Background and Aims: Model for End-stage Liver Disease (MELD) and MELDNa are used worldwide to guide graft allocation in liver transplantation (LT). Evidence exists that females are penalized in the present allocation systems. Recently, new sex-adjusted scores have been proposed with improved performance respect to MELD and MELDNa. GEMA-Na, MELD 3.0, and sex-adjusted MELDNa were developed to improve the 90-day dropout prediction from the list. The present study aimed at evaluating the accuracy and calibration of these scores in an Italian setting. Methods: The primary outcome of the present study was the dropout from the list up to 90 days because of death or clinical deterioration. We retrospectively analysed data from 855 adults enlisted for liver transplantation in the Lazio region (Italy) (2012–2018). Ninety-day prediction of GEMA-Na, MELD 3.0 and sex-adjusted MELDNa with respect to MELD and MELDNa was analysed. Brier score and Brier Skill score were used for accuracy, and the Greenwood-Nam-D'Agostino test was used to evaluate the calibration of the models. Results: GEMA-Na (concordance = .82, 95% CI = .75–.89), MELD 3.0 (concordance = .81, 95% CI = .74–.87) and sex-adjusted MELDNa (concordance = .81, 95% CI = .74–.88) showed the best 90-day dropout prediction. GEMA-Na showed a higher increase in accuracy with respect to MELD (p = .03). No superiority was shown with respect to MELDNa. All the tested scores showed a good calibration of the models. Using GEMA-Na instead of MELD would potentially save one in nine dropouts and could save one dropout per 285 patients listed.
Superiority of the new sex-adjusted models to remove the female disadvantage restoring equity in liver transplant allocation / Marrone, Giuseppe; Giannelli, Valerio; Agnes, Salvatore; Avolio, Alfonso Wolfango; Baiocchi, Leonardo; Berardi, Giammauro; Ettorre, Giuseppe Maria; Ferri, Flaminia; Corradini, Stefano Ginanni; Grieco, Antonio; Guglielmo, Nicola; Lenci, Ilaria; Lionetti, Raffaella; Mennini, Gianluca; Milana, Martina; Rossi, Massimo; Spoletini, Gabriele; Tisone, Giuseppe; Manzia, Tommaso Maria; Lai, Quirino. - In: LIVER INTERNATIONAL. - ISSN 1478-3223. - 44:1(2024), pp. 103-112. [10.1111/liv.15735]
Superiority of the new sex-adjusted models to remove the female disadvantage restoring equity in liver transplant allocation
Giannelli, Valerio;Berardi, Giammauro;Ferri, Flaminia;Corradini, Stefano Ginanni;Grieco, Antonio;Guglielmo, Nicola;Mennini, Gianluca;Milana, Martina;Rossi, Massimo;Spoletini, Gabriele
;Lai, Quirino
2024
Abstract
Background and Aims: Model for End-stage Liver Disease (MELD) and MELDNa are used worldwide to guide graft allocation in liver transplantation (LT). Evidence exists that females are penalized in the present allocation systems. Recently, new sex-adjusted scores have been proposed with improved performance respect to MELD and MELDNa. GEMA-Na, MELD 3.0, and sex-adjusted MELDNa were developed to improve the 90-day dropout prediction from the list. The present study aimed at evaluating the accuracy and calibration of these scores in an Italian setting. Methods: The primary outcome of the present study was the dropout from the list up to 90 days because of death or clinical deterioration. We retrospectively analysed data from 855 adults enlisted for liver transplantation in the Lazio region (Italy) (2012–2018). Ninety-day prediction of GEMA-Na, MELD 3.0 and sex-adjusted MELDNa with respect to MELD and MELDNa was analysed. Brier score and Brier Skill score were used for accuracy, and the Greenwood-Nam-D'Agostino test was used to evaluate the calibration of the models. Results: GEMA-Na (concordance = .82, 95% CI = .75–.89), MELD 3.0 (concordance = .81, 95% CI = .74–.87) and sex-adjusted MELDNa (concordance = .81, 95% CI = .74–.88) showed the best 90-day dropout prediction. GEMA-Na showed a higher increase in accuracy with respect to MELD (p = .03). No superiority was shown with respect to MELDNa. All the tested scores showed a good calibration of the models. Using GEMA-Na instead of MELD would potentially save one in nine dropouts and could save one dropout per 285 patients listed.File | Dimensione | Formato | |
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