Second Kidney Transplant Outcomes in Dialysis Dependent Recipients by Induction Type in the United States

BACKGROUND

We examined the association between induction type for a second kidney transplant in dialysis-dependent recipients and the long-term outcomes.

METHODS

Using the Scientific Registry of Transplant Recipients, we identified all second kidney transplant recipients who returned to dialysis before re-transplantation. Exclusion criteria included: missing, unusual, or no-induction regimens, maintenance regimens other than tacrolimus and mycophenolate, and positive crossmatch status. We grouped recipients by induction type into 3 groups: the anti-thymocyte group (N = 9899), the alemtuzumab group (N = 1982), and the interleukin 2 receptor antagonist group (N = 1904). We analyzed recipient and death-censored graft survival (DCGS) using the Kaplan-Meier survival function with follow-up censored at 10 years post-transplant. We used Cox proportional hazard models to examine the association between induction and the outcomes of interest. To account for the center-specific effect, we included the center as a random effect. We adjusted the models for the pertinent recipient and organ variables.

RESULTS

In the Kaplan-Meier analyses, induction type did not alter recipient survival (log-rank P = .419) or DCGS (log-rank P = .146). Similarly, in the adjusted models, induction type was not a predictor of recipient or graft survival. Live-donor kidneys were associated with better recipient survival (HR 0.73, 95% CI [0.65, 0.83], P < .001) and graft survival (HR 0.72, 95% CI [0.64, 0.82], P < .001). Publicly insured recipients had worse recipient and allograft outcomes.

CONCLUSION

In this large cohort of average immunologic-risk dialysis-dependent second kidney transplant recipients, who were discharged on tacrolimus and mycophenolate maintenance, induction type did not influence the long-term outcomes of recipient or graft survival. Live-donor kidneys improved recipient and graft survival.

Bacterial and Viral Infection and Sepsis in Kidney Transplanted Patients

Kidney transplanted patients are a unique population with intrinsic susceptibility to viral and bacterial infections, mainly (but not exclusively) due to continuous immunosuppression. In this setting, infectious episodes remain among the most important causes of death, with different risks according to the degree of immunosuppression, time after transplantation, type of infection, and patient conditions. Prevention, early diagnosis, and appropriate therapy are the goals of infective management, taking into account that some specific characteristics of transplanted patients may cause a delay (the absence of fever or inflammatory symptoms, the negativity of serological tests commonly adopted for the general population, or the atypical anatomical presentation depending on the surgical site and graft implantation). This review considers the recent available findings of the most common viral and bacterial infection in kidney transplanted patients and explores risk factors and outcomes in septic evolution.

A New Clinical and Immunovirological Score for Predicting the Risk of Late Severe Infection in Solid Organ Transplant Recipients: The CLIV Score

BACKGROUND

We aimed at constructing a composite score based on Epstein-Barr virus DNAemia (EBVd) and simple clinical and immunological parameters to predict late severe infection (LI) beyond month 6 in solid organ transplantation (SOT) recipients.

METHODS

Kidney and liver transplant recipients between May 2014 and August 2016 at 4 participating centers were included. Serum immunoglobulins and complement factors, peripheral blood lymphocyte subpopulations, and whole blood EBVd were determined at months 1, 3, and 6. Cox regression analyses were performed to generate a weighted score for the prediction of LI.

RESULTS

Overall, 309 SOT recipients were followed-up for a median of 1000 days from transplant (interquartile range, 822-1124). Late severe infection occurred in 104 patients (33.6%). The CLIV Score consisted of the following variables at month 6: high-level EBVd (>1500 IU/mL) and recurrent infection during the previous months (6 points); recipient age ≥70 years and chronic graft dysfunction (5 points); cytomegalovirus mismatch (4 points); and CD8+ T-cell count <400 cells/μL (2 points). The area under receiver operating characteristics curve was 0.77 (95% confidence interval, 0.71-0.84). The risk of LI at day 1000 was as follows: score 0, 12.6%; score 2-5, 25.5%; score 6-9, 52.7%; score ≥10, 73.5%.

CONCLUSIONS

While waiting for further external validation, the CLIV Score based on clinical and immune-virological parameters is potentially useful to stratify the risk of LI after SOT.

Immunosuppressive Agents and Infectious Risk in Transplantation: Managing the "Net State of Immunosuppression"

Successful solid organ transplantation reflects meticulous attention to the details of immunosuppression, balancing risks for graft rejection against risks for infection. The 'net state of immune suppression' is a conceptual framework of all factors contributing to infectious risk. Assays which measure immune function in the immunosuppressed transplant recipient relative to infectious risk and allograft function are lacking. The best measures of integrated immune function may be quantitative viral loads to assess the individual's ability to control latent viral infections. Few studies address adjustment of immunosuppression during active infections. Thus, confronted with infection in solid organ recipients, the management of immunosuppression is based largely on clinical experience. This review examines known measures of immune function and the immunologic effects of common immunosuppressive drugs and available studies reporting modification of drug regimens for specific infections. These data provide a conceptual framework for the management of immunosuppression during infection in organ recipients.

Derivation and external validation of the SIMPLICITY score as a simple immune-based risk score to predict infection in kidney transplant recipients

Existing approaches for infection risk stratification in kidney transplant recipients are suboptimal. Here, we aimed to develop and validate a weighted score integrating non-pathogen-specific immune parameters and clinical variables to predict the occurrence of post-transplant infectious complications. To this end, we retrospectively analyzed a single-center derivation cohort of 410 patients undergoing kidney transplantation in 2008-2013 in Madrid. Peripheral blood lymphocyte subpopulations, serum immunoglobulin and complement levels were measured at one-month post-transplant. The primary and secondary outcomes were overall and bacterial infection through month six. A point score was derived from a logistic regression model and prospectively applied on a validation cohort of 522 patients undergoing kidney transplantation at 16 centers throughout Spain in 2014-2015. The SIMPLICITY score consisted of the following variables measured at month one after transplantation: C3 level, CD4⁺ T-cell count, CD8⁺ T-cell count, IgG level, glomerular filtration rate, recipient age, and infection within the first month. The discrimination capacity in the derivation and validation cohorts was good for overall (areas under the receiver operating curve of 0.774 and 0.730) and bacterial infection (0.767 and 0.734, respectively). The cumulative incidence of overall infection significantly increased across risk categories in the derivation (low-risk 13.7%; intermediate-risk, 35.9%; high-risk 77.6%) and validation datasets (10.2%, 28.9% and 50.4%, respectively). Thus, the SIMPLICITY score, based on easily available immune parameters, allows for stratification of kidney transplant recipients at month one according to their expected risk of subsequent infection.

Predictive tools to determine risk of infection in kidney transplant recipients

Introduction: Infection represents a major complication after kidney transplantation (KT). Therapeutic drug monitoring is essentially the only approach for the adjustment of immunosuppression in current practice, with suboptimal results. The implementation of immune monitoring strategies may contribute to minimizing the risk of adverse events attributable to over-immunosuppression without compromising graft outcomes.Areas covered: The present review (based on PubMed/MEDLINE searches from database inception to November 2019) is focused on immune biomarkers with no antigen specificity (non-pathogen-specific), including serum levels of immunoglobulins and complement factors, peripheral blood lymphocyte subpopulations, soluble CD30, intracellular ATP production by stimulated CD4⁺ T-cells, and other cell-based immune assays. We also summarized recent advances in the use of replication kinetics of latent viruses to assess the functionality of T-cell immunity, with focus on the nonpathogenic anelloviruses. Finally, the composite risk scores reported in the literature are critically discussed.Expert opinion: Notable efforts have been made to develop an enlarging repertoire of immune biomarkers and prediction models, although most of them still lack technical standardization and external validation. Preventive interventions based on these tools (prolongation of prophylaxis, tapering of immunosuppression, or immunoglobulin replacement therapy in hypogammaglobulinemic patients) remain to be defined, ideally in the context of controlled trials.

A simple score can identify kidney transplant recipients at high risk of severe infection over the following 2 years

BACKGROUND

The aim of this study was to determine whether a composite score of simple immune biomarkers and clinical characteristics could predict severe infections in kidney transplant recipients.

METHODS

We conducted a prospective study of 168 stable kidney transplant recipients who underwent measurement of lymphocyte subsets, immunoglobulins, and renal function at baseline and were followed up for 2 years for the development of any severe infections, defined as infection requiring hospitalization. A point score was developed to predict severe infection based on logistic regression analysis of factors in baseline testing.

RESULTS

Fifty-nine (35%) patients developed severe infection, 36 (21%) had two or more severe infections, and 3 (2%) died of infection. A group of 19 (11%) patients had the highest predicted infectious risk (>60%), as predicted by the score. Predictive variables were mycophenolate use, graft function, CD4+, and natural killer cell number. The level of immunosuppression score had an area under the receiver operating curve of 0.75 (95% CI: 0.67-0.83).

CONCLUSION

Our level of immunosuppression score for predicting the development of severe infection over 2 years has sufficient prognostic accuracy for identification of high-risk patients. This data can inform research that examines strategies to reduce the risks of infection.

Can immune biomarkers predict infections in solid organ transplant recipients? A review of current evidence

Despite improvements in graft survival, solid organ transplantation is still associated with considerable infection induced morbidity and mortality. If we were able to show that serious infection risk was associated with excessive suppression of immune capacity, we would be justified in "personalizing" the extent of immunosuppression by carefully monitored reduction to see if we can improve immune compromize without increasing the risk of rejection. Reliable biomarkers are needed to identify this patients at an increased risk of infection. This review focuses on the currently available evidence in solid organ transplant recipients for immune non-pathogen specific biomarkers to predict severe infections with the susceptibility to particular pathogens according to the component of the immune system that is suppressed. This review is categorized into immune biomarkers representative of the humoral, cellular, phagocytic, natural killer cell and complement system. Biomarkers humoral and cellular systems of the that have demonstrated an association with infections include immunoglobulins, lymphocyte number, lymphocyte subsets, intracellular concentrations of adenosine triphosphate in stimulated CD4⁺ cells and soluble CD30. Biomarkers of the innate immune system that have demonstrated an association with infections include natural killer cell numbers, complement and mannose binding lectin. Emerging evidence shows that quantification of viral nucleic acid (such as Epstein Barr Virus) can act as a biomarker to predict all-cause infections. Studies that show the most promise are those in which several immune biomarkers are assessed in combination. Ongoing research is required to validate non-pathogen specific immune biomarkers in multi-centre studies using standardized study designs.