantation,a landmark manuscript published in1999 suggested that programsperforming ,20 transplants per yearhad inferior outcomes.15 Althoughseveral studies have refuted theseconclusions,16,17 other investigationsinto all types of solid organtransplants have upheld therelationship between low volumeand poor outcomes.18–22 Specificallyin the field of pediatric livertransplantation, researchers workingwith the Scientific Registry ofTransplant Recipients database haveshown inferior outcomes intransplantation associated with low-volume centers.14 In this study, weused multivariate analysis toinvestigate the relationship betweenwait-list and transplant outcomesand pediatric transplant liver centervolume. We sought to look beyondthese outcomes by analyzing the

effect of center volume on transplantaccess.

Allocation of pediatric livers fortransplantation is designed to servethe sickest patients first. Thesepatients with acute liver failure aredesignated Status 1A, whereas Status1B is reserved for very sickchronically ill pediatric patients.Aside from these special statuscategories, the priority fortransplantation is based on thePediatric End-Stage Liver Disease(PELD) score for children aged#11 years and on the Model forEnd-Stage Liver Disease (MELD)score for children aged from 12 to 18years. The PELD score is a model forwait-list mortality that includesbilirubin, international normalizedratio, albumin, growth failure, and age,1 year. The MELD score includesinternational normalized ratio,bilirubin, and creatinine. Whena pediatric liver donor becomesavailable, it is first offered to Status1A children in the United Network forOrgan Sharing (UNOS) region andthen nationally. Subsequently, it isoffered to Status 1 adults, to Status1B children, to children 0 to 11 yearsin order of decreasing PELD scores inthe UNOS region, and to children 12to 18 also in decreasing order ofMELD scores. Transplant centercharacteristics do not affect allograftallocation; only candidatecharacteristics are considered.

FIGURE 1Dot plot with logarithmic trendline. Abscissa number of yearly transplants. Ordinate transplant rateover the study period.

TABLE 1 Risk Factors Considered inUnivariate and MultivariateAnalysis

Risk Factors EntryCompletion

Donor risk factorsAge 100African American 100ALT IU/L 87.4AST IU/L 87.4Bilirubin mg/dL 87.1Cause of deathAnoxia 88.0Cerebral vascular accident 88.0

Cold ischemia time in hours 91.0Deceased donor after cardiac

death100

Diabetes mellitus 88.0Creatinine clearance 87.8Female 100Live donor allograft 100National allocation 100Regional allocation 100Cadaveric technical variant

allograft99.9

Warm ischemia time inminutes

36.0

Center risk factorsCenter volume .15 transplants/y 100Center volume 10–15

transplants/y100

Center volume 5–9 transplants/y 100Center volume ,5 transplants/y 100Center experience in y 100

Recipient risk factorsABO incompatible 100Admitted to hospital 100Admitted to ICU 100African American 100Age 100Albumin g/dL 99.9Ascites 94.2Creatinine clearance 93.1DiagnosisAcute hepatic failure 99.6Hepatoblastoma 99.6Biliary atresia 99.6Metabolic disorder 99.6

Dialysis 96.1Encephalopathy 94.3Height deficit 1–2 SD 99.9Height deficit .2 SD 99.9Life support 100Previous transplantation 100PELD laboratory score 99.7Serum sodium mEq/L 74.7UNOS Status 1 99.9Wt in kg 100Wt deficit 1–2 SD 95.9Wt deficit .2 SD 95.9Center experience in y 100

ALT, alanine transaminase; AST, aspartate aminotransferase.

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METHODS

Study Population

We performed a retrospectiveanalysis of the UNOS deidentifiedpatient-level data of all candidateslisted for liver transplant betweenMarch 1, 2002, and December 31,2012. We analyzed the liver registrydata collected from all transplantrecipients younger than 18 years bythe Organ Procurement andTransplantation Network. Donor andrecipient characteristics werereported at the time of transplant.Follow-up information was collectedat 6 months and then yearly aftertransplantation. Patients undergoingcombined or multivisceral transplants(n = 767) and candidates placed onthe wait-list for combined ormultivisceral transplants (n = 662)

were excluded. Retransplantationcandidates were also excluded (n =1064). From the date of listing, 6628patients were followed, and 4532candidates received a transplantduring the study period. All patientswere followed to either death (n =1171) or the date of last knownfollow-up (n = 5457).

Statistical Analysis

Data were analyzed by usinga standard statistical softwarepackage, Stata 9 (Stata Corp, CollegeStation, TX). Continuous variableswere reported as mean 6 SD andcompared using the Student t test andthe Mann-Whitney U test.Contingency table analysis was usedto compare categorical variables.A P value ,.05 was consideredsignificant, and all reported P values

were 2-sided. A hazard ratio (HR) .1indicates a greater risk of mortality.

Probability of Transplant Analysis

The primary outcome measure wastransplantation. All listed candidateswere included in the analysis(n = 6628). Patients who died werecensored. Time to transplantationwas assessed as time from date oflisting to date of transplantation.

Wait-List Survival Analysis

The primary outcome measure wasdeath on the wait list. All listedcandidates were included in theanalysis (n = 6628). Candidates werenot removed from the analysis if theywere taken off the wait list. Death wasestablished by the UNOS death dateand social security death master files.Time to death was assessed as the

TABLE 2 Demographics and Clinical Characteristics

Demographics/Characteristics .15 Transplants/y 10–15 Transplants/y 5–9 Transplants/y ,5 Transplants/y

Number of centers 10 6 11 79Listed candidates 2002–2012 2233 766 1080 2549% total listed candidates 33.7 11.6 16.3 38.5Transplanted recipients 1852 721 906 1053Transplant rate, % 82.9 94.1 83.9 41.3a

Waiting time in d, median (25th–75th percentile) 47 (11–131) 53 (12–179) 47 (12–120) 46.5 (9–136)% total listed patients at end of follow-upAlive posttransplant 78.7 82.5 73.6 30.4a

Dead posttransplant 7.5 8.2 9.8a 6.2Alive on the wait list 10.8 6.7a 12.7 46.2a

Transferred to another center 1.8 0.6a 1.4 6.2a

Condition improved 5.2 3.6 6.4 22.9a

Dead on the wait list 3.9 3.2 4.6 21.6a

% total transplantedAge (y) 4.7 6 5.7 4.8 6 5.5 4.6 6 5.6 6.4 6 6.6a

Biliary atresia 34.8 33.3 35.1 30.5a

Acute liver failure 12.0 14.0 10.4 12.5Transplant rate for candidates listed with acute liver failure 71.4 82.1 66.7 28.6a

Idiopathic cause of liver failure 14.4 10.8 11.0 11.2a

Cadaveric technical variant grafts 28.7 29.4 29.4 19.7a

Live donor transplant 13.6 11.0 14.3 13.5Cold ischemia time 7.0 6 4.3 7.7 6 3.4a 6.3 6 3.6a 6.7 6 3.7Dialysis 2.7 5.3a 3.3 3.8Donor age 15.6 6 14.2 13.4 6 12.8a 14.8 6 13.8 16.8 6 14.6a

Height (cm) 95.8 6 38.3 95.7 6 37.6 93.9 6 39.2 106.1 6 43.3a

Hepatoblastoma 7.2 4.0a 7.0 2.9a

Hospitalized 19.0 16.1 15.1a 14.6a

ICU 23.3 26.1 21.7 26.9a

Laboratory PELD score 14.6 6 14.6 16.1 6 14.0a 14.8 6 14.6 16.7 6 13.9a

Life support 9.3 15.3a 8.8 13.0a

Metabolic 11.4 13.0 11.1 11.7Status 1 17.6 18.0 16.2 18.9Wt (kg) 20.5 6 20.4 20.1 6 19.3 19.7 6 20.3 27.4 6 25.7a

Wt ,5 kg 6.1 7.9 8.6a 4.5a P , .05 compared with .15 transplants/y.

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time from date of listing to date ofdeath while on the wait list.Candidates who underwenttransplantation were censored. Earlylisted patients with improved liverfunction make up a majority of long-term wait-list survivors.

Posttransplant Survival Analysis

The primary outcome measure wasdeath after transplantation. Onlyrecipients who underwenttransplantation were included in thisanalysis (n = 4532). Time to deathwas assessed as the time from date oftransplantation to date of death.

Intent-to-Treat Analysis

The primary outcome measure wasdeath, regardless whether it wasposttransplant or wait-list death.Candidates were followed from timeof listing (n = 6628) to time of deathor last known follow-up, regardless oftransplantation. UNOS death date andsocial security master death fileswere used to establish death. Time todeath was assessed as the time fromdate of listing to date of death.

Kaplan-Meier analysis with log-ranktest and Cox regression were used fortime-to-event analysis. Survival, onthe wait list or posttransplant, wasthe dependent variable, and the riskfactors were the independentvariables in the regression analysis.Risk factors that were significant inunivariate analysis (P , .05) wereincluded in the multivariate analysis.Multivariate Cox regression wasperformed combining 100 bootstraps.Patients lost to follow-up or alive onDecember 31, 2012, were censored atthe date of last known follow-up.

Risk Factors

Pediatric liver-transplant volume foreach center was the average numberof cases performed from 2002 to2012. Centers were categorized aslow volume when their recordsshowed ,5 cases performed peryear. The slope of the curve issteepest between 0 and 4 cases peryear (Fig 1). The other groups were

categorized as multiples of 5.Experience of center was defined asthe number of consecutive years thatpediatric liver transplants wereperformed since 1987. To accountfor the impact of individual centers,we repeated all analyses withconditional Cox regressionstratifying for individual transplantcenters.

The recipient and donor risk factorsconsidered in this analysis are listed

in Table 1. Creatinine clearance wascalculated with the updated Schwartzbedside formula: estimatedglomerular filtration rate = 0.41 3

height (cm)/Scr (mg/dL). Height andweight deficits were based on Centersfor Disease Control and Preventiongrowth charts. Standard deviationswere calculated according topublished Z scores. Status 1 includedStatus1A and Status1B. Life supportis a UNOS designation for ventilator

FIGURE 2Kaplan-Meier curve of probability of liver transplant by center volume. *P , .001 for each group bylog-rank test with reference to ,5 transplants per year.

TABLE 3 Multivariate Analysis: Pediatric Liver Transplant Waitlist Survival

Risk Factors: Statistically Significant HR P CI

Center volume ,5 transplants/y 3.27 ,.01 2.53–4.23Dialysis 2.57 ,.01 1.54–4.29Status 1 1.66 ,.01 1.25–2.19Laboratory PELD (per point) 1.05 ,.01 1.04–1.06Serum sodium (per mEq/L) 1.03 .004 1.01–1.05Albumin (per g/dL) 0.82 .008 0.70–0.95

Not statistically significant: encephalopathy, HR 1.04, P = .71, CI 0.84–1.30; center volume: 5–9 transplants/y, HR 1.04, P =.81, CI 0.89–1.16; glomerular filtration rate, HR 1.00, P = .90, CI 0.99–1.00; recipient wt (per kg), HR 1.00, P = .52, CI0.99–1.01; recipient height (per cm), HR 1.00, P = .15, CI 0.99–1.00; biliary atresia, HR .84, P = .19, CI 0.64–1.10; metabolic,HR .79, P = .23, CI 0.53–1.17.

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support, artificial liver, or a write inentry for another mechanism.

Missing Variables

Multiple imputation with predictedmean matching was performed forthe following incomplete predictorsin the Organ Procurement andTransplantation Network database:serum sodium (25.3%), cold ischemiatime (9.0% missing), serumcreatinine (6.9%), ascites (5.8%),encephalopathy (5.7%), recipientweight (4.1% missing), diagnosis(0.4%), PELD score (0.3%), recipientheight (0.1% missing), albumin(0.1%), and Status 1 (0.1%). Wefound no significant difference in themissing variables between low- andhigher volume centers. We also foundno significant differences in oursurvival models if serum sodium wasremoved.

Candidates’ Removal From the WaitList for Conditioned Improved

These candidates were removed fromthe wait list for improvement in theirmedical condition. They did notreceive a transplant at a later date ordie within our study period.

Geographic Variation

To investigate clustering oflow-volume centers in particularUNOS regions, we compared theproportions of low-volume listings tooverall listings among UNOSgeographic regions.

RESULTS

Data Entry Rate

Data entry completion for variables islisted in Table 1. Most variables werewell populated. Multiple imputationwith predicted mean values wasperformed for missing variables.

Study Population

The study population at the time totransplant and wait-list survivalanalysis consisted of 6628 patients.Wait-list analysis comprised 4554years-at-risk for liver transplant

recipients. Mean follow-up was 0.7years. The study population for theposttransplant survival analysis had4532 patients. Posttransplant survivalanalysis comprised 22 549 years-at-risk for liver transplant recipients.Mean follow-up was 5.0 years.Demographic and clinical

characteristics are summarized inTable 2.

Transplant Rate

Centers with .15 transplants a yearhad a transplant rate over the studyperiod of 83%; those with 10 to 15transplants per year, 94%; 5 to 9

FIGURE 3Kaplan-Meier curve of wait-list survival by pediatric liver center volume P , .001 for each group bylog-rank test with reference to ,5 transplants per year.

TABLE 4 Multivariate Analysis: Pediatric Liver Transplant Posttransplant Survival

Risk Factors: Statistically Significant HR P CI

Hepatoblastoma 3.48 ,.01 2.30–5.27Life support 2.69 ,.01 1.82–3.99Center volume ,5 transplants/y 2.21 ,.01 1.43–3.40Center volume 5–9 transplants/y 1.14 .02 1.02–1.27Age 1.09 .02 1.01–1.17Laboratory PELD (per point) 1.02 ,.01 1.01–1.03Recipient height (per cm) 0.99 .03 0.97–0.99Biliary atresia 0.62 ,.01 0.43–0.89

Not statistically significant: ICU admission, HR 1.24, CI 0.84–1.83; encephalopathy, HR 1.17, CI 0.88–1.57; regional sharing,HR 1.13, CI 0.85–1.49; cadaveric technical variant graft, HR 1.09, CI 0.77–1.55; cold ischemia time (per h), HR 1.03, CI0.99–1.05; center experience (per y), HR 1.01, CI 0.99–1.03; serum sodium, HR 1.00, CI 0.98–1.03; recipient wt (per kg), HR1.00, CI 0.99–1.01; glomerular filtration rate, HR 0.99, CI 0.99–1.00; donor age, HR 0.99, CI 0.98–1.01; center volume; 10–15transplants/y, HR 0.87, CI 0.70–1.10; live donor transplant, HR 0.85, CI 0.45–163; hemodialysis, HR 0.76, CI 0.43–1.31; Status1, HR 0.71, CI 0.50–1.01; national share, HR 0.70, CI 0.45–1.08.

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transplants per year, 84%; and .5transplants per year, 41%. Figure 1shows the dot plot of transplant ratesfor each center’s transplant volume.Figure 2 shows the Kaplan-Meiercurve of the probability oftransplantation.

Wait-List Survival Analysis

The recipient and center risk factorslisted in Table 1 were considered. Riskfactors that were significant inmultivariate analysis are presented inTable 3. The most significant riskfactors were as follows: listing ina center with transplant volume ,5cases per year (HR 3.3, confidenceinterval [CI] 2.5–4.2) and dialysis (HR2.6, CI 1.5–4.3). The Kaplan-Meier curvefor wait-list survival is shown in Fig 3.

Posttransplant Survival Analysis

The risk factors listed in Table 1 wereconsidered. Risk factors that weresignificant in multivariate analysis arepresented in Table 4. The mostsignificant risk factors werehepatoblastoma (HR 3.5, CI 2.3–5.3),life support (HR 2.7, CI 1.8–4.0), andtransplantation in a center with atransplant volume ,5 (HR 2.2, CI1.4–3.4). The Kaplan-Meier curve forposttransplant survival is shown inFig 4.

Intent-to-Treat Analysis

The Kaplan-Meier curve for survivalof all listed candidates from time oflisting is shown in Fig 5.

Cadaveric Technical Variant Grafts

Centers performing ,5 transplantsper year used cadaveric technicalvariant grafts 18% of the time. Thispercentage was significantly smaller(P , .001) than the percentages ofthe other volume groups: 5 to 9transplants per year, 29%; 10 to 15transplants per year, 29%; and .15transplants per year, 29%.

High-Risk Recipients

The survival of recipients under 6 kgtreated in centers performing .15transplants per year was significantly

better than the survival in othercenters. Centers with .15transplants a year had a 1-yearsurvival of 94.1%, 5-year survival of92.0%, and 10-year survival of92.0%. Centers performing 10 to 15transplants per year had a 1-yearsurvival of 84.8%, 5-year survival of82.5%, and 10-year survival of82.5%. For those centers performing5 to 9 transplants per year, 1-yearsurvival was 87.9%, 5-year survival83.6%, and 10-year survival 82.0%.Centers performing ,5 transplantsper year had a 1-year survival of89.6%, 5-year survival of 82.2%, and10-year survival of 82.2%. The Pvalue was ,.001 for each group bylog-rank test with reference to .15transplants per year.

The survival of recipients on lifesupport treated in centers performing.15 transplants per year was

significantly better than the survival inother centers. Centers with .15transplants a year had a 1-year survivalof 90.2%, 5-year survival of 84.7%, and10-year survival of 83.4%. Centers thatperformed 10 to 15 transplants peryear had a 1-year survival of 80.7%,5-year survival of 79.7%, and 10-yearsurvival of 78.0%. Those thatperformed 5 to 9 transplants per yearreached a 1-year survival of 74.3%,5-year survival of 71.6%, and 10-yearsurvival of 68.6%. Centers performing,5 transplants per year had a 1-yearsurvival of 75.8%, 5-year survival of66.6%, and 10-year survival of 63.3%.The P value was ,.001 for each groupby log-rank test with reference to .15transplants per year.

Candidate Status at the End ofFollow-up

The candidate status at the end offollow-up on December 31, 2012,

FIGURE 4Kaplan-Meier curve of posttransplant survival by pediatric liver center volume. P , .05 for eachgroup by log-rank test with reference to ,5 transplants per year.

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including alive posttransplant, deadposttransplant, alive on the wait list,and dead on the wait list is reportedin Table 2.

Candidates Removal From the WaitList for Conditioned Improved

There is a disproportionate numberof candidates removed for conditionimproved from the low-volume center

wait list (Table 2). The 3 mostcommon diagnoses for removedcandidates for improved liverfunction were acute liver failure(25%), idiopathic etiology (24%), andbiliary atresia (14%). If these patientsare removed from the analysis, theadjusted transplant rate for low-volume centers (,5 transplants peryear) is 53.6% compared with 87.4%(.15 transplants per year), 96.0%(10–15 transplants per year), and90.9% (5–10 transplants per year).The adjusted HR for wait-listmortality on the low-volume wait listis HR 4.76 (CI 3.63–6.24) comparedwith the unadjusted HR of 3.27(CI 2.53–4.23).

Geographic Variation

We report on variations of low-volume listings by UNOS region inTable 5. Low-volume center listings inregions 1, 4, 7, and 11 wereoverrepresented. Only region 1 isconsidered disadvantageous in terms

of donor allograft supply anddemand23 (Table 5).

Impact of Individual Centers

We found no significant differences inthe outcomes or regression analyseswhen we accounted for the impact ofindividual centers.

DISCUSSION

Investigators have established thatlow case volumes adversely affectsurvival outcomes in a variety ofprocedures, from those as simple asinguinal hernia repairs to those ascomplex as pediatric livertransplantation.1–9 Although studieshave refuted this assertion,5 themajority seems to accept therelationship. Overall, thisunderstanding has also been reachedin the field of transplantation.A number of researchers have shownbetter outcomes in high-volumecenters for renal, cardiac, and livertransplantations,18–22 but others haverefuted these assertions.16,17 Parallelstudies in pediatric renal, cardiac, andliver transplantation have alsodemonstrated this low-volume–pooroutcome relationship.14,20,24 Asa result of the general acceptance ofthis conclusion, insurance companiesroutinely require a minimum yearlycase volume to designate a programas a center of excellence in adult andpediatric transplantation.25

Our analysis is unique in the body ofliterature on this topic because itlooks beyond survival outcomes intoaccess to transplantation. We do seeworse wait-list and posttransplantsurvival in low-volume pediatric livertransplant centers, but the mostprofound differences are in thelikelihood of transplantation. Low-volume centers (,5 transplants peryear), where 39% of the children arelisted, have a smaller transplant rate(41%) than the other centers (85%).This staggering difference in thelikelihood of transplantation isexacerbated by poorer wait-list andposttransplant survival in low-

FIGURE 5Kaplan-Meier curve of intent-to-treat analysis of candidate survival from listing by pediatric livercenter volume. P , .05 for each group by log-rank test with reference to ,5 transplants per year.

TABLE 5 Regional Variations

Region % of Low-Volumea

Listings% of AllListings

1 5.18b 3.712 13.12 14.213 6.91b 10.714 13.28b 11.365 17.28b 20.586 1.89b 2.647 11.70b 8.198 6.56 7.029 6.25 7.7110 7.74 8.6311 10.09b 5.24a Fewer than 5 transplants per year.b P , .05 compared with all listings.

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volume centers. The 5-year wait-listsurvival in low-volume centers (63%)was also lower than thecorresponding survival (92%) inhigher volume centers (those with.15 transplants per year). The5-year posttransplant survival was83% in low-volume centers and 92%in high-volume centers. Listing andtransplantation in low-volumecenters were among the strongestrisk factors in our multivariateanalysis for wait-list andposttransplant mortality (HR 3.3 and2.2, respectively).

Our analysis does shed light on thereasons behind the poor access totransplantation in low-volumecenters. In low-volume centers,patients may be listed fortransplantation too early in theirdisease progression. About 22.9% ofcandidates listed for transplant inlow-volume centers were removedfrom the wait list due toimprovement of the liver function,whereas only 0.6% to 1.8% of thecandidates were removed from thewait list in the other centers. Theseearly listing practices may lead tosome patients receiving unnecessaryliver transplants. The transplant ratefor candidates listed with acute liverfailure in low-volume centers was28.6% compared with 71.4% (.15transplants per year), 82.1% (10–15transplants per year), and 66.7%(,5 transplants per year). This willclearly affect the number ofcandidates who die on the list as wellas the number of patients who areremoved for recovering liverfunction. There were no significantdifferences with the percentage ofpatients transplanted with acuteliver failure (Table 2). Early listing isnot the sole explanation; we considerthat much greater wait-list mortalitymay also contribute. At the end offollow-up, 21.6% of waitlisted

patients in low-volume centers died,compared with 3.2% to 4.6% inother centers. The management ofend-stage liver disease in children ischallenging and requires extensivemedical, critical care, andinstitutional expertise. Our analysisalso suggests that low-volumecenters are less likely totake technical variant cadavericallografts and less likely to takeother extended criteria donors. Oncelisted, candidates from low-volumecenters are also less likely to transferto high-volume centers (only 6.2% ofcandidates). Other factors beyondmedical issues also contributed tothe differences, including policiesand strategies to maintain activeprograms and surgeon availability.Regional variations in thedistribution of low-volume centersdid not explain the differences in thelikelihood of transplantation oroutcomes.

The significant differences insurvival outcomes and in thelikelihood of transplantation suggestthat pediatric liver transplantationshould be consolidated in highervolume centers. If substantiated byother studies, this change in policywould not be trivial because 39% ofpatients are listed in centersperforming ,5 transplants peryear. We would strongly suggesta policy change to exempt centersserving geographically isolatedpopulations. We did not findsignificant differences in thelikelihood of transplantation orsurvival outcomes among centersin which $5 transplants wereperformed per year. However,when we considered our riskiestpediatric recipients (,6 kg andon life support), we found thebest outcomes in our highestvolume centers (.15 transplantsper year).

Since the passage of the NationalTransplantation Act of 1984, dataentry has been mandatory for all UStransplant centers. Nevertheless, allpatient registries often suffer fromvariability in data entry. The findingsfrom this study were based onlarge cohorts of patients and areunlikely to be significantly affectedby small amounts of missing data.We attempted to account for missingdata with multiple imputationanalysis. Another significantlimitation was that center-specificfactors could not be appropriatelyaccounted for.

CONCLUSIONS

Of pediatric transplant candidates,38.5% are listed in low-volumetransplant centers and havea reduced likelihood oftransplantation and poorer outcomes.If further studies substantiated thesefindings, we would advocateconsolidating pediatric livertransplantation in higher volumecenters.

ACKNOWLEDGMENTS

We thank Ana María Rodríguez, PhD,a member of the Baylor College ofMedicine Michael E. DeBakeyDepartment of Surgery ResearchCore, for her editorial assistanceduring preparation of themanuscript.

ABBREVIATIONS

CI: confidence intervalHR: hazard ratioMELD: Model for End-Stage Liver

DiseasePELD: Pediatric End-Stage Liver

DiseaseUNOS: United Network for Organ

Sharing

PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online, 1098-4275).

Copyright © 2015 by the American Academy of Pediatrics

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

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FUNDING: This study was funded by the Cade R. Alpard Foundation.

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

REFERENCES

1. Hughes RG, Garnick DW, Luft HS, McPheeSJ, Hunt SS. Hospital volume and patientoutcomes. The case of hip fracturepatients. Med Care. 1988;26(11):1057–1067

2. Hannan EL, Kilburn H Jr, Bernard H,O’Donnell JF, Lukacik G, Shields EP.Coronary artery bypass surgery: therelationship between inhospitalmortality rate and surgical volume aftercontrolling for clinical risk factors.Med Care. 1991;29(11):1094–1107

3. Kimmel SE, Berlin JA, Laskey WK. Therelationship between coronaryangioplasty procedure volume andmajor complications. JAMA. 1995;274(14):1137–1142

4. Cebul RD, Snow RJ, Pine R, Hertzer NR,Norris DG. Indications, outcomes, andprovider volumes for carotidendarterectomy. JAMA. 1998;279(16):1282–1287

5. Begg CB, Cramer LD, Hoskins WJ,Brennan MF. Impact of hospital volumeon operative mortality for major cancersurgery. JAMA. 1998;280(20):1747–1751

6. Vree FE, Cohen SL, Chavan N, EinarssonJI. The impact of surgeon volume onperioperative outcomes in hysterectomy.J Society of Laparoscopic Surgeons.2014;18(2):174–181

7. Ho V, Heslin MJ. Effect of hospital volumeand experience on in-hospital mortalityfor pancreaticoduodenectomy. Ann Surg.2003;237(4):509–514

8. Luft HS, Bunker JP, Enthoven AC. Shouldoperations be regionalized? Theempirical relation between surgicalvolume and mortality. N Engl J Med.1979;301(25):1364–1369

9. Showstack JA, Rosenfeld KE, Garnick DW,Luft HS, Schaffarzick RW, Fowles J.Association of volume with outcome of

coronary artery bypass graft surgery.Scheduled vs nonscheduled operations.JAMA. 1987;257(6):785–789

10. Checchia PA, McCollegan J, Daher N,Kolovos N, Levy F, Markovitz B. The effectof surgical case volume on outcomeafter the Norwood procedure. J ThoracCardiovasc Surg. 2005;129(4):754–759

11. Hannan EL, Racz M, Kavey RE,Quaegebeur JM, Williams R. Pediatriccardiac surgery: the effect of hospitaland surgeon volume on in-hospitalmortality. Pediatrics. 1998;101(6):963–969

12. Safford SD, Pietrobon R, Safford KM,Martins H, Skinner MA, Rice HE. A studyof 11,003 patients with hypertrophicpyloric stenosis and the associationbetween surgeon and hospital volumeand outcomes. J Pediatr Surg. 2005;40(6):967–972, discussion 972–973

13. Berry JG, Lieu TA, Forbes PW, GoldmannDA. Hospital volumes for commonpediatric specialty operations. ArchPediatr Adolesc Med. 2007;161(1):38–43

14. Tracy ET, Bennett KM, Danko ME, et al.Low volume is associated with worsepatient outcomes for pediatric livertransplant centers. J Pediatr Surg. 2010;45(1):108–113

15. Edwards EB, Roberts JP, McBride MA,Schulak JA, Hunsicker LG. The effectof the volume of procedures attransplantation centers on mortalityafter liver transplantation. N Engl J Med.1999;341(27):2049–2053

16. Northup PG, Pruett TL, Stukenborg GJ,Berg CL. Survival after adult livertransplantation does not correlate withtransplant center case volume in theMELD era. Am J Transplant. 2006;6(10):2455–2462

17. Reese PP, Yeh H, Thomasson AM, Shults J,Markmann JF. Transplant center volumeand outcomes after liverretransplantation. Am J Transplant. 2009;9(2):309–317

18. Axelrod DA, Guidinger MK, McCulloughKP, Leichtman AB, Punch JD, Merion RM.Association of center volume withoutcome after liver and kidneytransplantation. Am J Transplant. 2004;4(6):920–927

19. Hosenpud JD, Breen TJ, Edwards EB,Daily OP, Hunsicker LG. The effect oftransplant center volume on cardiactransplant outcome. A report of theUnited Network for Organ SharingScientific Registry. JAMA. 1994;271(23):1844–1849

20. Schurman SJ, Stablein DM, Perlman SA,Warady BA. Center volume effects inpediatric renal transplantation. A reportof the North American Pediatric RenalTransplant Cooperative Study. PediatrNephrol. 1999;13(5):373–378

21. Tsao SY, Lee WC, Loong CC, Chen TJ, ChiuJH, Tai LC. High-surgical-volume hospitalsassociated with better quality and lowercost of kidney transplantation in Taiwan.J Chin Med Assoc. 2011;74(1):22–27

22. Sloan FA, Shayne MW, Doyle MD. Is therea rationale for regionalizing organtransplantation services? J Health PolitPolicy Law. 1989;14(1):115–167

23. Davies RR, Russo MJ, Hong KN, et al.Increased short- and long-term mortalityat low-volume pediatric heart transplantcenters: should minimum standards beset? Retrospective data analysis. AnnSurg. 2011;253(2):393–401

24. Finks JF, Osborne NH, Birkmeyer JD.Trends in hospital volume and operativemortality for high-risk surgery. N Engl JMed. 2011;364(22):2128–2137

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