Pretransplantation soluble CD30 level as a predictor of acute rejection in kidney transplantation: A meta-analysis

Transplantation

Volumn 94, Issue 9, 2012, Pages 911-918

  Chen, Yile ^a   Tai, Qiang ^a   Hong, Shaodong ^a   Kong, Yuan ^a   Shang, Yushu ^a   Liang, Wenhua ^a   Guo, Zhiyong ^a   He, Xiaoshun ^a  

^a SUN YAT SEN UNIVERSITY   (China)

Author keywords

Acute rejection; Kidney transplantation; Meta analysis; Predictor; sCD30

Indexed keywords

CD30 ANTIGEN;

ACCURACY; AREA UNDER THE CURVE; ARTICLE; CONFIDENCE INTERVAL; EMBASE; HUMAN; KIDNEY GRAFT REJECTION; KIDNEY TRANSPLANTATION; MAXIMUM LIKELIHOOD METHOD; MEDLINE; PREDICTION; PREOPERATIVE EVALUATION; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; RISK ASSESSMENT; SENSITIVITY AND SPECIFICITY; SYSTEMATIC REVIEW;

ADULT; ANTIGENS, CD30; BIOLOGICAL MARKERS; FEMALE; GRAFT REJECTION; HUMANS; KIDNEY TRANSPLANTATION; MALE; MIDDLE AGED; PREDICTIVE VALUE OF TESTS; PREOPERATIVE PERIOD; RISK FACTORS; ROC CURVE; SENSITIVITY AND SPECIFICITY;

EID: 84869509306     PISSN: 00411337     EISSN: None     Source Type: Journal    
DOI: 10.1097/TP.0b013e31826784ad     Document Type: Article

References (42)

1. Gebel HM, Bray RA, Nickerson P. Pre-transplant assessment of donor reactive, HLA specific antibodies in renal transplantation: contraindication vs. risk. Am J Transplant 2003; 3: 1488.
2. Smith CA, Gruss HJ, Davis T, et al. CD 30 antigen, a marker for Hodgkin's lymphoma, is a receptor whose ligand defines an emerging family of cytokines with homology to TNF. Cell 1993; 3: 349.
3. Kennedy MK, Willis CR, Armitage RJ. Deciphering CD30 ligand biology and its role in humoral immunity. Immunology 2006; 118: 143.
4. Pelzl S, Opelz G, Wiesel M, et al. Soluble CD30 as a predictor of kidney graft outcome. Transplantation 2002; 73: 3.
5. Rajakariar R, Jivanji N, Varagunam M, et al. High pre-transplant soluble CD30 levels are predictive of the grade of rejection. Am J Transplant 2005; 5: 1922.
6. Süsal C, Pelzl S, Döhler B, et al. Identification of highly responsive kidney transplant recipients using pretransplant soluble CD30. J Am Soc Nephrol 2002; 13: 1650.
7. Ayed K, Abdallah TB, Bardi R, et al. Plasma levels of soluble CD30 in kidney graft recipients as predictors of acute allograft rejection. Transplant Proc 2006; 38: 2300.
8. Nafar M, Farrokhi F, Vaezi M, et al. Pre-transplant and posttransplant soluble CD30 for prediction and diagnosis of acute kidney allograft rejection. Int Urol Nephrol 2009; 41: 687.
9. Giannoli C, Bonnet MC, Perrat G, Houillon A, et al. High pretransplantation soluble CD30 levels: impact in renal transplantation. Transplant Proc 2007; 39: 2574.
10. Wang D, Wu W, Chen J, et al. Pre-transplant soluble CD30 level as a predictor of not only acute rejection and graft loss but pneumonia in renal transplant recipients. Transpl Immunol 2010; 22: 115.
11. Domingues EM, Matuck T, Graciano ML, et al. Panel reactive HLA antibodies, soluble CD30 levels, and acute rejection six months following renal transplant. Clin Transplant 2010; 24: 821.
12. Kovac J, Arnol M, Vidan Jeras B, et al. Pretransplant soluble CD30 serum concentration does not affect kidney graft outcomes 3 years after transplantation. Transplant Proc 2010; 42: 4043.
13. Kim MS, Kim HJ, Kim SI, et al. Pretransplant soluble CD30 level has limited effect on acute rejection, but affects graft function in living donor kidney transplantation. Transplantation 2006; 82: 1602.
14. Azarpira N, Aghdaie MH, Malekpour Z. Soluble CD30 in renal transplant recipients: is it a good biomarker to predict rejection? Saudi J Kidney Dis Transpl 2010; 21: 31.
15. Cinti P, Pretagostini R, Arpino A, et al. Evaluation of pretransplant immunologic status in kidney-transplant recipients by panel reactive antibody and soluble CD30 determinations. Transplantation 2005; 79: 1154.
16. Platt RE, Wu KS, Poole K, et al. Soluble CD30 as a prognostic factor for outcome following renal transplantation. J Clin Pathol 2009; 62: 662.
17. Iv R, He Q, Wang HP, et al. High serum level of the soluble CD30 identifies Chinese kidney transplant recipients at high risk of unfavorable outcome. Transplant Proc 2008; 40: 3375.
18. Spiridon C, Nikaein A, Lerman M, et al. CD30, a marker to detect the high-risk kidney transplant recipients. Clin Transplant 2008; 22: 765.
19. Vaidya S, Partlow D, Barnes T, et al. Pretransplant soluble CD30 is a better predictor of posttransplant development of donor-specific antibodies and acute vascular rejection than panel reactive antibodies. Transplantation 2006; 82: 1606.
20. Matinlauri IH, Kyllönen LE, Salmela KT, et al. Serum sCD30 in monitoring of alloresponse in well HLA-matched cadaveric kidney transplantations. Transplantation 2005; 80: 1809.
21. Sengul S, Keven K, Gormez U, et al. Identification of patients at risk of acute rejection by pretransplantation and posttransplantation monitoring of soluble CD30 levels in kidney transplantation. Transplantation 2006; 81: 1216.
22. Ló pez-Hoyos M, San Segundo D, Benito MJ, et al. Association between serum soluble CD30 and serum creatinine before and after renal transplantation. Transplant Proc 2008; 40: 2903.
23. Langan LL, Park LP, Hughes TL, et al. Post-transplant HLA class II antibodies and high soluble CD30 levels are independently associated with poor kidney graft survival. Am J Transplant 2007; 7: 847.
24. Dong W, Shunliang Y, Weizhen W, et al. Prediction of acute renal allograft rejection in early post-transplantation period by soluble CD30. Transpl Immunol 2006; 16: 41.
25. Kamali K, Abbasi MA, Farokhi B, et al. Posttransplant Soluble CD30 as a predictor of acute renal allograft rejection. Exp Clin Transplant 2009; 7: 237.
26. Yang JL, Hao HJ, Zhang B, et al. Level of soluble CD30 after kidney transplantation correlates with acute rejection episodes. Transplant Proc 2008; 40: 3381.
27. Matinlauri I, Höckerstedt K, Isoniemi H. High serum soluble CD30 does not predict acute rejection in liver transplant patients. Transplant Proc 2006; 38: 3601.
28. Sakata-Kaneko S, Wakatsuki Y, Matsunaga Y, et al. Altered Th1/Th2 commitment in human CD4+ T cells with ageing. Clin Exp Immunol 2000; 120: 267.
29. Altermann W, Schlaf G, Rothhoff A, et al. High variation of individual soluble serum CD30 levels of pre-transplantation patients: sCD30 a feasible marker for prediction of kidney allograft rejection? Nephrol Dial Transplant 2007; 22: 2795.
30. Wells GA, Shea B, O'Connell D, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses, Ottawa Health Research Institute (2011), Available at: www.ohri.ca/programs/clinical- epidemiology/oxford.asp. Accessed Oct 20, 2011.
31. Stroup DF, Berlin JA, Morton SC, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 2000; 283: 2008.
32. Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ 2009; 339: b2700.
33. Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ 2009; 339: b2535.
34. Altman DG, Bland JM. Diagnostic tests 1: sensitivity and specificity. BMJ 1994; 308: 1552.
35. Deeks JJ, Altman DG. Diagnostic tests 4: likelihood ratios. BMJ 2004; 329: 168.
36. Glas AS, Lijmer JG, Prins MH, et al. The diagnostic odds ratio: a single indicator of test performance. J Clin Epidemiol 2003; 56: 1129.
37. Moses LE, Shapiro D, Littenberg B. Combining independent studies of a diagnostic test into a summary ROC curve: data-analytic approaches and some additional considerations. Stat Med 1993; 12: 1293.
38. DerSimonian R, Kacker R. Random-effects model for meta-analysis of clinical trials: An update. Contemp Clin Trials 2007; 28: 105.
39. Devillé WL, Buntinx F, Bouter LM, et al. Conducting systematic reviews of diagnostic studies: didactic guidelines. BMC Med Res Methodol 2002; 2: 9.
40. Egger M, Davey Smith G, Schneider M, et al. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997; 315: 629.
41. Sterne JA, Gavaghan D, Egger M. Publication and related bias in metaanalysis: power of statistical tests and prevalence in the literature. J Clin Epidemiol 2000; 53: 1119.
42. Zamora J, Muriel A, Abraira V. Meta-DiSc for Windows. XI Cochrane Colloquium. Barcelona, 2003.