Utility of gene expression profiling score variability to predict clinical events in heart transplant recipients
Autor: | J. Yee, Hannah A. Valantine, Abdallah G. Kfoury, Barbara Elashoff, Randall C. Starling, Mario C. Deng, William Cotts, D. Hiller, Gregory A. Ewald, Roberta C. Bogaev, Allen S. Anderson, Khurram Shahzad, David A. Baran, Jeffrey J. Teuteberg, Thomas P. Cappola, M.X. Pham, Andrew Kao |
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Rok vydání: | 2014 |
Předmět: |
Oncology
Adult Graft Rejection Male medicine.medical_specialty Pathology Multivariate analysis Time Factors Biopsy Transplant Predictive Value of Tests Clinical and Translational Research Internal medicine medicine Molecular diagnostics Humans Genetic Predisposition to Disease Genetic Testing Aged Proportional Hazards Models Transplantation Univariate analysis business.industry Proportional hazards model Gene Expression Profiling Tests Hazard ratio Middle Aged Prognosis United States Gene expression profiling Treatment Outcome Risk factors Predictive value of tests Test score Multivariate Analysis Heart Transplantation Female business |
Zdroj: | Transplantation |
ISSN: | 1534-6080 |
Popis: | 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 Supplemental digital content is available in the article. |
Databáze: | OpenAIRE |
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