Nomogram that predicts graft survival probability following living-donor kidney transplant

被引:0
作者
Akl, Ahmed [1 ]
Mostafa, Amani [1 ]
Ghoneim, Mohamed A. [1 ]
机构
[1] Urol & Nephrol Ctr, Mansoura, Egypt
关键词
renal transplantation; prognostic model; prediction; regression modeling; prognostic tools;
D O I
暂无
中图分类号
R3 [基础医学]; R4 [临床医学];
学科分类号
1001 ; 1002 ; 100602 ;
摘要
Objectives: The goal of this project was to develop a nomogram that predicts the probability of graft survival at 5 years. Materials and Methods: From our dataset, 1581 patients were used to construct a nomogram (modeling group), the remaining 319 patients (testing group) were used for its validation. Initially, the modeling group variables were correlated with graft survival by univariate analysis. Significant factors were subjected to a multivariate analysis using a Cox regression model. The results formed the basis of our nomogram construction. Internal validation was done first by discrimination using the concordance index. Second, the calibration was assessed graphically. And finally, for external validation, the nomogram was used to predict graft survival using the testing group. The predicted probability(s) was compared with the actual survival estimates. Results: Validation of the nomogram yielded a concordance index of 0.77, and the observed correspondence between predicted and actual outcomes suggested a high level of calibration. Nomogram predictions of the testing group revealed no differences in the means of predicted and observed graft survival at 5 years, with a high correlation coefficient and accepted predictive accuracy (concordance index, 0.72). Conclusions: We developed a well-validated and reasonably precise nomogram for predicting 5-year graft survival.
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收藏
页码:30 / 36
页数:7
相关论文
共 19 条
[1]   Prediction of delayed renal allograft function using an artificial neural network [J].
Brier, ME ;
Ray, PC ;
Klein, JB .
NEPHROLOGY DIALYSIS TRANSPLANTATION, 2003, 18 (12) :2655-2659
[2]   Novel artificial neural network for early detection of prostate cancer [J].
Djavan, B ;
Remzi, M ;
Zlotta, A ;
Seitz, C ;
Snow, P ;
Marberger, M .
JOURNAL OF CLINICAL ONCOLOGY, 2002, 20 (04) :921-929
[3]   Validation of the postoperative nomogram for 12-year sarcoma-specific mortality [J].
Eilber, FC ;
Brennan, MF ;
Eilber, FR ;
Dry, SM ;
Singer, S ;
Kattan, MW .
CANCER, 2004, 101 (10) :2270-2275
[4]   Prediction of 3-yr cadaveric graft survival based on pre-transplant variables in a large national dataset [J].
Goldfarb-Rumyantzev, AS ;
Scandling, JD ;
Pappas, L ;
Smout, RJ ;
Horn, S .
CLINICAL TRANSPLANTATION, 2003, 17 (06) :485-497
[5]   Validation study of the accuracy of a postoperative nomogram for recurrence after radical prostatectomy for localized prostate cancer [J].
Graefen, M ;
Karakiewicz, PI ;
Cagiannos, I ;
Klein, E ;
Kupelian, PA ;
Quinn, DI ;
Henshall, SM ;
Grygiel, JJ ;
Sutherland, RL ;
Stricker, PD ;
de Kernion, J ;
Cangiano, T ;
Schröder, FH ;
Wildhagen, MF ;
Scardino, PT ;
Kattan, MW .
JOURNAL OF CLINICAL ONCOLOGY, 2002, 20 (04) :951-956
[6]   Utility of a mathematical nomogram to predict delayed graft function: A single-center experience [J].
Grossberg, JA ;
Reinert, SE ;
Monaco, AP ;
Gohh, R ;
Morrissey, PE .
TRANSPLANTATION, 2006, 81 (02) :155-159
[7]   Variable selection under multiple imputation using the bootstrap in a prognostic study [J].
Heymans, Martijn W. ;
van Buuren, Stef ;
Knol, Dirk L. ;
van Mechelen, Willem ;
de Vet, Henrica C. W. .
BMC MEDICAL RESEARCH METHODOLOGY, 2007, 7 (1)
[8]  
Kantoff PW, 2003, J UROLOGY, V170, pS10
[9]   Development and validation of a nomogram predicting the outcome of prostate biopsy based on patient age, digital rectal examination and serum prostate specific antigen [J].
Karakiewicz, PI ;
Benayoun, S ;
Kattan, MW ;
Perrotte, P ;
Valiquette, L ;
Scardino, PT ;
Cagiannos, I ;
Heinzer, H ;
Tanguay, S ;
Aprikian, AG ;
Huland, H ;
Graefen, M .
JOURNAL OF UROLOGY, 2005, 173 (06) :1930-1934
[10]  
Kattan MW, 1997, CANCER-AM CANCER SOC, V79, P528, DOI 10.1002/(SICI)1097-0142(19970201)79:3<528::AID-CNCR15>3.0.CO