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      Performance of gene-expression profiling test score variability to predict future clinical events in heart transplant recipients

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          Abstract

          Background

          A single non-invasive gene expression profiling (GEP) test (AlloMap®) is often used to discriminate if a heart transplant recipient is at a low risk of acute cellular rejection at time of testing. In a randomized trial, use of the test (a GEP score from 0–40) has been shown to be non-inferior to a routine endomyocardial biopsy for surveillance after heart transplantation in selected low-risk patients with respect to clinical outcomes. Recently, it was suggested that the within-patient variability of consecutive GEP scores may be used to independently predict future clinical events; however, future studies were recommended. Here we performed an analysis of an independent patient population to determine the prognostic utility of within-patient variability of GEP scores in predicting future clinical events.

          Methods

          We defined the GEP score variability as the standard deviation of four GEP scores collected ≥315 days post-transplantation. Of the 737 patients from the Cardiac Allograft Rejection Gene Expression Observational (CARGO) II trial, 36 were assigned to the composite event group (death, re-transplantation or graft failure ≥315 days post-transplantation and within 3 years of the final GEP test) and 55 were assigned to the control group (non-event patients). In this case-controlled study, the performance of GEP score variability to predict future events was evaluated by the area under the receiver operator characteristics curve (AUC ROC). The negative predictive values (NPV) and positive predictive values (PPV) including 95 % confidence intervals (CI) of GEP score variability were calculated.

          Results

          The estimated prevalence of events was 17 %. Events occurred at a median of 391 (inter-quartile range 376) days after the final GEP test. The GEP variability AUC ROC for the prediction of a composite event was 0.72 (95 % CI 0.6-0.8). The NPV for GEP score variability of 0.6 was 97 % (95 % CI 91.4-100.0); the PPV for GEP score variability of 1.5 was 35.4 % (95 % CI 13.5-75.8).

          Conclusion

          In heart transplant recipients, a GEP score variability may be used to predict the probability that a composite event will occur within 3 years after the last GEP score.

          Trial registration

          Clinicaltrials.gov identifier NCT00761787

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12872-015-0106-1) contains supplementary material, which is available to authorized users.

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          Most cited references14

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          Gene-expression profiling for rejection surveillance after cardiac transplantation.

          Endomyocardial biopsy is the standard method of monitoring for rejection in recipients of a cardiac transplant. However, this procedure is uncomfortable, and there are risks associated with it. Gene-expression profiling of peripheral-blood specimens has been shown to correlate with the results of an endomyocardial biopsy. We randomly assigned 602 patients who had undergone cardiac transplantation 6 months to 5 years previously to be monitored for rejection with the use of gene-expression profiling or with the use of routine endomyocardial biopsies, in addition to clinical and echocardiographic assessment of graft function. We performed a noninferiority comparison of the two approaches with respect to the composite primary outcome of rejection with hemodynamic compromise, graft dysfunction due to other causes, death, or retransplantation. During a median follow-up period of 19 months, patients who were monitored with gene-expression profiling and those who underwent routine biopsies had similar 2-year cumulative rates of the composite primary outcome (14.5% and 15.3%, respectively; hazard ratio with gene-expression profiling, 1.04; 95% confidence interval, 0.67 to 1.68). The 2-year rates of death from any cause were also similar in the two groups (6.3% and 5.5%, respectively; P=0.82). Patients who were monitored with the use of gene-expression profiling underwent fewer biopsies per person-year of follow-up than did patients who were monitored with the use of endomyocardial biopsies (0.5 vs. 3.0, P<0.001). Among selected patients who had received a cardiac transplant more than 6 months previously and who were at a low risk for rejection, a strategy of monitoring for rejection that involved gene-expression profiling, as compared with routine biopsies, was not associated with an increased risk of serious adverse outcomes and resulted in the performance of significantly fewer biopsies. (ClinicalTrials.gov number, NCT00351559.) 2010 Massachusetts Medical Society
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            Noninvasive discrimination of rejection in cardiac allograft recipients using gene expression profiling.

            Rejection diagnosis by endomyocardial biopsy (EMB) is invasive, expensive and variable. We investigated gene expression profiling of peripheral blood mononuclear cells (PBMC) to discriminate ISHLT grade 0 rejection (quiescence) from moderate/severe rejection (ISHLT > or = 3A). Patients were followed prospectively with blood sampling at post-transplant visits. Biopsies were graded by ISHLT criteria locally and by three independent pathologists blinded to clinical data. Known alloimmune pathways and leukocyte microarrays identified 252 candidate genes for which real-time PCR assays were developed. An 11 gene real-time PCR test was derived from a training set (n = 145 samples, 107 patients) using linear discriminant analysis (LDA), converted into a score (0-40), and validated prospectively in an independent set (n = 63 samples, 63 patients). The test distinguished biopsy-defined moderate/severe rejection from quiescence (p = 0.0018) in the validation set, and had agreement of 84% (95% CI 66% C94%) with grade ISHLT > or = 3A rejection. Patients >1 year post-transplant with scores below 30 (approximately 68% of the study population) are very unlikely to have grade > or = 3A rejection (NPV = 99.6%). Gene expression testing can detect absence of moderate/severe rejection, thus avoiding biopsy in certain clinical settings. Additional clinical experience is needed to establish the role of molecular testing for clinical event prediction and immunosuppression management.
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              The use of unequal randomisation ratios in clinical trials: a review.

              To examine reasons given for the use of unequal randomisation in randomised controlled trials (RCTs). Setting of the trial; intervention being tested; randomisation ratio; sample size calculation; reason given for randomisation. Review of trials using unequal randomisation. DATABASES AND SOURCES: Cochrane library, Medline, Pub Med and Science Citation Index. A total of 65 trials were identified; 56 were two-armed trials and nine trials had more than two arms. Of the two-arm trials, 50 trials recruited patients in favour of the experimental group. Various reasons for the use of unequal randomisation were given. Six studies stated that they used unequal randomisation to reduce the cost of the trial, with one screening trial limited by the availability of the intervention. Other reasons for using unequal allocation were: avoiding loss of power from drop-out or cross-over, ethics and the gaining of additional information on the treatment. Thirty seven trials papers (57%) did not state why they had used unequal randomisation and only 14 trials (22%) appeared to have taken the unequal randomisation into account in their sample size calculation. Although unequal randomisation offers a number of advantages to trials the method is rarely used and is especially under-utilised to reduce trial costs. Unequal randomisation should be considered more in trial design especially where there are large differences between treatment costs.
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                Author and article information

                Contributors
                marisa.crespo.leiro@sergas.es
                stypmann@ukmuenster.de
                uschulz@hdz-nrw.de
                andreas.zuckermann@meduniwien.ac.at
                Paul.Mohacsi@insel.ch
                bara.christoph@mh-hannover.de
                Heather.Ross@uhn.ca
                Jayan.Parameshwar@papworth.nhs.uk
                zaklimed@onet.pl
                roberto.fiocchi@gmail.com
                Daniel.Hoefer@i-med.ac.at
                MDeng@mednet.ucla.edu
                pascal.leprince@psl.aphp.fr
                dhiller@caredx.com
                leubank@caredx.com
                edeljkich@caredx.com
                Jyee@caredx.com
                +32 16 3 44251 , johan.vanhaecke@uzleuven.be
                Journal
                BMC Cardiovasc Disord
                BMC Cardiovasc Disord
                BMC Cardiovascular Disorders
                BioMed Central (London )
                1471-2261
                9 October 2015
                9 October 2015
                2015
                : 15
                : 120
                Affiliations
                [ ]Instituto de Investigación Biomédica de A Coruña (INIBIC), Complexo Hospitalario Universitario de A Coruña (CHUAC), SERGAS. Universidade da Coruña (UDC), Coruña, Spain
                [ ]University Hospital Muenster, Muenster, Germany
                [ ]Ruhr University of Bochum, Bad Oeynhausen, Germany
                [ ]Medical University of Vienna, Vienna, Austria
                [ ]University Hospital Bern, Bern, Switzerland
                [ ]Hannover Medical School, Hannover, Germany
                [ ]Toronto General Hospital, Toronto, Canada
                [ ]Papworth Hospital, Papworth Everard, Cambridge, UK
                [ ]Silesian Center for Heart Disease, Zabrze, Poland
                [ ]Ospedali Riuniti di Bergamo, Bergamo, Italy
                [ ]Innsbruck Medical University, Innsbruck, Austria
                [ ]David Geffen School of Medicine, University of California, Los Angeles, USA
                [ ]Groupe Hospitalier Pitié-Salpêtrière, Paris, France
                [ ]CareDx, Brisbane, USA
                [ ]University Hospital of Leuven, Leuven, Belgium
                [ ]Department of Cardiology, Herestraat 49, 3000 Leuven, Belgium
                Article
                106
                10.1186/s12872-015-0106-1
                4600291
                d94e03d2-1cd2-4ccb-bfea-844d60449850
                © Crespo-Leiro et al. 2015

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 2 July 2015
                : 21 September 2015
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2015

                Cardiovascular Medicine
                heart transplant,gene expression profiling,allomap,surveillance of cardiac recipients,acute cellular rejection,allomap score variability,gene expression profiling score

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