Predicting survival after liver transplantation in patients with hepatocellular carcinoma using the LiTES-HCC score
Open accessAbstract
Background & aims Liver transplant priority in the US and Europe follows the 'sickest-first' principle. However, for patients with hepatocellular carcinoma (HCC), priority is based on binary tumor criteria to expedite transplant for patients with 'acceptable' post-transplant outcomes. Newer risk scores developed to overcome limitations of these binary criteria are insufficient to be used for waitlist priority as they focus solely on HCC-related pre-transplant variables. We sought to develop a risk score to predict post-transplant survival for patients using HCC- and non-HCC-related variables.Methods We performed a retrospective cohort study using national registry data on adult deceased-donor liver transplant (DDLT) recipients with HCC from 2/27/02-12/31/18. We fit Cox regression models focused on 5- and 10-year survival to estimate beta coefficients for a risk score using manual variable selection. We then calculated absolute predicted survival time and compared it to available risk scores.Results Among 6,502 adult DDLT recipients with HCC, 11 variables were selected in the final model. The AUCs at 5- and 10-years were: 0.62, 95% CI 0.57-0.67 and 0.65, 95% CI 0.58-0.72, which was not statistically significantly different to the Metroticket and HALT-HCC scores. The LiTES-HCC score was able to discriminate patients based on post-transplant survival among those meeting Milan and UCSF criteria.Conclusion We developed and validated a risk score to predict post-transplant survival for patients with HCC. By including HCC- and non-HCC-related variables (e.g., age, chronic kidney disease), this score could allow transplant professionals to prioritize patients with HCC in terms of predicted survival. In the future, this score could be integrated into survival benefit-based models to lead to meaningful improvements in life-years at the population level.Lay summary We created a risk score to predict how long patients with liver cancer will live if they get a liver transplant. In the future, this could be used to decide which waitlisted patients should get the next transplant.
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Despite the MELD score's many benefits, about 15 to 20% of patients' survival cannot be reliably predicted by the MELD score.
“Despite the MELD score’s many benefits, about 15 to 20% of patients’ survival cannot be reliably predicted by the MELD score.”
From Blockchain and Artificial Intelligence Technology in E-Health (2021) · cites this paper as Goldberg et al. 2021
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Erdogan, D., Heijnen, B. H. M., Bennink, R. J., Kok, M., Dinant, S., Straatsburg, I. H., Gouma, D. J., & van Gulik, T. M. (2004) · Liver International · doi:10.1111/j.1478-3231.2004.00901.x · Cited by 11,656 · see citing works
Mazzaferro, V., Regalia, E., Doci, R., Andreola, S. A., Pulvirenti, A., Bozzetti, F., Montalto, F., Ammatuna, M., Morabito, A., & Gennari, L. (1996) · New England Journal of Medicine · doi:10.1056/nejm199603143341104 · Cited by 7,173 · see citing works
Acute Abdomen: A Rare Case of Ruptured Hepatocellular Carcinoma
Gloor, S., Jensen, K. O., Breitenstein, S., Binkert, C. A., Angst, E., & Hetzer, F. H. (2017) · Case Reports in Gastroenterology · doi:10.1159/000463378 · Cited by 5,370 · see citing works
A Model to Predict Survival in Patients With End–Stage Liver Disease
Kamath, P. S., Wiesner, R. H., Malinchoc, M., Kremers, W. K., Therneau, T. M., Kosberg, C. L., D’Amico, G., Dickson, R. E., & Kim, W. R. (2001) · Hepatology · doi:10.1053/jhep.2001.22172 · Cited by 4,989 · see citing works
Levey, A., Eckardt, K., Tsukamoto, Y., Levin, A., Coresh, J., Rossert, J., de Zeeuw, D., Hostetter, T., Lameire, N., & Eknoyan, G. (2005) · Kidney International · doi:10.1111/j.1523-1755.2005.00365.x · Cited by 3,963 · see citing works
PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies
Wolff, R. F., Moons, K. G. M., Riley, R. D., Whiting, P. F., Westwood, M., Collins, G. S., Reitsma, J. B., Kleijnen, J., Mallett, S., & for the PROBAST Group† (2019) · Annals of Internal Medicine · doi:10.7326/m18-1376 · Cited by 2,984 · see citing works
Mazzaferro, V., Llovet, J. M., Miceli, R., Bhoori, S., Schiavo, M., Mariani, L., Camerini, T., Roayaie, S., Schwartz, M., Grazi, G. L., et al. (2008) · The Lancet Oncology · doi:10.1016/s1470-2045(08)70284-5 · Cited by 2,048 · see citing works
A Comprehensive Risk Quantification Score for Deceased Donor Kidneys: The Kidney Donor Risk Index
Rao, P. S., Schaubel, D. E., Guidinger, M. K., Andreoni, K. A., Wolfe, R. A., Merion, R. M., Port, F. K., & Sung, R. S. (2009) · Transplantation · doi:10.1097/tp.0b013e3181ac620b · Cited by 1,079 · see citing works
Duvoux, C., Roudot‐Thoraval, F., Decaens, T., Pessione, F., Badran, H. M., Piardi, T., Francoz, C., Compagnon, P., Vanlemmens, C., Dumortier, J., et al. (2012) · Gastroenterology · doi:10.1053/j.gastro.2012.05.052 · Cited by 953 · see citing works
Principles for allocation of scarce medical interventions
Persad, G., Wertheimer, A., & Emanuel, E. J. (2009) · The Lancet · doi:10.1016/s0140-6736(09)60137-9 · Cited by 929 · see citing works
Self-citationYounossi, Z. M., Stepanova, M., Ong, J. P., Jacobson, I. M., Bugianesi, E., Duseja, A. K., Eguchi, Y., Wong, V. W., Negro, F., Yilmaz, Y. N., et al. (2018) · Clinical Gastroenterology and Hepatology · doi:10.1016/j.cgh.2018.05.057 · Cited by 807 · see citing works
Wong, R. J., Cheung, R. C., & Ahmed, A. (2013) · Hepatology · doi:10.1002/hep.26986 · Cited by 720 · see citing works
mRECIST for HCC: Performance and novel refinements
Llovet, J. M., & Lencioni, R. A. (2020) · Journal of Hepatology · doi:10.1016/j.jhep.2019.09.026 · Cited by 689 · see citing works
Mazzaferro, V., Sposito, C., Zhou, J., Pinna, A. D., De Carlis, L., Fan, J., Cescon, M., Di Sandro, S., Yi-feng, H., Lauterio, A., et al. (2018) · Gastroenterology · doi:10.1053/j.gastro.2017.09.025 · Cited by 655 · see citing works
Application of Artificial Intelligence to Gastroenterology and Hepatology
Berre, C. L., Sandborn, W. J., Aridhi, S., Devignes, M., Fournier, L. S., Smaïl‐Tabbone, M., Danese, S., & Peyrin‐Biroulet, L. (2019) · Gastroenterology · doi:10.1053/j.gastro.2019.08.058 · Cited by 528 · see citing works
Multivariable Analysis: A Primer for Readers of Medical Research
Katz, M. H. (2003) · Annals of Internal Medicine · doi:10.7326/0003-4819-138-8-200304150-00012 · Cited by 400 · see citing works
Yao, F. Y., Bass, N. M., Nikolai, B., Davern, T. J., Kerlan, R. K., Wu, V., Ascher, N. L., & Roberts, J. P. (2002) · Liver Transplantation · doi:10.1053/jlts.2002.34923 · Cited by 389 · see citing works
A prospective study on downstaging of hepatocellular carcinoma prior to liver transplantation
Yao, F. Y., Hirose, R., LaBerge, J. M., Davern, T. J., Bass, N. M., Kerlan, R. K., Merriman, R. B., Feng, S., Freise, C. E., Ascher, N. L., et al. (2005) · Liver Transplantation · doi:10.1002/lt.20526 · Cited by 288 · see citing works
Toso, C., Meeberg, G., Hernandez‐Alejandro, R., Dufour, J., Marotta, P., Majno, P. E., & Kneteman, N. M. (2015) · Hepatology · doi:10.1002/hep.27787 · Cited by 281 · see citing works
Performance standards for therapeutic abdominal paracentesis
Grabau, C. M., Crago, S. F., Hoff, L. K., Simon, J. A., Melton, C. A., Ott, B. J., & Kamath, P. S. (2004) · Hepatology · doi:10.1002/hep.20317 · Cited by 280 · see citing works
Hameed, B., Mehta, N. J., Sapisochín, G., Roberts, J. P., & Yao, F. Y. (2014) · Liver Transplantation · doi:10.1002/lt.23904 · Cited by 279 · see citing works
Fisher, R. A., Kulik, L., Freise, C. E., Lok, A. S.-F., Shearon, T. H., Brown, R. S., Ghobrial, R. M., Fair, J. H., Olthoff, K. M., Kam, I., et al. (2007) · American Journal of Transplantation · doi:10.1111/j.1600-6143.2007.01802.x · Cited by 272 · see citing works
Notarpaolo, A., Layese, R., Magistri, P., Gambato, M., Colledan, M., Magini, G. M., Miglioresi, L., Vitale, A., Vennarecci, G., Ambrosio, C. D., et al. (2016) · Journal of Hepatology · doi:10.1016/j.jhep.2016.10.038 · Cited by 224 · see citing works
Su, F., Yu, L., Berry, K., Liou, I. W., Landis, C. S., Rayhill, S. C., Reyes, J. D., & Ioannou, G. N. (2015) · Gastroenterology · doi:10.1053/j.gastro.2015.10.043 · Cited by 207 · see citing works
Allen, A. M., Heimbach, J. K., Larson, J. J., Mara, K. C., Kim, W. R., Kamath, P. S., & Therneau, T. M. (2018) · Transplantation · doi:10.1097/tp.0000000000002196 · Cited by 185 · see citing works
VanWagner, L. B., Harinstein, M. E., Runo, J. R., Darling, C., Serper, M., Hall, S. A., KOBASHIGAWA, J. A., & Hammel, L. L. (2017) · American Journal of Transplantation · doi:10.1111/ajt.14531 · Cited by 162 · see citing works
Heimbach, J. K., Hirose, R., Stock, P. G., Schladt, D. P., Xiong, H., Liu, J., Olthoff, K. M., Harper, A., Snyder, J. J., Israni, A. K., et al. (2015) · Hepatology · doi:10.1002/hep.27704 · Cited by 129 · see citing works
Is it Time to Abandon the Milan Criteria?
Halazun, K. J., Tabrizian, P., Najjar, M., Florman, S. S., Schwartz, M., Michelassi, F., Samstein, B., Brown, R. S., Emond, J. C., Busuttil, R. W., et al. (2018) · Annals of Surgery · doi:10.1097/sla.0000000000002964 · Cited by 122 · see citing works
Vitale, A., Volk, M. L., Feo, T. M. D., Burra, P., Frigo, A. C., Morales, R., Carlis, L. G. D., Belli, L. S., Colledan, M., FAGIUOLI, S., et al. (2013) · Journal of Hepatology · doi:10.1016/j.jhep.2013.10.010 · Cited by 110 · see citing works
Sasaki, K., Firl, D. J., Hashimoto, K., Fujiki, M., Diago‐Uso, T., Quintini, C., Eghtesad, B., Fung, J. J., Aucejo, F., & Miller, C. M. (2017) · The Lancet. Gastroenterology & hepatology · doi:10.1016/s2468-1253(17)30106-1 · Cited by 100 · see citing works
Cotter, T. G., Paul, S., Sandıkçı, B., Couri, T., Bodzin, A. S., Little, E. C., Sundaram, V., & Charlton, M. (2019) · Liver Transplantation · doi:10.1002/lt.25424 · Cited by 95 · see citing works
Cullaro, G., Verna, E. C., Lee, B. P., & Lai, J. C. (2019) · Liver Transplantation · doi:10.1002/lt.25694 · Cited by 82 · see citing works
Cucchetti, A., Serenari, M., Sposito, C., Sandro, S. D., Mosconi, C., Vicentin, I., Garanzini, E. M., Mazzaferro, V., Carlis, L. G. D., Golfieri, R., et al. (2020) · Journal of Hepatology · doi:10.1016/j.jhep.2020.03.018 · Cited by 80 · see citing works
Berry, K., & Ioannou, G. N. (2015) · Gastroenterology · doi:10.1053/j.gastro.2015.05.025 · Cited by 76 · see citing works
Penston, J. G. (2011) · BMJ · doi:10.1136/bmj.d6395 · Cited by 71 · see citing works
Risk factor model to predict venous thromboembolism in hospitalized medical patients
Rothberg, M. B., Lindenauer, P. K., Lahti, M., Pekow, P. S., & Selker, H. P. (2011) · Journal of Hospital Medicine · doi:10.1002/jhm.888 · Cited by 70 · see citing works
Vitale, A., Cucchetti, A., Qiao, G. L., Cescon, M., Li, J., Morales, R., Frigo, A. C., Xia, Y., Tuci, F., Shen, F., et al. (2014) · Journal of Hepatology · doi:10.1016/j.jhep.2014.01.022 · Cited by 58 · see citing works
Key Concepts and Limitations of Statistical Methods for Evaluating Biomarkers of Kidney Disease
Parikh, C. R., & Thiessen‐Philbrook, H. (2014) · Journal of the American Society of Nephrology · doi:10.1681/asn.2013121300 · Cited by 58 · see citing works
Ratzinger, F., Haslacher, H., Perkmann, T., Pinzan, M., Anner, P., Makristathis, A., Burgmann, H., Heinze, G., & Dorffner, G. (2018) · Scientific Reports · doi:10.1038/s41598-018-30236-9 · Cited by 55 · see citing works
Vitale, A., Huo, T.-L., Cucchetti, A., Lee, Y.-H., Volk, M. L., Frigo, A. C., Cescon, M., Tuci, F., Pinna, A. D., & Cillo, U. (2014) · Annals of Surgical Oncology · doi:10.1245/s10434-014-4099-2 · Cited by 53 · see citing works
Firl, D. J., Sasaki, K., Agopian, V. G., Gorgen, A., Kimura, S., Dumronggittigule, W., McVey, J. C., Iesari, S., Mennini, G., Vitale, A., et al. (2019) · Hepatology · doi:10.1002/hep.30838 · Cited by 49 · see citing works
Nonparametric estimation of time‐dependent ROC curves conditional on a continuous covariate
Rodríguez‐Álvarez, M. X., Meira‐Machado, L., Abu‐Assi, E., & Raposeiras‐Roubín, S. (2015) · Statistics in Medicine · doi:10.1002/sim.6769 · Cited by 44 · see citing works
Alver, S., Lorenz, D. J., Marvin, M. R., & Brock, G. N. (2016) · Liver Transplantation · doi:10.1002/lt.24503 · Cited by 29 · see citing works
Combescure, C., Perneger, T., Weber, D. C., Daurès, J., & Foucher, Y. (2013) · Epidemiology · doi:10.1097/ede.0000000000000004 · Cited by 27 · see citing works
Mahmud, N., Hoteit, M. A., & Goldberg, D. S. (2020) · Liver Transplantation · doi:10.1002/lt.25787 · Cited by 26 · see citing works
Self-citationReporting functional status in UNOS : The weakness of the Karnofsky Performance Status Scale
Wang, C. W., & Lai, J. C. (2017) · Clinical Transplantation · doi:10.1111/ctr.13004 · Cited by 23 · see citing works
Firl, D. J., Kimura, S., McVey, J. C., Hashimoto, K., Yeh, H., Miller, C. M., Markmann, J. F., Sasaki, K., & Aucejo, F. (2018) · Hepatology · doi:10.1002/hep.29907 · Cited by 23 · see citing works
Dugas, A. F., Hsieh, Y., LoVecchio, F., Moran, G. J., Steele, M. T., Talan, D. A., Rothman, R. E., Stubbs, A. M., Kemble, L., Beckham, D., et al. (2019) · Clinical Infectious Diseases · doi:10.1093/cid/ciz171 · Cited by 22 · see citing works
Differences in Posttransplant Hepatocellular Carcinoma Recurrence by Etiology of Liver Disease
Mahmud, N., Shaked, A. A., Olthoff, K. M., & Goldberg, D. S. (2018) · Liver Transplantation · doi:10.1002/lt.25363 · Cited by 12 · see citing works
Self-citationHarrell, F., Jr. (1996) · doi:10.1002/(sici)1097-0258(19960229)15:4
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Blockchain and Artificial Intelligence Technology in E-Health
Tagde, P., Tagde, S., Bhattacharya, T., Tagde, P., Chopra, H., Akter, R., Kaushik, D., & Rahman, M. H. (2021) · Environmental Science and Pollution Research · doi:10.1007/s11356-021-16223-0 · Cited by 281 · see citing works
“The MELD score will be further refined and validated in the future (Goldberg et al. 2021).”
BackgroundRevisiting Surgical Strategies for Hepatocellular Carcinoma With Microvascular Invasion
Zhang, E., Cheng, Q., Huang, Z., & Dong, W. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.691354 · Cited by 53 · see citing works
He, X., Xu, S., Tang, L., Ling, S., Wei, X., & Xu, X. (2023) · International Journal of Surgery · doi:10.1097/js9.0000000000000806 · Cited by 38 · see citing works
“Many other studies also indicated AFP as a potent prognostic risk factor and enlarge the population of LT candidates, including but not limited to 5-5-500, total tumor volume (TTV)/AFP, and the LiTES-HCC score [36 – 38] .”
BackgroundKim, S. J., & Kim, J. M. (2022) · Clinical and Molecular Hepatology · doi:10.3350/cmh.2022.0060 · Cited by 36 · see citing works
Lerut, J. P., Foguenne, M., & Lai, Q. (2021) · Updates in Surgery · doi:10.1007/s13304-021-01078-4 · Cited by 30 · see citing works
Książek, W., Turza, F., & Pławiak, P. (2022) · International Journal for Numerical Methods in Biomedical Engineering · doi:10.1002/cnm.3599 · Cited by 25 · see citing works
Accurate long‐term prediction of death for patients with cirrhosis
Goldberg, D. S., Mantero, A. M. A., Kaplan, D. E., Delgado, C., John, B. V., Nuchovich, N., Emanuel, E., & Reese, P. P. (2022) · Hepatology · doi:10.1002/hep.32457 · Cited by 19 · see citing works
“, posttransplant survival).[31,32] Such an approach provides a superior population- based approach to allocation that ensures maximal lifeyears gained from the scarce supply of donor livers but requires a tool such as LTCS to predict cirrhosis- related mortality.”
BackgroundSelf-citationLiver transplantation in malignant disease
Lang, S. A., Bednarsch, J., Czigány, Z., Joechle, K., Kroh, A., Amygdalos, I., Strnad, P., Bruns, T., Heise, D., Ulmer, T. F., et al. (2021) · World Journal of Clinical Oncology · doi:10.5306/wjco.v12.i8.623 · Cited by 16 · see citing works
Trends in Survival for Adult Organ Transplantation
Patrick, G., Hickner, B. T., Goli, K., Ferreira, L. D., Goss, J. A., & Rana, A. A. (2024) · Annals of Surgery Open · doi:10.1097/as9.0000000000000383 · Cited by 15 · see citing works
“21,31 In addition, new allocation systems have been developed with the intent to increase graft survival and waitlist survival, such as the use of the MELD score and Share 35.”
BackgroundCillo, U., Vitale, A., Volk, M. L., Frigo, A. C., Feltracco, P., Cattelan, A. M., Brancaccio, G., Feltrin, G., Angeli, P., Burra, P., et al. (2021) · Cancers · doi:10.3390/cancers13061416 · Cited by 11 · see citing works
“T2 HCC (single nodule 2–5 cm, or 2–3 nodules ≤ 3 cm) now represents the vast majority of listed HCC patients [23], reaching almost 40% of overall transplant indications in Italy [6,24].”
BackgroundRecurrence risk prediction models for hepatocellular carcinoma after liver transplantation
Zhang, X., Chen, C., Wang, Y., & Xu, J. (2024) · Journal of Gastroenterology and Hepatology · doi:10.1111/jgh.16693 · Cited by 9 · see citing works
Lai, Q., lesari, S., & Lerut, J. P. (2022) · Current Opinion in Organ Transplantation · doi:10.1097/mot.0000000000000955 · Cited by 9 · see citing works
Survival benefit from liver transplantation for patients with and without hepatocellular carcinoma
Goudsmit, B. F. J., Prosepe, I., Tushuizen, M. E., Mazzaferro, V., Alwayn, I. P. J., van Hoek, B., Braat, A. E., & Putter, H. (2023) · JHEP Reports · doi:10.1016/j.jhepr.2023.100907 · Cited by 9 · see citing works
“6,10,15,17,24 Therefore, in a large and recent United States cohort, this study aims to construct a single bene fi t score for patients with and without HCC.”
Schmauch, B., Elsoukkary, S. S., Moro, A., Raj, R., Wehrle, C. J., Sasaki, K., Caldéraro, J., Sin‐Chan, P., Aucejo, F., & ROBERTS, D. E. (2023) · Journal of Pathology Informatics · doi:10.1016/j.jpi.2023.100360 · Cited by 8 · see citing works
“The authors received no speci fi c funding for this work.”
BackgroundWu, F., Sun, H., Zhang, S., Zhou, C., Huang, P., Xiao, Y., Yang, C., & Zeng, M. (2023) · Journal of Hepatocellular Carcinoma · doi:10.2147/jhc.s410237 · Cited by 7 · see citing works
“Recently, a risk scoring system has been reported as a novel and effective prediction model commonly used clinically.(21,22) Based on the total score, it generates the risk of MVI in patients with resectable mHCC, allowing a simple risk stratification.”
MethodTırnova, İ., & Kanmaz, T. (2025) · Frontiers in Surgery · doi:10.3389/fsurg.2025.1594361 · Cited by 6 · see citing works
Eden, J., Müller, P. C., Kuemmerli, C., Peters, F., Litke, T., Kranich, A. L., Kremer, A. E., von Felten, S., Dutkowski, P., HOPE4Cancer Trial Investigators, et al. (2025) · Trials · doi:10.1186/s13063-025-09120-1 · Cited by 5 · see citing works
“However, HCC recurrence may occur after LT and is reported in up to 15% of cases, associated with poor outcome [4, 5].”
Predicting long-term survival among patients with HCC
Goldberg, D. S., Reese, P. P., Kaplan, D. A., Zarnegarnia, Y., Gaddipati, N., Gaddipati, S., John, B. V., & Blandon, C. (2024) · Hepatology Communications · doi:10.1097/hc9.0000000000000581 · Cited by 4 · see citing works
“[66] In the example shown, we provide expected 3-year survival for patients with HCC, conditioned on them surviving 2 years after diagnosis, compared to their expected 3-year posttransplant survival.”
BackgroundSelf-citationWang, X., Chen, J., Lin, L., Li, Y., Tao, Q., Lang, Z., Zheng, J., & Yu, Z. (2023) · BMC Cancer · doi:10.1186/s12885-023-10766-w · Cited by 5 · see citing works
“However, the prognosis of HCC patients after transplantation still remains poor because of the differences in tumor burden and liver function [6, 7].”
BackgroundOrci, L. A., Combescure, C., Fink, M. A., Oldani, G., Compagnon, P., Andrès, A., Berney, T., & Toso, C. (2021) · Transplant International · doi:10.1111/tri.14161 · Cited by 5 · see citing works
Current status of liver transplantation for non‐B non‐C liver cirrhosis and hepatocellular carcinoma
Nishio, T., Ito, T., Hata, K., Taura, K., & Hatano, E. (2022) · Annals of Gastroenterological Surgery · doi:10.1002/ags3.12612 · Cited by 4 · see citing works
Kim, D. G., Yim, S. H., Min, E., Choi, M. C., Joo, D. J., Kim, M. S., & Lee, J. G. (2023) · Scientific Reports · doi:10.1038/s41598-023-46803-8 · Cited by 4 · see citing works
mTOR inhibitor reduces nontumour-related death in liver transplantation for hepatocellular carcinoma
Zhang, L., Liu, P., Li, Z., Ling, S., Zhan, Q., Zhou, W., Su, R., Lu, Y., Que, Q., Hong, J., et al. (2024) · Molecular Biomedicine · doi:10.1186/s43556-024-00170-6 · Cited by 4 · see citing works
“In our cohort, the nontumour-related death rate was 29.5%, which was similar to the 26.6% rate reported by Goldberg et al. [7].”
BackgroundResultInfluentialHow to Predict Recurrence After Resection of Hepatocellular Carcinoma
Petruch, N., Bolm, L., Nebbia, M., Arya, S., Ventin, M., Qadan, M., Elias, N., Duhn, J., Rades, D., Dageforde, L. A., et al. (2024) · Anticancer Research · doi:10.21873/anticanres.17404 · Cited by 4 · see citing works
Optimal Liver Transplantation Criteria for Hepatocellular Carcinoma
Yilma, M., & Mehta, N. J. (2023) · Surgical Oncology Clinics of North America · doi:10.1016/j.soc.2023.06.011 · Cited by 3 · see citing works
Voskanyan, S. E., Рудаков, В. С., Сушков, А. И., Башков, А. Н., Губарев, К. К., Попов, М. В., Artemyev, A. I., Kolyshev, I. Y., Muktarzhan, M., Naydenov, E. V., et al. (2024) · Annaly khirurgicheskoy gepatologii = Annals of HPB surgery · doi:10.16931/1995-5464.2024-4-66-80 · Cited by 2 · see citing works
DCP as a biomarker for TACE efficacy in hepatocellular carcinoma
Xie, H., Li, Y., Yang, J., Tan, Y., Xu, J., & Yang, X. (2025) · Frontiers in Oncology · doi:10.3389/fonc.2025.1560210 · Cited by 2 · see citing works
New prognostic model for liver transplantation outcomes in hepatocellular carcinoma
Voskanyan, S. E., Рудаков, В. С., Сушков, А. И., Попов, М. В., Башков, А. Н., Губарев, К. К., Artemyev, A. I., Kolyshev, I. Y., Muktarzhan, M., Pashkov, A. N., et al. (2024) · Transplantologiya The Russian Journal of Transplantation · doi:10.23873/2074-0506-2024-16-3-278-290 · Cited by 2 · see citing works
Clarke, L. (2009) · Durham e-Theses (Durham University) · Cited by 2 · see citing works
Simulating the impact of survival benefit-based liver transplant organ allocation
Goldberg, D., Blandon, C., Delgado, C., John, B. V., Emanuel, E., Kaplan, D. E., & Reese, P. P. (2025) · Hepatology · doi:10.1097/hep.0000000000001338 · Cited by 1 · see citing works
Self-citationPrognostic risk scores for liver transplantation: game changers or statistical artworks?
Claasen, M. P. A. W., Ivanics, T., Gravely, A., & Sapisochín, G. (2021) · HepatoBiliary Surgery and Nutrition · doi:10.21037/hbsn-21-258 · Cited by 1 · see citing works
“Though the models in Figure 1 have resulted in furthering our understanding of HCC, none can be used to determine transplant eligibility, allocation prioritization, or to compare their oncologic outcomes with risk models for alternative HCC treatments (1,7-12).”
BackgroundMethodInfluentialSehjal, J., Sharples, L. D., Keogh, R. H., Walker, K., Prachalias, A. A., Heaton, N. D., Ivanics, T., van der Meulen, J., & Wallace, D. (2022) · Transplantation · doi:10.1097/tp.0000000000004282
“Also, many studies have developed risk scores to predict post-LT survival in these patients (eg, based on alpha-fetoprotein trends, history of locoregional therapy, etc) that could be extended to UK populations.(26,27) Using the results from this analysis to help create a targeted surveillance program in the UK could…”
BackgroundBlockchain and artificial intelligence: an overview
Malviya, R., Singh, A. K., Sundram, S., Balusamy, B., & Kadry, S. (2023) · Institute of Physics eBooks · doi:10.1088/978-0-7503-5839-2ch1
Liver transplantation meets gastrointestinal cancer
Loosen, S. H., Leyh, C., Neumann, U. P., Bock, H. H., Weigel, C., Luedde, T., & Roderburg, C. (2024) · Zeitschrift für Gastroenterologie · doi:10.1055/a-2226-0123
“The Liver Transplant Expected Survival (LiTES)-HCC score is based on the assumption that most deaths after transplantation for HCC are independent on tumor recurrence [21].”
BackgroundLiver Transplantation: An Updated Criteria Selection for HCC
Duc, N. H. (2024) · IntechOpen eBooks · doi:10.5772/intechopen.1004265
Artificial intelligence in e-health
Karunakaran, N., Maryam, B., Sadiq, M. S., Sıngh, I. P., & Ahmad, M. M. (2024) · The Journal of Community Health Management · doi:10.18231/j.jchm.2024.013
Gundlach, J.-P., Heckl, S. M., Langguth, P., Oberkofler, C. E., Taivankhuu, T., Beckmann, J. H., Becker, T., Braun, F., & Linecker, M. (2025) · Cancers · doi:10.3390/cancers17233829
“In addition, the LiTES score demonstrated the benefit of non-HCC related variables for the discrimination of risk of tumor recurrence after LT while integrating non-HCC related pre-transplant variables, especially relevant previous illnesses [55].”
Wang, X., Chen, J., Lin, L., Li, Y., Tao, Q., Lang, Z., Zheng, J., & Yu, Z. (2024) · Figshare · doi:10.6084/m9.figshare.26578532
- Authors
- Goldberg, D., Mantero, A., Newcomb, C., Delgado, C., Forde, K. A., Kaplan, D. E., John, B., Nuchovich, N., Dominguez, B., Emanuel, E., & Reese, P. P.
- Affiliations
- University of Miami (US)
- University of Pennsylvania (US)
- Philadelphia VA Medical Center (US)
- Bruce W. Carter VA Medical Center (US)
- Corresponding author
- Goldberg, David
- ORCID
- Venue
- Journal of Hepatology
- Publisher
- Elsevier BV
- Published
- 2021-06
- Volume
- 74
- Issue
- 6
- Pages
- 1398-1406
- ISSN
- 0168-8278 (ISSN-L)
- PMC
- PMC8137533
- OpenAlex
- W3120206188
- Cited by
- 38
- References
- 50
- Citations by year
- 2025: 5 · 2024: 11 · 2023: 8 · 2022: 6 · 2021: 7
- FWCI
- 4.44
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Hepatology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Gilead Sciences
- National Institute of Diabetes and Digestive and Kidney Diseases (R01 DK120561)
- AbbVie
- Pfizer
- National Institutes of Health
- Merck
- Topics
- Health Sciences › Medicine › Hepatology › Hepatocellular Carcinoma Treatment and Prognosis
- Health Sciences › Medicine › Surgery › Organ Transplantation Techniques and Outcomes
- Health Sciences › Medicine › Surgery › Transplantation: Methods and Outcomes
- Keywords
- hepatocellular carcinoma, liver transplantation, post-transplant survival, risk score, deceased donor liver transplantation, Milan criteria, UCSF criteria, chronic kidney disease, survival prediction
- MeSH terms
- Aged, Female, Follow-Up Studies, Carcinoma, Hepatocellular, Humans, Liver Neoplasms, Male, Middle Aged, Neoplasm Recurrence, Local, Prognosis, Registries, Research Design, Retrospective Studies, Risk Factors, Tissue Donors, Waiting Lists, Survival Rate, Liver Transplantation, Treatment Outcome, Transplant Recipients
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