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Activity Number:
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549
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Type:
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Contributed
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Date/Time:
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Thursday, August 2, 2007 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Teaching Statistics in the Health Sciences
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| Abstract - #309369 |
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Title:
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Determining Graft Survival After Clinical Islet Transplantation: Superior Performance of Extended Cox-Based Models
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Author(s):
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Abdul Salam*+ and Peter Senior and Abdulkadir Hussein and Patricia M. Campbell and Kathleen LaBranche and James A.M. Shapiro
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Companies:
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University of Alberta and University of Alberta and University of Windsor and University of Alberta and University of Alberta and University of Alberta
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Address:
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8215 112 Street, Edmonton, AB, t6g2c8, Canada
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Keywords:
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survival analysis ; extended Cox-based models ; recurrent events ; islet transplantation ; panel reactive antibodies
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Abstract:
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Two or more islet transplants are often required to achieve insulin independence in patients with type 1 diabetes. Conventional outcome measures in clinical islet transplantation (CIT) are based on graft survival either from time of first or time of final transplant. Consequently, important data may be overlooked or imprecise estimates of graft survival result. Data from 91 patients undergoing 182 transplants were examined to determine the effect of pretransplant panel reactive antibodies on graft survival. Our objective is to illustrate, using real-life CIT data, the use of extended Cox-based models and compare with the Kaplan Meier method. We conclude that extended Cox-based models (such as AG; PWP-TT; PWP-GT; LWA) are potentially important in CIT data because estimates of hazard ratio (95%CI) are more consistent and precise compared with KM method.
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