Background & Aims: In the context of liver transplantation (LT) for hepatocellular carcinoma (HCC), prediction models are used to ensure that the risk of post-LT recurrence is acceptably low. However, the weighting that ‘response to neoadjuvant therapies’ should have in such models remains unclear. Herein, we aimed to incorporate radiological response into the Metroticket 2.0 model for post-LT prediction of “HCC-related death”, to improve its clinical utility. Methods: Data from 859 transplanted patients (2000-2015) who received neoadjuvant therapies were included. The last radiological assessment before LT was reviewed according to the modified RECIST criteria. Competing-risk analysis was applied. The added value of including radiological response into the Metroticket 2.0 was explored through category-based net reclassification improvement (NRI) analysis. Results: At last radiological assessment prior to LT, complete response (CR) was diagnosed in 41.3%, partial response/stable disease (PR/SD) in 24.9% and progressive disease (PD) in 33.8% of patients. The 5-year rates of “HCC-related death” were 3.1%, 9.6% and 13.4% in those with CR, PR/SD, or PD, respectively (p <0.001). Log10AFP (p <0.001) and the sum of number and diameter of the tumour/s (p <0.05) were determinants of “HCC-related death” for PR/SD and PD patients. To maintain the post-LT 5-year incidence of “HCC-related death” <30%, the Metroticket 2.0 criteria were restricted in some cases of PR/SD and in all cases with PD, correctly reclassifying 9.4% of patients with “HCC-related death”, at the expense of 3.5% of patients who did not have the event. The overall/net NRI was 5.8. Conclusion: Incorporating the modified RECIST criteria into the Metroticket 2.0 framework can improve its predictive ability. The additional information provided can be used to better judge the suitability of candidates for LT following neoadjuvant therapies. Lay summary: In the context of liver transplantation for patients with hepatocellular carcinoma, prediction models are used to ensure that the risk of recurrence after transplantation is acceptably low. The Metroticket 2.0 model has been proposed as an accurate predictor of “tumour-related death” after liver transplantation. In the present study, we show that its accuracy can be improved by incorporating information relating to the radiological responses of patients to neoadjuvant therapies.

Including mRECIST in the Metroticket 2.0 criteria improves prediction of hepatocellular carcinoma-related death after liver transplant / Cucchetti A.; Serenari M.; Sposito C.; Di Sandro S.; Mosconi C.; Vicentin I.; Garanzini E.; Mazzaferro V.; De Carlis L.; Golfieri R.; Spreafico C.; Vanzulli A.; Buscemi V.; Ravaioli M.; Ercolani G.; Pinna A.D.; Cescon M.. - In: JOURNAL OF HEPATOLOGY. - ISSN 0168-8278. - ELETTRONICO. - 73:2(2020), pp. 342-348. [10.1016/j.jhep.2020.03.018]

Including mRECIST in the Metroticket 2.0 criteria improves prediction of hepatocellular carcinoma-related death after liver transplant

Cucchetti A.
Primo
;
Serenari M.
Secondo
;
Mosconi C.;Golfieri R.;Ravaioli M.;Ercolani G.;Pinna A. D.
Penultimo
;
Cescon M.
Ultimo
2020

Abstract

Background & Aims: In the context of liver transplantation (LT) for hepatocellular carcinoma (HCC), prediction models are used to ensure that the risk of post-LT recurrence is acceptably low. However, the weighting that ‘response to neoadjuvant therapies’ should have in such models remains unclear. Herein, we aimed to incorporate radiological response into the Metroticket 2.0 model for post-LT prediction of “HCC-related death”, to improve its clinical utility. Methods: Data from 859 transplanted patients (2000-2015) who received neoadjuvant therapies were included. The last radiological assessment before LT was reviewed according to the modified RECIST criteria. Competing-risk analysis was applied. The added value of including radiological response into the Metroticket 2.0 was explored through category-based net reclassification improvement (NRI) analysis. Results: At last radiological assessment prior to LT, complete response (CR) was diagnosed in 41.3%, partial response/stable disease (PR/SD) in 24.9% and progressive disease (PD) in 33.8% of patients. The 5-year rates of “HCC-related death” were 3.1%, 9.6% and 13.4% in those with CR, PR/SD, or PD, respectively (p <0.001). Log10AFP (p <0.001) and the sum of number and diameter of the tumour/s (p <0.05) were determinants of “HCC-related death” for PR/SD and PD patients. To maintain the post-LT 5-year incidence of “HCC-related death” <30%, the Metroticket 2.0 criteria were restricted in some cases of PR/SD and in all cases with PD, correctly reclassifying 9.4% of patients with “HCC-related death”, at the expense of 3.5% of patients who did not have the event. The overall/net NRI was 5.8. Conclusion: Incorporating the modified RECIST criteria into the Metroticket 2.0 framework can improve its predictive ability. The additional information provided can be used to better judge the suitability of candidates for LT following neoadjuvant therapies. Lay summary: In the context of liver transplantation for patients with hepatocellular carcinoma, prediction models are used to ensure that the risk of recurrence after transplantation is acceptably low. The Metroticket 2.0 model has been proposed as an accurate predictor of “tumour-related death” after liver transplantation. In the present study, we show that its accuracy can be improved by incorporating information relating to the radiological responses of patients to neoadjuvant therapies.
2020
Including mRECIST in the Metroticket 2.0 criteria improves prediction of hepatocellular carcinoma-related death after liver transplant / Cucchetti A.; Serenari M.; Sposito C.; Di Sandro S.; Mosconi C.; Vicentin I.; Garanzini E.; Mazzaferro V.; De Carlis L.; Golfieri R.; Spreafico C.; Vanzulli A.; Buscemi V.; Ravaioli M.; Ercolani G.; Pinna A.D.; Cescon M.. - In: JOURNAL OF HEPATOLOGY. - ISSN 0168-8278. - ELETTRONICO. - 73:2(2020), pp. 342-348. [10.1016/j.jhep.2020.03.018]
Cucchetti A.; Serenari M.; Sposito C.; Di Sandro S.; Mosconi C.; Vicentin I.; Garanzini E.; Mazzaferro V.; De Carlis L.; Golfieri R.; Spreafico C.; Vanzulli A.; Buscemi V.; Ravaioli M.; Ercolani G.; Pinna A.D.; Cescon M.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/796910
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