# A pre-emptive risk model for acute rejection in liver transplantation: an immunopharmacologic biomarker panel combining CD4+ T-cell profiling and tacrolimus exposure

## TL;DR

This study creates a model to predict liver transplant rejection using immune cell levels and drug exposure, offering early warnings before damage occurs.

## Contribution

A novel immunopharmacologic model combining CD4+ T-cell profiling and tacrolimus levels for pre-emptive acute rejection risk assessment.

## Key findings

- The model achieved good discrimination with an AUC of 0.774 and a median 8-day warning window before injury.
- It outperformed monitoring tacrolimus or CD4+ T cells alone in predicting acute rejection.
- The model captures the interaction between immune activation and subtherapeutic immunosuppression.

## Abstract

Acute cellular rejection (ACR) is a T cell-driven event in liver transplantation. Current monitoring relies on detecting graft injury, lacking tools for pre-emptive risk assessment based on the patient’s real-time immune status.

We developed an immunopharmacologic risk model in a retrospective cohort of 98 liver transplant recipients (18 with biopsy-proven ACR). The model integrated peripheral CD4+ T-cell percentage (flow cytometry) and tacrolimus trough level. Firth-penalized logistic regression was used for model development, with internal validation via bootstrapping.

The parsimonious model, comprising only CD4+ T-cell percentage and tacrolimus level, demonstrated good discrimination (AUC 0.774, 95% CI 0.674-0.874) and calibration. Critically, lead-time analysis revealed the model provided a median warning window of 8 days (IQR: 3.5 days) prior to biochemical injury onset. It offered significant incremental value over monitoring tacrolimus alone (AUC 0.774 vs. 0.694, ΔAUC=0.080, p=0.007) or CD4+ T cells alone (AUC 0.774 vs. 0.733, ΔAUC=0.041, p=0.014).

We identify and validate a novel, clinically actionable immunopharmacologic biomarker panel for ACR. This model enables pre-emptive risk stratification by capturing the high-risk confluence of immune activation and subtherapeutic immunosuppression, paving the way for personalized immunotherapy in transplant recipients.