2019
Modeling of implementation of the new Organ Procurement and Transplantation Network/United Network for Organ Sharing policy for patients with hepatocellular carcinoma
Kokabi N, Nezami N, Xing M, Ludwig JM, Strazzabosco M, Kim HS. Modeling of implementation of the new Organ Procurement and Transplantation Network/United Network for Organ Sharing policy for patients with hepatocellular carcinoma. Journal Of Comparative Effectiveness Research 2019, 8: 993-1002. PMID: 31512955, DOI: 10.2217/cer-2019-0076.Peer-Reviewed Original ResearchConceptsTransplantation Network/United NetworkOrgan Sharing (UNOS) policyUnited NetworkNew Organ ProcurementHepatocellular carcinomaOrgan procurementOrthotopic liver transplantation outcomesLiver transplantation outcomesOrgan Sharing databaseOverall survivalPatient characteristicsSharing databaseTransplantation outcomesPatientsCarcinomaAMPTransplantationGroup
2016
Liver-allocation policies for patients affected by HCC in Europe
De Carlis L, Di Sandro S, Centonze L, Lauterio A, Buscemi V, De Carlis R, Ferla F, Sguinzi R, Okolicsanyi S, Belli L, Strazzabosco M. Liver-allocation policies for patients affected by HCC in Europe. Current Transplantation Reports 2016, 3: 313-318. PMID: 28473952, PMCID: PMC5410888, DOI: 10.1007/s40472-016-0117-6.Peer-Reviewed Original ResearchLiver allocation policyWaiting listCentro Nazionale TrapiantiOrgan SharingDeceased donor liver transplantLong-term survival ratesTransplant waiting listOrgan allocation systemOrgan allocation policyEtablissement français des GreffesLiver graftsLiver transplantLiver diseaseUnited NetworkNHS BloodSurvival rateDisease changesPatients
2014
A Bayesian methodology to improve prediction of early graft loss after liver transplantation derived from the Liver Match study
Angelico M, Nardi A, Romagnoli R, Marianelli T, Corradini SG, Tandoi F, Gavrila C, Salizzoni M, Pinna AD, Cillo U, Gridelli B, De Carlis LG, Colledan M, Gerunda GE, Costa AN, Strazzabosco M, Investigators L, Committee: L, Angelico M, Cillo U, Fagiuoli S, Strazzabosco M, Board: A, Caraceni P, Toniutto P, Board: C, Costa A, Investigators: P, Salizzoni T, Romagnoli R, Bertolotti G, Patrono D, De Carlis L, Slim A, Mangoni J, Rossi G, Caccamo L, Antonelli B, Mazzaferro V, Regalia E, Sposito C, Colledan M, Corno V, Tagliabue F, Marin S, Cillo U, Vitale A, Gringeri E, Donataccio M, Donataccio D, Baccarani U, Lorenzin D, Bitetto D, Valente U, Gelli M, Cupo P, Gerunda G, Rompianesi G, Pinna A, Grazi G, Cucchetti A, Zanfi C, Risaliti A, Faraci M, Tisone G, Anselmo A, Lenci I, Sforza D, Agnes S, Di Mugno M, Avolio A, Ettorre G, Miglioresi L, Vennarecci G, Berloco P, Rossi M, Corradini S, Molinaro A, Calise F, Scuderi V, Cuomo O, Migliaccio C, Lupo L, Notarnicola G, Gridelli B, Volpes R, Petri S, Zamboni F, Carbotta G, Dedola S, Collection and Verification and Biostatistics: D, Nardi A, Marianelli T, Gavrila C, Ricci A, Vespasiano F. A Bayesian methodology to improve prediction of early graft loss after liver transplantation derived from the Liver Match study. Digestive And Liver Disease 2014, 46: 340-347. PMID: 24411484, DOI: 10.1016/j.dld.2013.11.004.Peer-Reviewed Original ResearchMeSH KeywordsAdultAge FactorsAgedBayes TheoremBody Mass IndexCohort StudiesCold IschemiaDelayed Graft FunctionEnd Stage Liver DiseaseFemaleGraft RejectionGraft SurvivalHumansItalyLiver TransplantationMaleMiddle AgedMultivariate AnalysisPrimary Graft DysfunctionProportional Hazards ModelsProspective StudiesRisk AssessmentRisk FactorsTissue DonorsTreatment OutcomeConceptsEarly graft lossGraft lossUnited NetworkLiver transplantationPrior upper abdominal surgeryDonor body mass indexProspective European cohortsUpper abdominal surgeryOrgan Sharing registryPrimary liver transplantCold ischaemia timeBody mass indexRisk indexRecipient creatinineBayesian Cox modelsLiver transplantPortal thrombosisAbdominal surgeryCardiac deathIschaemia timeMass indexDonor ageEuropean cohortOrgan SharingCox model