@article { ISI:000314445800011,
	title = {Predicting acute cardiac rejection from donor heart and pre-transplant recipient blood gene expression},
	journal = {JOURNAL OF HEART AND LUNG TRANSPLANTATION},
	volume = {32},
	number = {2},
	year = {2013},
	month = {FEB},
	pages = {259-265},
	publisher = {ELSEVIER SCIENCE INC},
	type = {Article},
	address = {360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA},
	abstract = {BACKGROUND: Acute rejection in cardiac transplant patients remains a contributory factor to limited survival of implanted hearts. Currently, there are no biomarkers in clinical use that can predict, at the time of transplantation, the likelihood of post-transplant acute cellular rejection. Such a development would be of great value in personalizing immunosuppressive treatment. METHODS: Recipient age, donor age, cold ischemic time, warm ischemic time, panel-reactive antibody, gender mismatch, blood type mismatch and human leukocyte antigens (HLA-A, -B and -DR) mismatch between recipients and donors were tested in 53 heart transplant patients for their power to predict post-transplant acute cellular rejection. Donor transplant biopsy and recipient pre-transplant blood were also examined for the presence of genomic biomarkers in 7 rejection and 11 non-rejection patients, using non-targeted data mining techniques. RESULTS: The biomarker based on the 8 clinical variables had an area under the receiver operating characteristic curve (AUC) of 0.53. The pre-transplant recipient blood gene-based panel did not yield better performance, but the donor heart tissue gene-based panel had an AUC = 0.78. A combination of 25 probe sets from the transplant donor biopsy and 18 probe sets from the pre-transplant recipient whole blood had an AUC = 0.90. Biologic pathways implicated include VEGF- and EGFR-signaling, and MAPK. CONCLUSIONS: Based on this study, the best predictive biomarker panel contains genes from recipient whole blood and donor myocardial tissue. This panel provides clinically relevant prediction power and, if validated, may personalize immunosuppressive treatment and rejection monitoring. I Heart Lung Transplant 2013;32:259-265 (C) 2013 International Society for Heart and Lung Transplantation. All rights reserved.},
	keywords = {acute rejection, biomarker, cardiac transplant, prediction},
	issn = {1053-2498},
	doi = {10.1016/j.healun.2012.11.008},
	author = {Hollander, Zsuzsanna and Chen, Virginia and Sidhu, Keerat and Lin, David and Ng, Raymond T. and Balshaw, Robert and Cohen-Freue, Gabriela V. and Ignaszewski, Andrew and Imai, Carol and Kaan, Annemarie and Tebbutt, Scott J. and Wilson-McManus, Janet E. and McMaster, Robert W. and Keown, Paul. A. and McManus, Bruce M. and NCE CECR PROOF Ctr Excellence}
}
@article { ISI:000186756300013,
	title = {Local linear extrapolation},
	journal = {JOURNAL OF NONPARAMETRIC STATISTICS},
	volume = {15},
	number = {4-5},
	year = {2003},
	month = {AUG-OCT},
	pages = {565-578},
	publisher = {TAYLOR \& FRANCIS LTD},
	type = {Article},
	address = {4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND},
	abstract = {A local linear estimator is proposed for extrapolating beyond the range of independent regression data. The asymptotic bias and variance of the local linear extrapolant are presented and used to calculate the asymptotic mean squared error. Three procedures are considered for choice of the bandwidth: a plug-in procedure. a forward cross-validation procedure and a procedure that combines the two. All of these are, in some sense. based on minimizing the asymptotic mean squared error. A simulation study shows that the forward cross-validation procedure outperforms the other two procedures both in terms of choosing a bandwidth and in terms of accurate extrapolation. The techniques are applied to two data sets.},
	keywords = {bandwidth selection, local linear estimation, prediction},
	issn = {1048-5252},
	doi = {10.1080/10485250310001605432},
	author = {Li, XC and Heckman, NE}
}
