The Authors' Reply: Tacrolimus Trough Concentrations After Liver Transplantation: Back to the Future

The authors thank Dr Rodríguez-Perálvarez for initiating this valuable discussion on our article. We strongly agree with the authors that minimizations strategies are required to reduce the side effects associated with calcineurin inhibitors (CNI) exposure, and our results should not be interpreted as an encouragement to increase immunosuppression (IS) during the early posttransplant period. We deliberately referred to the first 15 days of CNI exposure (not minimization) as a poor tool in predicting long-term adverse events, at least in our population. We concluded that “the effect of early CNI exposure is possibly limited to early posttransplant outcomes and that other factors developing over time have possibly a greater impact on long-term events.”1 Indeed, and as an example, we as well as others have clearly shown the impact of additional variables, such as Framingham score or cumulative doses of CNI overtime on long-term outcomes.2,3 We understand the concerns of the authors regarding the subgroup analysis of patients immunosuppressed with tacrolimus (TAC); indeed, these types of analyses should always be interpreted with caution. We therefore additionally conducted a Bayesian model to further estimate the distribution of IS levels considering a confidence interval (CI) between 0.8 and 1.4 as clinically relevant. The area under the curve obtained of 0.81 highlights that, in our cohort, the first 15 days of CNI levels had no impact on long-term survival or graft loss with an 80% probability. Though we also agree with the authors that mean TAC levels may better reflect peaks of TAC, we also believe that predicting the lifetime events of a transplant patient by 1 TAC peak during the first 15 days is likely an overestimation of the potential toxicities of CNI. Furthermore, it is known that CNI levels during the first 15 days post–liver transplantation are extremely variable as shown in Figure S1 (SDC, https://links.lww.com/TP/B854) of the article.1 In that sense, using median levels of CNI, probably more consistent with their real exposition, is a better approach for understanding the real impact of early IS. Moreover, similar results were achieved regardless of the statistical approach used (mean versus median levels, sensitivity analysis). As highlighted by Rodríguez-Perálvarez, there may be competing risks for particular outcomes such as cardiovascular events; thus, we additionally performed a competing risk analysis for cardiovascular events taking into consideration mortality without finding any association between early IS exposition and cardiovascular events (hazard ratio = 1.229, CI 95% = 0.630-2.398, P = 0.489; hazard ratio = 0.944, CI 95% = 0.478-1.864, P = 0.867, comparing high versus low and optimal IS, respectively, see Figure 1).Figure 1.: Competing risk regression for cardiovascular disease: the cumulative incidence of cardiovascular events comparing high vs low and optimal immunosuppression was not significantly different taking into consideration mortality as competing risk factor.Finally, we would like to highlight the current difficulties in defining optimal IS or minimization strategies given the lack of adequate tools that provide accurate measurement of the net status of IS in a given patient.4,5 Such tools have long been considered the holy grail in immunology and organ transplantation.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.