External Validation of a Pre-Transplant Biomarker Model (REVERSE) Predictive of Renal Recovery after Liver Transplantation.
Göran Klintmalm M.D.
Levitsky, J., S. K. Asrani, M. Abecassis, R. Ruiz, L. W. Jennings and G. Klintmalm (2019). “External Validation of a Pre-Transplant Biomarker Model (REVERSE) Predictive of Renal Recovery after Liver Transplantation.” Hepatology Apr 19. [Epub ahead of print].
In patients with end stage liver disease, the ability to predict recovery of renal function following liver transplantation alone (LTA) remains elusive. However, several important clinical decisions depend on whether renal dysfunction is recoverable after LTA. We used a cohort of patients undergoing LT to independently validate a pre-LT model predictive of post-LTA renal recovery (REVERSE: high osteopontin (OPN) and tissue inhibitor of metalloproteinases-1 (TIMP-1) levels, age <57, no diabetes). Serum samples pre-LT and 4-12 weeks post-LTA (n=117) were analyzed for kidney injury proteins from 3 groups of recipients: (1) estimated GFR (eGFR)<30ml/min/1.73m(2) prior to LTA and <30 ml/min/1.73m(2) after LTA (irreversible acute kidney injury = iAKI), (2) eGFR<30ml/min/1.73m(2) prior to LTA and >50 ml/min/1.73m(2) after LTA (reversible AKI = rAKI) (3) eGFR>50 ml/min/1.73m(2) prior to LTA and >50 ml/min/1.73m(2) after LTA (no AKI = nAKI). In patients with elevated pre-LTA serum levels of OPN and TIMP-1, recovery of renal function correlated with decreases in the level of both proteins. At four weeks post-LT (n=77 subset), the largest decline in OPN and TIMP-1 was seen in the rAKI group. Validation of the REVERSE model in this independent dataset had high area under the curve (AUC) (0.78) in predicting full post-LT renal recovery (sensitivity 0.86, specificity 0.6, PPV 0.81, NPV 0.69). Our eGFR findings were confirmed using measured GFR (mGFR). CONCLUSION: The REVERSE model, derived from an initial training set combining novel plasma biomarkers and clinical characteristics, demonstrated excellent external validation performance characteristics in an independent patient cohort using serum samples. Among patients with kidney injury pre-LTA, the predictive ability of this simple tool may prove beneficial in clinical decision-making both prior to and following transplantation.