Utility of gene expression profiling score variability to predict clinical events in heart transplant recipients.

Background: Gene expression profiling test scores have primarily been used to identify heart transplant recipients who have a low probability of rejection at the time of surveillance testing. We hypothesized that the variability of gene expression profiling test scores within a patient may predict risk of future events of allograft dysfunction or death.

Method: Patients from the IMAGE study with rejection surveillance gene expression profiling tests performed at 1- to 6-month intervals were selected for this cohort study. Gene expression profiling score variability was defined as the standard deviation of an individual's cumulative test scores. Gene expression profiling ordinal score (range, 0-39), threshold score (binary value=1 if ordinal score ≥ 34), and score variability were studied in multivariate Cox regression models to predict future clinical events.

Results: Race, age at time of transplantation, and time posttransplantation were significantly associated with future events in the univariate analysis. In the multivariate analyses, gene expression profiling score variability, but not ordinal scores or scores over threshold, was independently associated with future clinical events. The regression coefficient P values were <0.001, 0.46, and 0.773, for gene expression profiling variability, ordinal, and threshold scores, respectively. The hazard ratio for a 1 unit increase in variability was 1.76 (95% CI, 1.4-2.3).

Discussion: The variability of a heart recipient's gene expression profiling test scores over time may provide prognostic utility. This information is independent of the probability of acute cellular rejection at the time of testing that is rendered from a single ordinal gene-expression profiling test score.