Secondary Logo

Journal Logo

Posttransplant sCD30 as a Predictor of Kidney Graft Outcome

Süsal, Caner1,5; Döhler, Bernd1; Sadeghi, Mahmoud1; Salmela, Kaija T.2; Weimer, Rolf3; Zeier, Martin4; Opelz, Gerhard1

doi: 10.1097/TP.0b013e31821aba74
Clinical and Translational Research

Background. Reliable markers for assessing the biological effect of immunosuppressive drugs and identification of transplant recipients at risk of developing rejection are not available.

Methods. In a prospective multicenter study, we investigated whether posttransplant measurement of the T-cell activation marker soluble CD30 (sCD30) can be used for estimating the risk of graft loss in kidney transplant recipients. Pre- and posttransplant sera of 2322 adult deceased-donor kidney recipients were tested for serum sCD30 content using a commercial enzyme-linked immunosorbent assay.

Results. sCD30 decreased posttransplant and reached a nadir on day 30. Patients with a high sCD30 of more than or equal to 40 U/mL on day 30 showed a subsequent graft survival rate after 3 years of 78.3±4.1%, significantly lower than the 90.3±1.0% rate in recipients with a low sCD30 on day 30 of less than 40 U/mL (log-rank P<0.001; Cox hazard ratio 2.02, P<0.001). Although an association was found between pre- and posttransplant sCD30 levels, patients with high sCD30 on posttransplant day 30 demonstrated significantly lower 3-year graft survival irrespective of the pretransplant level.

Conclusions. Our data suggest that posttransplant measurement of sCD30 on day 30 is a predictor of subsequent graft loss in kidney transplant recipients and that sCD30 may potentially serve as an indicator for adjustment of immunosuppressive medication.

1Department of Transplantation Immunology, Institute of Immunology, University of Heidelberg, Heidelberg, Germany.

2Division of Transplantation, 4th Department of Surgery, Helsinki University Central Hospital, Helsinki, Finland.

3Department of Internal Medicine, University Clinic of Giessen and Marburg, Campus Giessen, Giessen, Germany.

4Department of Nephrology, University of Heidelberg, Heidelberg, Germany.

The authors declare no conflict of interest.

5Address correspondence to: Caner Süsal, M.D., Department of Transplantation Immunology, Institute of Immunology, University of Heidelberg, Im Neuenheimer Feld 305, D-69120 Heidelberg, Germany.


C.S. and G.O. participated in research design and writing of the manuscript; M.S., K.T.S., R.W., and M.Z. participated in performance of research and evaluation of data; and B.D. participated in statistical analysis and data management.

Received 21 January 2011. Revision requested 8 February 2011.

Accepted 15 March 2011.

To diminish undesired side effects and to guide the efficacy of immunosuppressive therapy, posttransplant blood level monitoring of immunosuppressive drugs has become routine practice. However, current drug monitoring does not take into account the drug's variable effect on the immune system of individual patients and consequently there is a risk of over- or underdosing. Reliable biological markers for assessing the biological effect of immunosuppressive treatment on the patient's immune system are not available. Such biomarkers would be useful for identifying patients who are at risk of developing rejection and patients who are suitable for minimization or weaning of immunosuppressive therapy.

We reported previously that the pretransplant serum content of the T-cell activation marker soluble CD30 (sCD30) is associated with chronic graft loss (1). In a subsequent pilot study of 56 kidney graft recipients, we found that a non-decreasing plasma sCD30 content during the first 3 to 5 posttransplant days is associated with acute rejection (2). These preliminary data were supported by the results of additional small single-center studies (3–6). Because of the small numbers of patients studied, important questions such as the optimal operative cut-off, appropriate determination time point, and whether sCD30 can be used for predicting the subsequent graft survival rate and not only acute rejection episodes have not been adequately addressed.

The CD30 molecule, a member of the tumor necrosis factor/nerve growth factor receptor superfamily, is a relatively large 120-kDa glycoprotein that was originally identified as a cell surface antigen on Hodgkin's and Reed Sternberg cells (7). After activation of CD30+ T cells, sCD30 is released into the bloodstream. At variance with previous studies in which CD30 was suggested as a marker of Th2-type immune reactivity (8, 9), more recent studies indicate that CD30 is a co-stimulatory molecule that plays an important role in the generation of memory T-cell responses and regulation of the balance between Th1-/Th2-type immune responses (10, 11). Martinez et al. (12) found that, in contrast to CD3-/CD28-mediated stimulation, CD30+ T cells were the major source of cytokine-producing human T lymphocytes after stimulation with alloantigens, suggesting a specific role of CD30+ T cells in alloimmunity. Gaspal et al. (10) reported that CD30-deficient mice lack memory antibody responses because of deficient CD4+ T-cell memory, and Dai et al. (13) found that CD4+/CD25+ regulatory T cells suppress CD8+ memory T cell-mediated allograft rejection via a CD30-dependent mechanism. It is conceivable that sCD30 in high concentrations may block this inhibitory pathway and lead to an increased memory T-cell response to alloantigens.

In the present study, we focused in a prospective multicenter study on a possible role of sCD30 during the posttransplant phase. We investigated whether measurement of sCD30 can be used for estimating the risk of graft loss in kidney transplant recipients.

Back to Top | Article Outline


As early as on posttransplant day 2, irrespective of whether 40, 50, or 60 U/mL was used as a cut off for the definition of positivity, high sCD30 values were associated with an increased risk of graft loss to year 3 (hazard ratios [HRs], 1.53, 1.60, and 1.57; P=0.050, 0.013, and 0.018, respectively). The most impressive result was obtained when sCD30 was assessed on posttransplant day 30. On this sampling day, sCD30 values reached a nadir with a mean of 21.3 U/mL (standard deviation±24.5) (Fig. 1), which was not significantly different from that found in sera of healthy controls (16.7 U/mL, standard deviation±10.2, exact Mann-Whitney U test, P=0.21). In 113 patients with an sCD30 of more than or equal to 40 U/mL on posttransplant day 30, the HR for graft loss to year 3 was 2.02 (95% confidence interval [CI], 1.33–3.07; P<0.001). Calculated from the posttransplant day of serum sample onward, these patients showed a 3-year graft survival rate of 78.3±4.1%, which was significantly lower than the 90.3±1.0% rate in 1149 recipients with a low sCD30 of less than 40 U/mL on day 30 (log-rank P<0.001) (Fig. 2). A lower cut off of 30 U/mL yielded a relatively unsatisfactory result (HR, 1.65), whereas higher cut offs of 50 or 60 clearly indicated an increased risk (HR, 2.01; P=0.004 and 2.12; P=0.009, respectively) but were found in much smaller patient numbers (77 and 48, respectively). Results based on sera obtained at time points later than 30 days yielded statistically significant results that were less impressive (not shown), leading us to conclude that measurement on day 30 appeared to be most clearly associated with graft survival. When patients who received cyclosporine, tacrolimus, mycophenolate acid, azathioprine, interleukin (IL)-2 receptor antagonists, or antithymocyte globulin were analyzed separately, the 3-year graft survival rate in patients with high sCD30 on posttransplant day 30 was significantly lower than that in patients with low sCD30 in all subgroups (P=0.022, 0.014, 0.003, <0.001, 0.043, 0.033, respectively).





Forty-two percent of patients with high (≥40 U/mL) sCD30 on posttransplant day 30 demonstrated a high pretransplant sCD30 value of more than or equal to 100 U/mL (=the relevant pretransplant cut-off established in previous studies), in contrast to only 11% of patients with low sCD30 on day 30 (P<0.001), thus indicating a strong association between pre- and posttransplant sCD30 levels. Six percent of patients with low pretransplant sCD30 developed high sCD30 on posttransplant day 30, and 73% of patients with a high pretransplant sCD30 demonstrated low sCD30 on posttransplant day 30. Importantly, irrespective of whether the pretransplant level was high or low, the sCD30 value obtained on posttransplant day 30 was significantly associated with the 3-year graft survival rate: pre-Tx high/post-Tx high: 78.8±6.3%, n=44; pre-Tx low/post-Tx high: 80.7±5.3%, n=60; pre-Tx low/post-Tx low: 89.9±1.1%, n=908; pre-Tx high/post-Tx low: 92.1±2.7%, n=109. Corresponding log-rank P values: high/high versus high/low: P=0.018; high/high versus low/low: P=0.008; low/high versus low/low: P=0.016; low/high versus high/low: P=0.031; low/high versus high/high: P=0.77; and low/low versus high/low P=0.57. These results show clearly that it is the posttransplant value that is relevant, irrespective of the pretransplant sCD30 value.

When posttransplant sCD30 was analyzed in combination with posttransplant enzyme-linked immunosorbent assay (ELISA)-reactive human leukocyte antigen (HLA) antibodies, 19 patients with high sCD30 of more than or equal to 40 U/mL and high HLA class I or II antibody reactivity of more than or equal to 250 (optical density) on posttransplant day 30 showed a 3-year graft survival rate of only 65.2±13.5%, in contrast to a 90.9±1.1% rate in 835 patients with low sCD30 and low HLA antibody reactivity on day 30 (log-rank P<0.001). Even in 87 patients with low HLA antibody reactivity, high sCD30 on day 30 was associated with an impaired 3-year graft survival rate of 82.2±4.2% (P=0.005 compared with low sCD30 and low antibody).

Numerous authors have reported that impaired early posttransplant graft function indicates an increased risk for subsequent graft loss (14, 15). It was therefore necessary to test for dissociation of increased sCD30 from increased serum creatinine. In contrast to creatinine, sCD30 is a rather large molecule (molecular weight=85 kDa), which should not be filtered by the kidney and therefore should not accumulate in the patient's serum. In previous investigations, we did not observe significant changes in serum sCD30 values of chronic dialysis patients measured before, during, or immediately after dialysis during two subsequent dialysis cycles (1). To exclude the possibility that high sCD30 might simply be a reflection of impaired graft function in this study, subanalysis was performed in 409 patients for whom information was available on serum creatinine on posttransplant day 30 (median, 1.8 mg/dL; interquartile range, 1.1 mg/dL). As expected, no association was observed between serum sCD30 and creatinine (Spearman rho=−0.017, P=0.74). Even in the presence of a low serum creatinine of less than 1.5 mg/dL, 10 patients with high sCD30 on day 30 showed a significantly lower graft survival at 3 years than 115 patients with low sCD30 (80.0±12.6% vs. 96.3±1.8%, P=0.031). In Cox regression analysis, in which serum creatinine was considered a confounder, high sCD30 and high creatinine of more than or equal to 3.0 mg/dL on posttransplant day 30 were found to be independent risk factors for subsequent graft loss to year 3 (sCD30≥40: HR=2.33, CI=1.27–4.29, P=0.006; creatinine 1.5–2.9: HR=1.76, CI 0.76–4.08, P=0.19; creatinine ≥3.0 mg/dL: HR=4.66, CI=1.97–11.02, P<0.001). At posttransplant year 1, serum creatinine values from all 675 patients were available for analysis. The highest 3-year graft survival rate calculated from year 1 was observed in 355 patients with low sCD30 and a low creatinine of less than 1.5 mg/dL at year 1, and the lowest in 73 patients with high sCD30 and a high creatinine of more than or equal to 1.5 mg/dL (97.5±1.0% vs. 81.8±5.1%, P<0.001). Fifty-three patients with high sCD30 but low creatinine and 194 patients with high creatinine but low sCD30 showed intermediate survival rates of 91.7±4.0% and 90.4±2.7%, respectively, suggesting that both parameters are predictive of outcome independent from each other.

Back to Top | Article Outline


In this prospective multicenter study, we targeted the clinical utility of posttransplant sCD30 measurement as a potential indicator for an increased risk of subsequent kidney graft loss. Because we recognized that large numbers of patients would be necessary for obtaining a meaningful result, we enlisted the support of transplant centers participating in the Collaborative Transplant Study (16). With the aid of 28 transplant centers from 16 countries, we obtained pre- and posttransplant sera for sCD30 determination on 2322 patients. Our key finding is that a serum sCD30 content of more than or equal to 40 U/ml on posttransplant day 30 is associated with a twofold increased risk of subsequent graft loss. This finding substantiates previous observations from small single-center studies in which posttransplant sCD30 was found to be associated with graft rejection in kidney, lung, and pancreatic islet transplantation (3, 6, 17, 18).

We have previously observed increased sCD30 levels in sera of preimmunized patients and patients who rejected a previous kidney transplant (1), and we and others have reported that patients with a high sCD30 serum content before transplantation show a decreased transplant success rate (1, 6, 19). These findings were appropriately considered in the present study by performing multivariate analysis considering preimmunization and retransplantation as confounders. Taken together, our data suggest that high serum levels of sCD30 before or after transplantation reflect an activated alloimmune state. This hypothesis is supported by in vitro experimental findings which identified CD30+ T cells as the major source of γ-interferon and IL-5 cytokine-producing human T-lymphocytes generated in response to stimulation with alloantigens (12). Conventional rejection diagnosis in the clinic, which usually consists of serum creatinine monitoring and allograft biopsy, does not recognize the underlying immune process at an early cellular response stage, but assesses progressive inflammatory destruction of the graft and first signs of functional failure. As shown in the present study, the non-invasive measurement of sCD30 on day 30 allows the identification of patients who are at an increased risk of graft loss even in patients with a good serum creatinine value and thus before substantial damage occurred in the graft. Even in patients reported by participating centers to have “excellent graft function” and a low serum creatinine of less than 1.5 mg/dL, sCD30 measured on posttransplant day 30 was significantly associated with subsequent graft survival.

As currently practiced, drug monitoring is restricted to measurement of blood levels and does not consider the drug's variable effect on the individual patient's immune system. For example, genetic variants of CYP3A5 were reported to influence blood levels of the immunosuppressive agents cyclosporine and tacrolimus (20), showing that an immunosuppressive drug can be well absorbed but have a limited effect on the immune system due to genetic variation at its target protein or other proteins in the biosynthetic pathway. On average, we noted a fourfold decrease of sCD30 values during the first month after transplantation, suggesting a direct effect of immunosuppressive therapy on sCD30 levels. When levels of HLA antibodies were analyzed, the (presumed) effect of immunosuppression was not nearly as strong, showing a 20% to 25% decline already on day 2, without a further decrease during subsequent follow up (data not shown). These observations are in agreement with the notion that currently used immunosuppressive regimens primarily affect T-cell alloreactivity. The fraction of patients who had a high sCD30 value on posttransplant day 30 was 9%. Our data suggest that, in this fraction, higher doses or different methods of immunosuppression might be necessary to prevent T-cell-mediated rejection. On the other hand, those patients who have low levels of sCD30 might benefit from minimization or weaning of immunosuppressive therapy. We recognize the speculative nature of this hypothesis and suggest that prospective trials be performed to address this question.

Although patients possessing both HLA antibodies and high sCD30 in their posttransplant serum had a particularly poor graft outcome, the described sCD30 effect was also evident in patients without HLA antibodies. Our findings thus support the well-known T-cell-associated feature of sCD30 but more studies are needed to clarify the role, origin, and characteristics of sCD30 and CD30+ T cells in the alloimmune response. It is interesting that we found a strong association between pre- and posttransplant sCD30 levels. This leads to the intriguing question whether elevated sCD30 might result from a genetic condition favoring CD30+ T-cell activation and what nature of pretransplant exposure to immunizing events might lead to CD30+ T-cell activation, aside from the posttransplant response to the transplant itself. Importantly, even if the pretransplant sCD30 level was high, patients with low sCD30 on posttransplant day 30 demonstrated excellent graft survival during further follow-up.

Our study describes a statistical association and does not prove causal relationship between high sCD30 and graft loss. We also recognize that the absence of biopsy data for confirmation of immunological graft loss is a limitation of our study. However, collecting biopsy material from multiple centers participating in the Collaborative Transplant Study seemed impractical and would in all likelihood have introduced bias, because it has been shown that there is large variation between institutions in the histological grading of renal allograft biopsies (21, 22). Supporting our use of graft loss as study endpoint, El-Zoghby et al. (23) showed that after detailed investigation of 330 patients who had lost a kidney transplant, the majority of graft losses could be ascribed to the consequences of alloimmunity. A further limitation of the study is that we cannot entirely exclude selection bias. Because of the multicenter nature of the study and limitations in our ability to control sample taking, serum samples were not obtained at all intended posttransplant time points. However, there was no indication of intentional bias in sampling and our analysis was based on all available serum samples without any exclusion.

In conclusion, our data suggest that posttransplant measurement of serum sCD30 on day 30 can be used to identify recipients who are at a high risk of subsequent graft loss. sCD30 is an attractive immunological marker because it is a relatively large molecule (85 kDa), which is resistant to repeated thawing cycles and temperature differences (1). A further advantage is the technical simplicity of sCD30 testing, which can be carried out using a commercially available ELISA. Whether sCD30-based adjustment of immunosuppressive therapy can prevent irreversible graft damage and improve long-term graft outcome remains to be tested in randomized controlled trials.

Back to Top | Article Outline


In a prospective study, sera of 2322 adult (≥18 years old) deceased donor kidney recipients transplanted between 1999 and 2008 were provided by 28 transplant centers from 16 countries (see Appendix). Patient consent was obtained and all investigations were carried out in adherence to the Declaration of Helsinki. The centers were asked to send one pretransplant serum and subsequent posttransplant sera obtained on days 2 (range, days 1–2), 4 (3–4), 6 (5–7), 30 (20–40), 90 (70–110), 180 (150–210), 365 (320–400), and 730 (690–770) to the study center in Heidelberg. Sera were shipped frozen and tested for serum sCD30 content using a commercially available ELISA kit (Bender MedSystems, Vienna, Austria). Because of varying posttransplant follow-up routines and logistical difficulties with scheduling, sera were not obtained at all sampling points on all patients that were enrolled in the study. Analysis was carried out based on all available serum measurements without any exclusion. Sera obtained from 120 adult healthy blood donors served as controls. Based on previous findings, pretransplant sCD30 values of more than or equal to 100 U/mL were considered as “high” (1). Because patients who received immunosuppressive treatment generally had lower sCD30 blood levels than pretransplant patients, it was necessary to determine the clinically most meaningful cut-off for posttransplant sCD30 analysis (see Results section).

sCD30 results were entered into the Collaborative Transplant Study database (16) and connected with previously registered information on the transplants in a blinded manner. A total of 95.5% of the patients received calcineurin inhibitors (44.4% cyclosporine and 51.1% tacrolimus), 79.9% mycophenolate acid, 10.7% azathioprine, and 6.0% mammalian target of rapamycin inhibitors. A total of 9.5% of the patients received antibody induction therapy with depleting and 40.9% with non-depleting antibodies. A total of 36.3% of the patients were women and 13.4% were retransplant recipients. Further characteristics of the complete patient series are shown in Table 1, and demographics of patients with low or high sCD30 in Table 2.





HLA typings and panel reactive antibody determinations were performed in the tissue typing laboratories of participating centers and reported to the study center in Heidelberg for analysis. All pretransplant sera were tested at the study center also for the presence of HLA alloantibodies using the AbScreen I und II ELISA kits of Bio-Rad (Munich, Germany), which use pooled HLA antigens and enable detection of HLA-A, -B, -C, -DR, and -DQ antibodies of the IgG isotype. Based on our previous findings (24, 25), an optical density (OD) of more than or equal to 300 was used as cut-off for positivity. Information on graft function and patient survival was documented at 3 and 6 months and yearly thereafter. Actuarial survival rates were computed according to the Kaplan-Meier method (26) and expressed as % ±standard error. Curves were compared using the log-rank test. For multivariate Cox regression analysis the following confounders were considered: transplant year, transplant number (retransplant), recipient race, recipient gender, donor gender, geographical region, recipient age, donor age, HLA A+B+DR mismatches, highest pretransplant cytotoxic panel reactivity, time on dialysis, original disease, ischemic preservation time, general clinical evaluation of the patient as a candidate for transplantation, and immunosuppressive therapy (type of calcineurin inhibitor, type of antimetabolite, steroids, antibody induction with IL-2 receptor antagonist, antibody induction with antithymocyte globulin). A back step elimination algorithm was used to exclude confounding factors with a threshold of P more than 0.2, and HRs for cumulative 3-year survival after serum date were calculated. Statistical calculations were performed using IBM SPSS Statistics (PASW version 18.0, SPSS Inc., Chicago, IL).

Back to Top | Article Outline


The authors thank Tina Nonn for excellent technical assistance, Andrea Ruhenstroth for assistance with the computer analysis, and staff members at the participating laboratories and clinical units for supplying us with sera and clinical follow-up data.

Back to Top | Article Outline


Sera and data for this multicenter analysis were provided by transplantation centers in the following cities: Baracaldo, Spain (Dr. Maruri, n=31); Bremen, Germany (Dr. Melchior, n=3); Budapest, Hungary (Dr. Langer, n=108); Cagliari, Italy (Dr. Altieri, n=66); Dresden, Germany (Dr. Gross, n=3); Freiburg, Germany (Dr. Pisarski, n=152); Giessen, Germany (Dr. Weimer, n=117); Halle, Germany (Dr. Altermann, n=2); Heidelberg, Germany (Dr. Zeier, n=421); Helsinki, Finland (Dr. Kyllönen, n=148); Innsbruck, Austria (Dr. Bösmüller, n=30); Izmir, Turkey (Dr. Yener, n=13); Leuven, Belgium (Dr. Vanrenterghem, n=314); Mannheim, Germany (Dr. Schnülle, n=1); Medellin, Columbia (Dr. Garcia, n=28); Mexico City, Mexico (Dr. Alberu-Gomez, n=14); Portland, OR (Dr. Norman, n=10); Porto Alegre, Brazil (Dr. Duro-Garcia, n=14); Prague, Czechia (Dr. Slavcev, n=172); Quebec, Canada (Dr. Roy, n=333); Reims, France (Dr. Cohen, n=23); Rijeka, Croatia (Dr. Balen, n=57); Rostock, Germany (Dr. Stein, n=3); Sao Paulo, Brazil (Dr. Medina-Pestana, n=11); St. Etienne, France (Dr. Berthoux, n=22); Torino, Italy (Dr. Amoroso, n=213); Ulm, Germany (Dr. Mytilineos, n=11), Valencia, Spain (Dr. Simon, n=2). We are indebted to the colleagues and staff members at these centers for their invaluable support.

Back to Top | Article Outline


1. 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.
2. Pelzl S, Opelz G, Daniel V, et al. Evaluation of posttransplantation soluble CD30 for diagnosis of acute renal allograft rejection. Transplantation 2003; 75: 421.
3. Süsal C, Opelz G. Options for immunologic support of renal transplantation through the HLA and immunology laboratories. Am J Transplant 2007; 7: 1450.
4. Wang D, Wu GJ, Wu WZ, et al. Pre- and post-transplant monitoring of soluble CD30 levels as predictor of acute renal allograft rejection. Transpl Immunol 2007; 17: 278.
5. 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.
6. Cervelli C, Fontecchio G, Scimitarra M, et al. Evaluation of serum sCD30 in renal transplantation patients with and without acute rejection. Transplant Proc 2009; 41: 1159.
7. Dürkop H, Latza U, Hummel M, et al. Molecular cloning and expression of a new member of the nerve growth factor receptor family that is characteristic for Hodgkin's disease. Cell 1992; 68: 421.
8. Del Prete G, De Carli M, Almerigogna F, et al. Preferential expression of CD30 by human CD4+ T cells producing Th2-type cytokines. FASEB J 1995; 9: 81.
9. Frezzolini A, Paradisi M, Ruffelli M, et al. Soluble CD30 in pediatric patients with atopic dermatitis. Allergy 1997; 52: 106.
10. Gaspal FM, Kim MY, McConnell FM, et al. Mice deficient in OX40 and CD30 signals lack memory antibody responses because of deficient CD4 T cell memory. J Immunol 2005; 174: 3891.
11. Pellegrini P, Berghella AM, Contasta I, et al. CD30 antigen: Not a physiological marker for TH2 cells but an important costimulator molecule in the regulation of the balance between TH1/TH2 response. Transpl Immunol 2003; 12: 49.
12. Martinez OM, Villanueva J, Abtahi S, et al. CD30 expression identifies a functional alloreactive human T-lymphocyte subset. Transplantation 1998; 65: 1240.
13. Dai Z, Li Q, Wang Y, et al. CD4+CD25+ regulatory T cells suppress allograft rejection mediated by memory CD8+ T cells via a CD30-dependent mechanism. J Clin Invest 2004; 113: 310.
14. Halloran PF, Hunsicker LG. Delayed graft function: State of the art, November 10–11, 2000. Summit meeting, Scottsdale, Arizona, USA. Am J Transplant 2001; 1: 115.
15. Süsal C, Döhler B, Sadeghi M, et al. HLA antibodies and the occurrence of early adverse events in the modern era of transplantation: A collaborative transplant study report. Transplantation 2009; 87: 1367.
16. Collaborative Transplant Study, University of Heidelberg, Germany, Website. Available at: Accessed January 14, 2011.
17. Fields RC, Bharat A, Steward N, et al. Elevated soluble CD30 correlates with development of bronchiolitis obliterans syndrome following lung transplantation. Transplantation 2006; 82: 1596.
18. Saini D, Ramachandran S, Nataraju A, et al. Activated effector and memory T cells contribute to circulating sCD30: Potential marker for islet allograft rejection. Am J Transplant 2008; 8: 1798.
19. Heinemann FM, Rebmann V, Witzke O, et al. Association of elevated pretransplant sCD30 levels with graft loss in 206 patients treated with modern immunosuppressive therapies after renal transplantation. Transplantation 2007; 83: 706.
20. Haufroid V, Mourad M, Van Kerckhove V, et al. The effect of CYP3A5 and MDR1 (ABCB1) polymorphisms on cyclosporine and tacrolimus dose requirements and trough blood levels in stable renal transplant patients. Pharmacogenetics 2004; 14: 147.
21. Furness PN, Taub N. International variation in the interpretation of renal transplant biopsies: Report of the CERTPAP Project. Kidney Int 2001; 60: 1998.
22. Furness PN, Taub N, Assmann KJ, et al. International variation in histologic grading is large, and persistent feedback does not improve reproducibility. Am J Surg Pathol 2003; 27: 805.
23. El-Zoghby ZM, Stegall MD, Lager DJ, et al. Identifying specific causes of kidney allograft loss. Am J Transplant 2009; 9: 527.
24. Süsal C, Opelz G. Kidney graft failure and presensitization against HLA class I and class II antigens. Transplantation 2002; 73: 1269.
25. Süsal C, Döhler B, Opelz G. Presensitized kidney graft recipients with HLA class I and II antibodies are at increased risk for graft failure: A Collaborative Transplant Study report. Hum Immunol 2009; 70: 569.
26. Kaplan EL, Meier P. Nonparametric estimation from incomplete observations. J Am Stat Assoc 1958; 53: 457.

sCD30; Kidney transplantation; Graft outcome

© 2011 Lippincott Williams & Wilkins, Inc.