1. AFP score and metroticket 2.0 perform similarly and could be used in a “within-ALL” clinical decision tool
- Author
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Piñero, F, Costentin, C, Degroote, H, Notarpaolo, A, Boin, I, Boudjema, K, Baccaro, C, Chagas, A, Bachellier, P, Ettorre, G, Poniachik, J, Muscari, F, Dibenedetto, F, Duque, S, Salame, E, Cillo, U, Marciano, S, Vanlemmens, C, Fagiuoli, S, Carrilho, F, Cherqui, D, Burra, P, Van Vlierberghe, H, Lai, Q, Silva, M, Rubinstein, F, Duvoux, C, Conti, F, Scatton, O, Bernard, P, Francoz, C, Durand, F, Dharancy, S, Woehl, M, Laurent, A, Radenne, S, Dumortier, J, Abergel, A, Barbier, L, Houssel-Debry, P, Pageaux, G, Chiche, L, Deledinghen, V, Hardwigsen, J, Gugenheim, J, Altieri, M, Hilleret, M, Decaens, T, Costa, P, de Ataide, E, Quiñones, E, Anders, M, Varón, A, Zerega, A, Soza, A, Machaca, M, Arufe, D, Menéndez, J, Zapata, R, Vilatoba, M, Muñoz, L, Menéndez, R, Maraschio, M, Podestá, L, Mccormack, L, Mattera, J, Gadano, A, Parente García, J, Magini, G, Miglioresi, L, Gambato, M, D'Ambrosio, C, Vitale, A, Colledan, M, Pinelli, D, Magistri, P, Vennarecci, G, Colasanti, M, Giannelli, V, Pellicelli, A, Eduard, C, Samuele, I, Jeroen, D, Jonas, S, Jacques, P, Chris, V, Dirk, Y, Peter, M, Valerio, L, Christophe, M, Olivier, D, Jean, D, Roberto, T, Paul, L, Piñero F., Costentin C., Degroote H., Notarpaolo A., Boin I. F., Boudjema K., Baccaro C., Chagas A., Bachellier P., Ettorre G. M., Poniachik J., Muscari F., Dibenedetto F., Duque S. H., Salame E., Cillo U., Marciano S., Vanlemmens C., Fagiuoli S., Carrilho F., Cherqui D., Burra P., Van Vlierberghe H., Lai Q., Silva M., Rubinstein F., Duvoux C., Conti F., Scatton O., Bernard P. H., Francoz C., Durand F., Dharancy S., Woehl M. l., Laurent A., Radenne S., Dumortier J., Abergel A., Barbier L., Houssel-Debry P., Pageaux G. P., Chiche L., Deledinghen V., Hardwigsen J., Gugenheim J., altieri M., Hilleret M. N., Decaens T., Costa P., de Ataide E. C., Quiñones E., Anders M., Varón A., Zerega A., Soza A., Machaca M. P., Arufe D., Menéndez J., Zapata R., Vilatoba M., Muñoz L., Menéndez R. C., Maraschio M., Podestá L. G., McCormack L., Mattera J., Gadano A., Parente García J. H., Magini G., Miglioresi L., Gambato M., D'Ambrosio C., Vitale A., Colledan M., Pinelli D., Magistri P., Vennarecci G., Colasanti M., Giannelli V., Pellicelli A., Eduard C., Samuele I., Jeroen D., Jonas S., Jacques P., Chris V., Dirk Y., Peter M., Valerio L., Christophe M., Olivier D., Jean D., Roberto T., Paul L. J., Piñero, F, Costentin, C, Degroote, H, Notarpaolo, A, Boin, I, Boudjema, K, Baccaro, C, Chagas, A, Bachellier, P, Ettorre, G, Poniachik, J, Muscari, F, Dibenedetto, F, Duque, S, Salame, E, Cillo, U, Marciano, S, Vanlemmens, C, Fagiuoli, S, Carrilho, F, Cherqui, D, Burra, P, Van Vlierberghe, H, Lai, Q, Silva, M, Rubinstein, F, Duvoux, C, Conti, F, Scatton, O, Bernard, P, Francoz, C, Durand, F, Dharancy, S, Woehl, M, Laurent, A, Radenne, S, Dumortier, J, Abergel, A, Barbier, L, Houssel-Debry, P, Pageaux, G, Chiche, L, Deledinghen, V, Hardwigsen, J, Gugenheim, J, Altieri, M, Hilleret, M, Decaens, T, Costa, P, de Ataide, E, Quiñones, E, Anders, M, Varón, A, Zerega, A, Soza, A, Machaca, M, Arufe, D, Menéndez, J, Zapata, R, Vilatoba, M, Muñoz, L, Menéndez, R, Maraschio, M, Podestá, L, Mccormack, L, Mattera, J, Gadano, A, Parente García, J, Magini, G, Miglioresi, L, Gambato, M, D'Ambrosio, C, Vitale, A, Colledan, M, Pinelli, D, Magistri, P, Vennarecci, G, Colasanti, M, Giannelli, V, Pellicelli, A, Eduard, C, Samuele, I, Jeroen, D, Jonas, S, Jacques, P, Chris, V, Dirk, Y, Peter, M, Valerio, L, Christophe, M, Olivier, D, Jean, D, Roberto, T, Paul, L, Piñero F., Costentin C., Degroote H., Notarpaolo A., Boin I. F., Boudjema K., Baccaro C., Chagas A., Bachellier P., Ettorre G. M., Poniachik J., Muscari F., Dibenedetto F., Duque S. H., Salame E., Cillo U., Marciano S., Vanlemmens C., Fagiuoli S., Carrilho F., Cherqui D., Burra P., Van Vlierberghe H., Lai Q., Silva M., Rubinstein F., Duvoux C., Conti F., Scatton O., Bernard P. H., Francoz C., Durand F., Dharancy S., Woehl M. l., Laurent A., Radenne S., Dumortier J., Abergel A., Barbier L., Houssel-Debry P., Pageaux G. P., Chiche L., Deledinghen V., Hardwigsen J., Gugenheim J., altieri M., Hilleret M. N., Decaens T., Costa P., de Ataide E. C., Quiñones E., Anders M., Varón A., Zerega A., Soza A., Machaca M. P., Arufe D., Menéndez J., Zapata R., Vilatoba M., Muñoz L., Menéndez R. C., Maraschio M., Podestá L. G., McCormack L., Mattera J., Gadano A., Parente García J. H., Magini G., Miglioresi L., Gambato M., D'Ambrosio C., Vitale A., Colledan M., Pinelli D., Magistri P., Vennarecci G., Colasanti M., Giannelli V., Pellicelli A., Eduard C., Samuele I., Jeroen D., Jonas S., Jacques P., Chris V., Dirk Y., Peter M., Valerio L., Christophe M., Olivier D., Jean D., Roberto T., and Paul L. J.
- Abstract
Background & Aims: Two recently developed composite models, the alpha-fetoprotein (AFP) score and Metroticket 2.0, could be used to select patients with hepatocellular carcinoma (HCC) who are candidates for liver transplantation (LT). The aim of this study was to compare the predictive performance of both models and to evaluate the net risk reclassification of post-LT recurrence between them using each model's original thresholds. Methods: This multicenter cohort study included 2,444 adult patients who underwent LT for HCC in 47 centers from Europe and Latin America. A competing risk regression analysis estimating sub-distribution hazard ratios (SHRs) and 95% CIs for recurrence was used (Fine and Gray method). Harrell's adapted c-statistics were estimated. The net reclassification index for recurrence was compared based on each model's original thresholds. Results: During a median follow-up of 3.8 years, there were 310 recurrences and 496 competing events (20.3%). Both models predicted recurrence, HCC survival and survival better than Milan criteria (p <0.0001). At last tumor reassessment before LT, c-statistics did not significantly differ between the two composite models, either as original or threshold versions, for recurrence (0.72 vs. 0.68; p = 0.06), HCC survival, and overall survival after LT. We observed predictive gaps and overlaps between the model's thresholds, and no significant gain on reclassification. Patients meeting both models (“within-ALL”) at last tumor reassessment presented the lowest 5-year cumulative incidence of HCC recurrence (7.7%; 95% CI 5.1-11.5) and higher 5-year post-LT survival (70.0%; 95% CI 64.9-74.6). Conclusions: In this multicenter cohort, Metroticket 2.0 and the AFP score demonstrated a similar ability to predict HCC recurrence post-LT. The combination of these composite models might be a promising clinical approach. Impact and implications: Composite models were recently proposed for the selection of liver transplant (LT
- Published
- 2023