Cumulative exposure to tacrolimus and incidence of cancer after liver transplantation.

Cancer is the leading cause of death after liver transplantation (LT). This multicenter case-control nested study aimed to evaluate the effect of maintenance immunosuppression on post-LT malignancy. The eligible cohort included 2495 LT patients who received tacrolimus-based immunosuppression. After 13 922 person/years follow-up, 425 patients (19.7%) developed malignancy (cases) and were matched with 425 controls by propensity score based on age, gender, smoking habit, etiology of liver disease, and hepatocellular carcinoma (HCC) before LT. The independent predictors of post-LT malignancy were older age (HR = 1.06 [95% CI 1.05-1.07]; p < .001), male sex (HR = 1.50 [95% CI 1.14-1.99]), smoking habit (HR = 1.96 [95% CI 1.42-2.66]), and alcoholic liver disease (HR = 1.53 [95% CI 1.19-1.97]). In selected cases and controls (n = 850), the immunosuppression protocol was similar (p = .51). An increased cumulative exposure to tacrolimus (CET), calculated by the area under curve of trough concentrations, was the only immunosuppression-related predictor of post-LT malignancy after controlling for clinical features and baseline HCC (CET at 3 months p = .001 and CET at 12 months p = .004). This effect was consistent for de novo malignancy (after excluding HCC recurrence) and for internal neoplasms (after excluding non-melanoma skin cancer). Therefore, tacrolimus minimization, as monitored by CET, is the key to modulate immunosuppression in order to prevent cancer after LT.

COVID-19 contagion forecasting framework based on curve decomposition and evolutionary artificial neural networks: A case study in Andalusia, Spain.

Many types of research have been carried out with the aim of combating the COVID-19 pandemic since the first outbreak was detected in Wuhan, China. Anticipating the evolution of an outbreak helps to devise suitable economic, social and health care strategies to mitigate the effects of the virus. For this reason, predicting the SARS-CoV-2 transmission rate has become one of the most important and challenging problems of the past months. In this paper, we apply a two-stage mid and long-term forecasting framework to the epidemic situation in eight districts of Andalusia, Spain. First, an analytical procedure is performed iteratively to fit polynomial curves to the cumulative curve of contagions. Then, the extracted information is used for estimating the parameters and structure of an evolutionary artificial neural network with hybrid architectures (i.e., with different basis functions for the hidden nodes) while considering single and simultaneous time horizon estimations. The results obtained demonstrate that including polynomial information extracted during the training stage significantly improves the mid- and long-term estimations in seven of the eight considered districts. The increase in average accuracy (for the joint mid- and long-term horizon forecasts) is 37.61% and 35.53% when considering the single and simultaneous forecast approaches, respectively.

GEMA-Na and MELD 3.0 severity scores to address sex disparities for accessing liver transplantation: a nationwide retrospective cohort study.

Background: The Gender-Equity Model for liver Allocation corrected by serum sodium (GEMA-Na) and the Model for End-stage Liver Disease 3.0 (MELD 3.0) could amend sex disparities for accessing liver transplantation (LT). We aimed to assess these inequities in Spain and to compare the performance of GEMA-Na and MELD 3.0. Methods: Nationwide cohort study including adult patients listed for a first elective LT (January 2016-December 2021). The primary outcome was mortality or delisting for sickness within the first 90 days. Independent predictors of the primary outcome were evaluated using multivariate Cox's regression with adjusted relative risks (RR) and 95% confidence intervals (95% CI). The discrimination of GEMA-Na and MELD 3.0was assessed using Harrell c-statistics (Hc). Findings: The study included 6071 patients (4697 men and 1374 women). Mortality or delisting for clinical deterioration occurred in 286 patients at 90 days (4.7%). Women had reduced access to LT (83.7% vs. 85.9%; p = 0.037) and increased risk of mortality or delisting for sickness at 90 days (adjusted RR = 1.57 [95% CI 1.09-2.28]; p = 0.017). Female sex remained as an independent risk factor when using MELD or MELD-Na but lost its significance in the presence of GEMA-Na or MELD 3.0. Among patients included for reasons other than tumours (n = 3606; 59.4%), GEMA-Na had Hc = 0.753 (95% CI 0.715-0.792), which was higher than MELD 3.0 (Hc = 0.726 [95% CI 0.686-0.767; p = 0.001), showing both models adequate calibration. Interpretation: GEMA-Na and MELD 3.0 might correct sex disparities for accessing LT, but GEMA-Na provides more accurate predictions of waiting list outcomes and could be considered the standard of care for waiting list prioritization. Funding: Instituto de Salud Carlos III, Agencia Estatal de Investigación (Spain), and European Union.

Development and validation of the Gender-Equity Model for Liver Allocation (GEMA) to prioritise candidates for liver transplantation: a cohort study.

BACKGROUND: The Model for End-stage Liver Disease (MELD) and its sodium-corrected variant (MELD-Na) have created gender disparities in accessing liver transplantation. We aimed to derive and validate the Gender-Equity Model for liver Allocation (GEMA) and its sodium-corrected variant (GEMA-Na) to amend such inequities. METHODS: In this cohort study, the GEMA models were derived by replacing creatinine with the Royal Free Hospital glomerular filtration rate (RFH-GFR) within the MELD and MELD-Na formulas, with re-fitting and re-weighting of each component. The new models were trained and internally validated in adults listed for liver transplantation in the UK (2010-20; UK Transplant Registry) using generalised additive multivariable Cox regression, and externally validated in an Australian cohort (1998-2020; Royal Prince Alfred Hospital [Australian National Liver Transplant Unit] and Austin Hospital [Victorian Liver Transplant Unit]). The study comprised 9320 patients: 5762 patients for model training, 1920 patients for internal validation, and 1638 patients for external validation. The primary outcome was mortality or delisting due to clinical deterioration within the first 90 days from listing. Discrimination was assessed by Harrell's concordance statistic. FINDINGS: 449 (5·8%) of 7682 patients in the UK cohort and 87 (5·3%) of 1638 patients in the Australian cohort died or were delisted because of clinical deterioration within 90 days. GEMA showed improved discrimination in predicting mortality or delisting due to clinical deterioration within the first 90 days after waiting list inclusion compared with MELD (Harrell's concordance statistic 0·752 [95% CI 0·700-0·804] vs 0·712 [0·656-0·769]; p=0·001 in the internal validation group and 0·761 [0·703-0·819] vs 0·739 [0·682-0·796]; p=0·036 in the external validation group), and GEMA-Na showed improved discrimination compared with MELD-Na (0·766 [0·715-0·818] vs 0·742 [0·686-0·797]; p=0·0058 in the internal validation group and 0·774 [0·720-0·827] vs 0·745 [0·690-0·800]; p=0·014 in the external validation group). The discrimination capacity of GEMA-Na was higher in women than in the overall population, both in the internal (0·802 [0·716-0·888]) and external validation cohorts (0·796 [0·698-0·895]). In the pooled validation cohorts, GEMA resulted in a score change of at least 2 points compared with MELD in 1878 (52·8%) of 3558 patients (25·0% upgraded and 27·8% downgraded). GEMA-Na resulted in a score change of at least 2 points compared with MELD-Na in 1836 (51·6%) of 3558 patients (32·3% upgraded and 19·3% downgraded). In the whole cohort, 3725 patients received a transplant within 90 days of being listed. Of these patients, 586 (15·7%) would have been differently prioritised by GEMA compared with MELD; 468 (12·6%) patients would have been differently prioritised by GEMA-Na compared with MELD-Na. One in 15 deaths could potentially be avoided by using GEMA instead of MELD and one in 21 deaths could potentially be avoided by using GEMA-Na instead of MELD-Na. INTERPRETATION: GEMA and GEMA-Na showed improved discrimination and a significant re-classification benefit compared with existing scores, with consistent results in an external validation cohort. Their implementation could save a clinically meaningful number of lives, particularly among women, and could amend current gender inequities in accessing liver transplantation. FUNDING: Junta de Andalucía and EDRF.