TY - JOUR
T1 - Use of 12-month renal function and baseline clinical factors to predict long-term graft survival
T2 - Application to BENEFIT and BENEFIT-EXT trials
AU - Schnitzler, Mark A.
AU - Lentine, Krista L.
AU - Axelrod, David
AU - Gheorghian, Adrian
AU - You, Min
AU - Kalsekar, Anupama
AU - L'Italien, Gilbert
PY - 2012/1/27
Y1 - 2012/1/27
N2 - Background. Innovation in renal transplant management would benefit from identification of early markers that accurately predict long-term graft survival. Methods. Data from the United States Renal Data System for kidney transplant recipients (1995-2004) were analyzed to develop prediction models for all-cause graft survival based on estimated glomerular filtration rate (eGFR), the presence or absence of acute rejection within 1 year, and recipient and donor demographic characteristics. The prediction models were applied to participants in the Belatacept Evaluation of Nephroprotection and Efficacy as First-line Immunosuppression Trial and Belatacept Evaluation of Nephroprotection and Efficacy as First-line Immunosuppression Trial-EXTended criteria donors trials comparing belatacept with cyclosporine in standard criteria donor (SCD) and expanded criteria donor (ECD) graft recipients, respectively, as an external validation of the model predictions in a diverse population. Results. Compared with eGFR 60 mL/min/1.73 m, the relative hazard for all-cause graft loss increased in an accelerating pattern with lower GFR to approximately eight and seven times, respectively, among SCD and ECD recipients with eGFR less than 15 mL/min/1.73 m. When applied to the clinical trial samples, the predicted differences in all-cause graft survival of less intensive belatacept versus cyclosporine at the second transplant anniversary (SCD: 3.9%, 95% confidence interval [CI]: 3.6% to 4.2%; ECD: 4.1%, 95% CI: 3.5% to 4.7%) were similar to observed differences (SCD: 4.2%, 97.3% CI:-1.3% to 10.1%; ECD: 1.4%, 97.3% CI:-7.5% to 10.2%). Conclusions. Accurate models of long-term graft survival can be developed using eGFR, donor, and recipient characteristics. Long-term survival prediction models may provide an efficient method for assessing the impact of novel pharmaceutical agents and clinical management protocols.
AB - Background. Innovation in renal transplant management would benefit from identification of early markers that accurately predict long-term graft survival. Methods. Data from the United States Renal Data System for kidney transplant recipients (1995-2004) were analyzed to develop prediction models for all-cause graft survival based on estimated glomerular filtration rate (eGFR), the presence or absence of acute rejection within 1 year, and recipient and donor demographic characteristics. The prediction models were applied to participants in the Belatacept Evaluation of Nephroprotection and Efficacy as First-line Immunosuppression Trial and Belatacept Evaluation of Nephroprotection and Efficacy as First-line Immunosuppression Trial-EXTended criteria donors trials comparing belatacept with cyclosporine in standard criteria donor (SCD) and expanded criteria donor (ECD) graft recipients, respectively, as an external validation of the model predictions in a diverse population. Results. Compared with eGFR 60 mL/min/1.73 m, the relative hazard for all-cause graft loss increased in an accelerating pattern with lower GFR to approximately eight and seven times, respectively, among SCD and ECD recipients with eGFR less than 15 mL/min/1.73 m. When applied to the clinical trial samples, the predicted differences in all-cause graft survival of less intensive belatacept versus cyclosporine at the second transplant anniversary (SCD: 3.9%, 95% confidence interval [CI]: 3.6% to 4.2%; ECD: 4.1%, 95% CI: 3.5% to 4.7%) were similar to observed differences (SCD: 4.2%, 97.3% CI:-1.3% to 10.1%; ECD: 1.4%, 97.3% CI:-7.5% to 10.2%). Conclusions. Accurate models of long-term graft survival can be developed using eGFR, donor, and recipient characteristics. Long-term survival prediction models may provide an efficient method for assessing the impact of novel pharmaceutical agents and clinical management protocols.
KW - Glomerular filtration rate
KW - Graft failure
KW - Kidney transplantation
KW - Mortality
KW - Regression analysis
KW - Validation
UR - http://www.scopus.com/inward/record.url?scp=84855847138&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84855847138&partnerID=8YFLogxK
U2 - 10.1097/TP.0b013e31823ec02a
DO - 10.1097/TP.0b013e31823ec02a
M3 - Article
C2 - 22198496
AN - SCOPUS:84855847138
VL - 93
SP - 172
EP - 181
JO - Transplantation
JF - Transplantation
SN - 0041-1337
IS - 2
ER -