Avolio, Alfonso W.

Paolo De Simone,

Quirino, Lai

Romagnoli, Renato

Umberto, Cillo

English

Institutional Research Information System University of Turin

Several pathogens, such as Epstein–Barr, varicella-zoster, andhepatitis Aviruses, can triggerAIHonset.4 In addition, some reportsdescribed a relationship between vaccination (i.e., hepatitis A andinfluenza virus) and the development of AIH,5–8 suggesting apotential role of both virus and vaccine in unmasking AIH inpredisposed individuals. Thus, the occurrence of acute or chronicliver disease following viral infection or vaccination should raisethe suspicionofAIH in thepresenceofotherautoimmunedisorders.Although the causal link between the SARS-CoV-2 vaccine andAIH cannot be definitively established, our case report suggests thatthisassociationcouldbemorethancoincidental. Indeed, themedicalhistorynegative for liverdiseaseaswellas thecoexistenceofanotherautoimmune disorder, the reasonable lag time between exposure tothe triggering factor, the typical onset of symptoms, the laboratory/histopathological findings and finally the excellent response totherapyareallpiecesof thepuzzle that reinforce thehypothesisof anassociation between AIH and SARS-CoV-2 vaccination.In summary, since the vaccination campaign against SARS-CoV-2 is reaching extraordinary coverage rates, healthcare pro-viders should be aware of the potential association between thevaccine and the onset of immunomediated disorders in patientswith a history of autoimmune diseases.Financial supportThe authors received no financial support to produce thismanuscript.Conflict of interestAlba Rocco, Costantino Sgamato, Debora Compare declare noconflict of interest.GerardoNardone has served as a speaker forMalesci and Takeda,and has received research funding from SOFAR Spa and Alfasigma.Please refer to the accompanying ICMJE disclosure forms forfurther details.Authors’ contributionsAlba Rocco, Costantino Sgamato and Debora Compare: patientcare, writing of the manuscript, and revision of the final versionof the manuscript. Gerardo Nardone made a critical revision ofthe letter to the Editor.Supplementary dataSupplementary data to this article can be found online at https://doi.org/10.1016/j.jhep.2021.05.038.References[1] Bril F, Al Diffalha S, Dean M, Fettig DM. Autoimmune hepatitis developingafter coronavirus disease 2019 (COVID-19) vaccine: Causality or casualty?J Hepatol 2021 Jul;75(1):222–224. https://doi.org/10.1016/j.jhep.2021.04.003.[2] Capecchi PL, Lazzerini PE, Brillanti S. Comment on “Autoimmune hepa-titis developing after coronavirus disease 2019 (COVID-19) Vaccine:Causality or casualty?”. J Hepatol 2021 May. https://doi.org/10.1016/j.jhep.2021.04.039.[3] Alvarez F, Berg PA, Bianchi FB, Bianchi L, Burroughs AK, Cancado EL, et al.International Autoimmune Hepatitis Group Report: review of criteria fordiagnosis of autoimmune hepatitis. J Hepatol 1999 Nov;31(5):929–938.https://doi.org/10.1016/s0168-8278(99)80297-9.[4] Zachou K, Muratori P, Koukoulis GK, Granito A, Gatselis N, Fabbri A, et al.Review article: autoimmune hepatitis – current management and chal-lenges. Aliment Pharmacol Ther 2013 Oct;38(8):887–913. https://doi.org/10.1111/apt.12470.[5] Perumalswami P, Peng L, Odin JA. Vaccination as a triggering event forautoimmune hepatitis. Semin Liver Dis 2009 Aug;29(3):331–334. https://doi.org/10.1055/s-0029-1233537. Epub 2009 Aug 12. PMID: 19676005.[6] Berry PA, Smith-Laing G. Hepatitis A vaccine associated with autoimmunehepatitis. World J Gastroenterol 2007 Apr 21;13(15):2238–2239. https://doi.org/10.3748/wjg.v13.i15.2238.[7] Sasaki T, Suzuki Y, Ishida K, Kakisaka K, Abe H, Sugai T, et al. Autoimmunehepatitis following influenza virus vaccination: two case reports. Medicine(Baltimore) 2018 Jul;97(30):e11621. https://doi.org/10.1097/MD.0000000000011621.[8] van Gemeren MA, van Wijngaarden P, Doukas M, de Man RA. Vaccine-related autoimmune hepatitis: the same disease as idiopathic autoimmunehepatitis? Two clinical reports and review. Scand J Gastroenterol 2017Jan;52(1):18–22. https://doi.org/10.1080/00365521.2016.1224379.Alba Rocco*Costantino SgamatoDebora CompareGerardo NardoneDepartment of Clinical Medicine and Surgery, Gastroenterology andHepatology, University Federico II of Naples, Italy*Corresponding author. Address: Department of Clinical Medicineand Surgery, Gastroenterology Unit, University “Federico II”, Via S.Pansini n 5, 80131 Naples, Italy; Tel.: 0039 081 7464293.E-mail address: a.rocco@unina.it (A. Rocco)L-GrAFT and EASE scores in liver transplantation: Need forreciprocal external validation and comparison with other scoresTo the Editor:We read with great interest the recent article by Agopian et al. onthe validation of the liver graft assessment followingtransplantation (L-GrAFT) score for prediction of early allograftfailure (EAF).1 EAF was defined as the failure of the graft(identified by retransplant or death) for any reason at 90 daysafter liver transplantation.1,2 Adopting an innovative “kinetic”approach which included calculation of the AUC and slope ofaspartate aminotransferase, bilirubin, platelet count, andinternational normalized ratio (INR), the L-GrAFT1,2 wasreported to outperform both the model for early allograftfunction (MEAF)3 and early allograft dysfunction (EAD)4 scores,Keywords: Liver transplantation; Early Allograft Failure; Primary non-function; Pri-mary dysfunction; Delayed non-function; Prognostic Score; EASE score; SmartphoneCalculator; Outcome; Re-transplant; Unsustainable-risk class; DCD;Machine Perfusion.Received 22 October 2020; received in revised form 7 December 2020; accepted 10December 2020; available online 17 December 2020https://doi.org/10.1016/j.jhep.2020.12.009Journal of Hepatology 2021 vol. 75 j 725–756 729namely the strongest validated scores available to date in thissetting. The authors used a cumulative retrospective databasefrom 4 North American (n = 3,201) and 7 European (n = 222)large volume centers.1 The L-GrAFT has 2 calculationmodalities: at 7 days (L-GrAFT7) and at 10 days (L-GrAFT10).Twenty-eight and 40 data entries are needed to calculate thescores, respectively. Both L-GrAFT scores were validated in theUS cohort, while only the score at 7 days was validated in theEuropean cohort. For the L-GrAFT7, the authors report a C-sta-tistic of 0.78 and 0.82 in the US and European cohort, respec-tively. Unfortunately, calculation of L-GrAFT scores is rathercomplex due to the significant number of requested data entriesand their estimation intrinsic nature. Moreover, dedicated soft-ware is not yet available, and its logarithmic transformation doesnot help daily use.On these bases, we herein provide a counterpoint to L-GrAFToffering additional evidence about early liver graft dysfunctionprediction. Starting from the seminal study by Agopian et al.,1 wehave recently validated the L-GrAFT10 on a population of 1,609patients transplanted between 2016 and 2017 in 14 Italiancenters and obtained a C-statistic of 0.72.5 Using the original L-GrAFT components, we have further refined and simplified the L-GrAFT10 formula reducing the number of data entries from 40 to17. The beta-coefficients were re-calculated, and additional donorand recipient parameters were tested in 8 models. The finalcomprehensive score for EAFassessment, namely the earlyallograftfailure simplified estimation (EASE) score, was internally validatedthrough bootstrap and externally validated on a UK database (2centers, 570 patients). The characteristics of both databases and theEASE-score formula are reported in Table S1 and S2, respectively.Notably, the overall prevalence of grafts from donors after cardiacdeath (DCD) and machine perfused (MP) grafts was 6.8% and5.8%, respectively. Because neither of these categories weresignificant predictors, EASE can also be used as a precisealgorithm to measure graft quality in translational studies thatinclude high-risk DCD and MP grafts.Unlike L-GrAFT10, the EASE score does not include INR. Its AUCand slope are based on a lower number of evaluations (4 vs. 10),and no logarithmic transformation was used for bilirubin.Furthermore, the EASE score includes the following, easy-to-be-retrieved additional parameters: model for end-stage liver dis-ease (MELD) score at transplant, number of intraoperativelytransfused packed red blood cells (PRBCs), hepatic vessel throm-bosis on day 10, and center volume (>−70 or between 36 and 69cases per year).As a result, the EASE achieved a C-statistic of 0.87 (95% CI0.83–0.91) in the derivation set and outperformed all previouslydeveloped scores to predict EAF (Table 1).1–4,6–8With respect to thecomparison with the L-GrAFT (C-statistic 0.72; 95% CI 0.65–0.78),the difference was significant using the DeLong test.9 Althoughone could argue that a researcher-derived bias cannot beexcluded, we invite the L-GrAFT developers to test the EASE scoreon both the North-American and COPE databases.The EASE score also achieved an excellent C-statistic (0.93; 95%CI 0.89–0.97) for prediction of EAF at 30 days and was furthervalidated in the UK cohort with a C-statistic of 0.78. Furthermore, itallows for stratificationof liver grafts into 5 classes,with thehighestone including cases to be referred for early retransplantation. Theonline EASE-score calculator is available atListing a patient for retransplant is often challenging, and sur-geons and transplant hepatologists are frequently reluctant in theabsence of objective signs of graft failure.10 In our opinion, theinclusion of MELD, PRBCs, and hepatic vessel thrombosis isessential for an innovative and comprehensive definition of EAF.Notably, thrombosis of a hepatic vessel is a well-known indicationfor early retransplant. However, medical and endovascular treat-ments of thrombosis are nowmore efficacious than in the past, andseveral patients without associated liver failure recover. From thisperspective, parenchymal and vascular causes of failure are linkedinan innovativedefinitionof EAF. Predictionof90-dayoutcomeandearly identificationofpatients inneedof retransplantation remainapriority. The choice of the best algorithm requiresmultiple externalvalidation studies. A further step could be to design a prospectiveinternational validation study to enroll a largernumberof cases andinclude series from small-volume centers.Financial supportThe authors received no financial support to produce thismanuscript.Conflict of interestThe authors declare no conflicts of interest that pertain to thiswork.Please refer to the accompanying ICMJE disclosure forms forfurther details.Authors’ contributionsAWA and QL wrote the letter, UC, RR and PDS revised andapproved the final version of the letter.Data availability statementThe data that support the findings of this study are availablefrom the corresponding author, upon request.Supplementary dataSupplementary data to this article can be found online at https://doi/org/10.1016/j.jhep.2020.12.009.Table 1. Comparison between EASE-score and other prognostic scorespredictive of EAF.*C-statistic 95% CI p valueEASE score5 0.87 0.83–0.91DRI8 0.53 0.46–0.59 <0.001EAD4 0.70 0.63–0.75 <0.001D-MELD6 0.60 0.54–0.67 <0.001New ET-DRI7 0.55 0.49–0.62 <0.001MEAF3 0.73 0.67–0.79 <0.001L-GrAFT102 0.72 0.65–0.78 <0.001DRI, Donor Risk Index; EAD, Early Allograft Dysfunction score; D-MELD, Donor age xMELDscore;NewET-DRI, NewEuro-TransplantDonorRisk Index;MEAF,Model for EarlyAllograft Failure score; L-GrAFT10, Liver Graft Assessment Following Transplantation.EASE score shows the highest C-statistic at 90 days. The p values refer to the comparisonof the indicated score against EASE-score. EASE-score has a high discrimination ability(absence of overlap of 95% CI between EASE score and other scores).*ClinicalTrials.gov (NCT03858088).730 Journal of Hepatology 2021 vol. 75 j 725–756Letters to the EditorReferences[1] Agopian VG, Markovic D, Klintmalm GB, Saracino G, Chapman WC,Vachharajani N, et al. Multicenter validation of the liver graft assessmentfollowing transplantation (L-GrAFT) score for the assessment of earlyallograft dysfunction. J Hepatol 2021;74:881–892.[2] Agopian VG, Harlander-Locke MP, Markovic D, Dumronggittigule W, Xia V,Kaldas FM, et al. Evaluation of early allograft function using the liver graftassessment following transplantation risk score model. JAMA Surg2018;153:436–444.[3] Pareja E, Cortes M, Hervás D, Mir J, Valdivieso A, Castell JV, et al. A scoremodel for the continuous grading of early allograft dysfunction severity.Liver Transpl 2015;21:38–46.[4] Olthoff KM, Kulik L, Samstein B, Kaminski M, Abecassis M, Emond J, et al.Validation of a current definition of early allograft dysfunction in liver trans-plant recipients and analysis of risk factors. Liver Transpl 2010;16:943–949.[5] Avolio AW, Franco A, Schlegel A, Lai Q, Meli S, Burra P, et al. Developmentand validation of a comprehensive model to estimate early allograftfailure among patients requiring early liver retransplant. Jama Surg 2020.https://doi.org/10.1001/jamasurg.2020.4095. Published online October28. Epub ahead of print.[6] Avolio AW, Agnes S, Cillo U, Lirosi MC, Romagnoli R, Baccarani U, et al. , theItalian survival calculator to optimize donor to recipient matching and toidentify the unsustainable matches in liver transplantation. Transpl Int2012;25:294–301. http://www.DMELD.com.[7] Braat AE, Blok JJ, Putter H, Adam R, Burroughs AK, Rahmel AO, et al. TheEurotransplant donor risk index in liver transplantation: ET-DRI. Am JTranspl 2012;12:2789–2796.[8] Feng S, Goodrich NP, Bragg-Gresham JL, Dykstra DM, Punch JD,DebRoy MA, et al. Characteristics associated with liver graft failure: theconcept of a donor risk index. Am J Transpl 2006;6:783–790.[9] DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas undertwo or more correlated receiver operating characteristic curves: anonparametric approach. Biometrics 1988;44:837–845.[10] Avolio AW, Agnes S, Chirico ASA, Castagneto M. Primary dysfunction afterliver transplantation: donor or recipient fault? Transplant Proc 1999;31(1–2):434–436. https://doi.org/10.1016/s0041-1345(99)00910-0. 10083176.Alfonso W. Avolio1,2,*Quirino Lai3Umberto Cillo4Renato Romagnoli5Paolo De Simone61General Surgery and Liver Transplantation Unit, Fondazione PoliclinicoUniversitario Agostino Gemelli IRCCS, Rome, Italy2Università Cattolica del Sacro Cuore, Rome, Italy3General Surgery and Transplantation Unit, Policlinico UniversitarioUmberto I, Rome, Italy4Hepatobiliary Surgery and Liver Transplantation Unit, UniversityHospital, Padua, Italy5General Surgery and Liver Transplant Unit, Molinette UniversityHospital, Turin, Italy6Hepatobiliary Surgery and Liver Transplantation, University HospitalPisa, Italy*Corresponding author. Address: Dept of Surgery, General Surgeryand Liver Transplant Unit, Fondazione Policlinico UniversitarioAgostino Gemelli IRCCS, Rome, Italy.E-mail address: alfonso.avolio@unicatt.it (A.W. Avolio)An unequivocal formula to calculate L-GrAFT score is neededTo the Editor:We read with interest the article by Agopian et al. entitled:“Multicenter validation of the liver graft assessment followingtransplantation (L-GrAFT) score for assessment of early allograftdysfunction”.1 Because early liver allograft dysfunction is difficultto assess, L-GrAFT emerges as a promising tool to detect suchTable 1. An example of the impact of rounding of coefficients on risk estimates using the unrounded (L-GrAFT10 calculator provided in the supplement ofthe Agopian et al. study1) and rounded coefficients.Predictor Log OR OR Variable value Log OR roundedIntercept 9.77AUC log AST -0.429459177 0.650861 51.73551342 -0.429AUC log AST, squared 0.004621305 1.004632 2676.563348 0.005Slope log AST (early) 4.607190144 100.2022 -0.205468062 4.607Slope log AST (early), squared 4.412900349 82.50842 0.042217125 4.413Log max INR 0.889739754 2.434496 0.405465108 0.890AUC log TBIL -0.04852114 0.9526372 22.36992196 -0.049AUC log TBIL, squared 0.00362542 1.003632 500.4134084 0.004Slope log TBIL 5.336266599 207.7357 -0.010094796 5.336AUC log PLT -0.046205313 0.9548459 44.91034035 -0.046Slope log PLT -5.248974974 0.0052529 0.171097045 -5.249Slope log PLT squared 13.08633488 482306.4 0.029274199 13.086L-GrAFT10 -2.39 With rounded factors: -1.17Odds -> 0.09 0.31Individualized risk 8.36% 23.68%AST, aspartate aminotransferase; AUC, area under curve calculated as 10-day mean * 10; early slope, slope of linear regression of values in first 7 days post-transplant; INR,international normalized ratio; OR, odds ratio; PLT, platelets; TBIL, total bilirubin.Keywords: Liver Transplantation; Liver Allograft; Risk Scores.Received 5 February 2021; received in revised form 7 March 2021; accepted 24 March2021; available online 29 March 2021https://doi.org/10.1016/j.jhep.2021.03.019Journal of Hepatology 2021 vol. 75 j 725–756 731

L-{GrAFT} and {EASE} scores in liver transplantation. Need for a reciprocal external validation and comparison with other scores

https://iris.unito.it/bitstream/2318/1807149/3/PIIS0168827820338484.pdf

L-{GrAFT} and {EASE} scores in liver transplantation. Need for a reciprocal external validation and comparison with other scores

Abstract

Similar works

Full text

Available Versions

Institutional Research Information System University of Turin