Background and aim. Earlier diagnosis and more effective treatments are improving the survival of patients with HCC. Moreover, the natural history of HCC patients is different from that patients with non-neoplastic indications for liver transplantation. This issue becomes critical to provide an equitable allocation policy to patients listed for transplantation. UNOS adopted a MELD-based policy that assigns the native MELD for patients with stage I HCC and 22 points for patients stage II HCC listed for Liver Transplant (LT), with an additional three points added every 3 months of waiting time in list for the latter. Organs are then assigned on the basis of the MELD score, irrespective of the indication. In countries outside the UNOS area, allocation for HCC patients still misses uniformity. Aim. The aim of the study was to generate an updated prognostic model for HCC applicable to organ allocation. Material and methods. We analysed disease progression (death or progression of HCC beyond T2 stage) in a cohort of 177 consecutive patients that presented with HCC inside the Milan criteria. Patients were treated according to the BCLC algorithm and prospectively followed by imaging every 3 months; 76 patients (43%) were listed for transplantation according to AISF/CNT guidelines. Transplanted patients were censored at the time of transplantation. Results. Median follow-up was 16 months. HCC progressed beyond T2 stage in 75 cases; 8 patients died while in T2 stage and 68 were transplanted. To verify the ability of the UNOS policy to predict HCC progression rate (PR), we compared the expected PR according to the UNOS policy with the observed PR for the respective population at risk. The current policy resulted in a large overestimation of PR in T2 patients. Two sensitivity analyses were conducted to identify risk factor (RF) for progression using the log-rank method: in the first one, transplanted patients were considered as disease progression; in the second one, only non-transplanted patients were analysed. RF significant in any analysis was considered for multivariable analysis. RF with the strongest relationship to progression included tumor persistence after local therapy or recurrence inside Milan criteria (HR 2.52–3.16; p < 0.0001). Using strongest RF for progression and the patient's natural MELD, an adjusted model applicable to organ allocation was generated, which decreased the discrepancy between expected and observed PR. Conclusions. Tumor persistence/recurrence inside Milan criteria after treatment strongly predicted the risk of tumor progression beyond Milan criteria. The current MELD exception largely overestimates progression in T2 patients treated according to BCLC. An adjusted model that begins with the patient's natural MELD, and stratifies progressive risk according to the response to local treatment, better captures the PR of T2 HCC
De Giorgio, M., Vezzoli, S., Cohen, E., Armellini, E., Lucà, M., Verga, G., et al. (2009). HCC persistence or recurrence after bridging therapy helps predict transplant list dropout and generate a more equitable exception policy. DIGESTIVE AND LIVER DISEASE, 41(3), A10-A11 [10.1016/j.dld.2008.12.025].
HCC persistence or recurrence after bridging therapy helps predict transplant list dropout and generate a more equitable exception policy
Valsecchi, MG;Antolini, L;Colledan, M;Fagiuoli, S;Strazzabosco, M
2009
Abstract
Background and aim. Earlier diagnosis and more effective treatments are improving the survival of patients with HCC. Moreover, the natural history of HCC patients is different from that patients with non-neoplastic indications for liver transplantation. This issue becomes critical to provide an equitable allocation policy to patients listed for transplantation. UNOS adopted a MELD-based policy that assigns the native MELD for patients with stage I HCC and 22 points for patients stage II HCC listed for Liver Transplant (LT), with an additional three points added every 3 months of waiting time in list for the latter. Organs are then assigned on the basis of the MELD score, irrespective of the indication. In countries outside the UNOS area, allocation for HCC patients still misses uniformity. Aim. The aim of the study was to generate an updated prognostic model for HCC applicable to organ allocation. Material and methods. We analysed disease progression (death or progression of HCC beyond T2 stage) in a cohort of 177 consecutive patients that presented with HCC inside the Milan criteria. Patients were treated according to the BCLC algorithm and prospectively followed by imaging every 3 months; 76 patients (43%) were listed for transplantation according to AISF/CNT guidelines. Transplanted patients were censored at the time of transplantation. Results. Median follow-up was 16 months. HCC progressed beyond T2 stage in 75 cases; 8 patients died while in T2 stage and 68 were transplanted. To verify the ability of the UNOS policy to predict HCC progression rate (PR), we compared the expected PR according to the UNOS policy with the observed PR for the respective population at risk. The current policy resulted in a large overestimation of PR in T2 patients. Two sensitivity analyses were conducted to identify risk factor (RF) for progression using the log-rank method: in the first one, transplanted patients were considered as disease progression; in the second one, only non-transplanted patients were analysed. RF significant in any analysis was considered for multivariable analysis. RF with the strongest relationship to progression included tumor persistence after local therapy or recurrence inside Milan criteria (HR 2.52–3.16; p < 0.0001). Using strongest RF for progression and the patient's natural MELD, an adjusted model applicable to organ allocation was generated, which decreased the discrepancy between expected and observed PR. Conclusions. Tumor persistence/recurrence inside Milan criteria after treatment strongly predicted the risk of tumor progression beyond Milan criteria. The current MELD exception largely overestimates progression in T2 patients treated according to BCLC. An adjusted model that begins with the patient's natural MELD, and stratifies progressive risk according to the response to local treatment, better captures the PR of T2 HCC
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