Secondary Logo

Share this article on:

Pediatric Outcomes in Transplant

PersOnaliSing Immunosuppression To ImproVe Efficacy (POSITIVE Study)

The Collaboration and Design of a National Transplant Precision Medicine Program

Papaz, Tanya, HBA1,2; Allen, Upton, MBBS2,3; Blydt-Hansen, Tom, MD2,4; Birk, Patricia E., MD5; Min, Sandar, MBBS1,2; Hamiwka, Lorraine, MD2,6; Phan, Veronique, MD7; Schechter, Tal, MD8; Wall, Donna A., MD2,8; Urschel, Simon, MD2,9; Foster, Bethany J., MD2,10; Mital, Seema, MD1,2

doi: 10.1097/TXD.0000000000000842
Pediatric Transplantation

Background Despite age-related differences in biology, physiology, and behavior, transplant immunosuppression is not tailored by age. This likely contributes to high graft failure and posttransplant complications. We present the aims, design, and methods of the Pediatric Outcomes in Transplant: PersOnaliSing Immunosuppression To ImproVe Efficacy Study aimed at personalizing posttransplant immunosuppression in children and young adults.

Methods In this prospective observational cohort study, we recruited pediatric and young adult solid organ transplant, pediatric allogeneic hematopoietic stem cell transplant recipients, and matched living and deceased organ donors from 14 transplant centers across Canada. Clinical data, questionnaires, biospecimens, and pharmacy records were collected at serial time points: (1) to identify genetic and host immune factors that influence immunosuppression dose requirements across different ages and transplant types, (2) to identify viral-host interactions that increase susceptibility to Epstein-Barr virus infection, and (3) to define care processes and structures associated with medication adherence in adolescents and young adults.

Results From 2015 to 2018, 1662 new and prevalent transplant recipients were screened, 1166 were recruited for the various aims, including 370 liver, 445 kidney, 277 heart, 19 lung, 19 multiple, and 36 hematopoietic stem cell transplant transplants. Twelve percent were younger than 2 years, 30% were 2 to 10 years, 42% were 10 to 18 years, and 16% were 18 to 24 years at enrollment. Nine hundred thirty-one consented to participation in aims 1 and 2 (90% consent rate), 287 to aim 3 (82% consent rate). Biospecimens collected included 898 for DNA, 276 for immunoassays, and 717 for biomarker studies. Seventy percent participants have completed follow-up; 30% are pending study completion.

Conclusions The design of this national multicenter cross-organ network helped maximize recruitment of a large patient cohort for studying age and organ-related differences in immunosuppression needs that would not otherwise be feasible. Leveraging the unique clinical, biological, environmental, and behavioral characteristics of this cohort will help develop precision medicine strategies for individualizing posttransplant immunosuppression.

1 Division of Cardiology, Department of Pediatrics, Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.

2 Canadian National Transplant Research Program, Edmonton, Alberta, Canada.

3 Division of Infectious Diseases, Hospital for Sick Children, Toronto, Ontario, Canada.

4 Division of Pediatric Nephrology, University of British Columbia, Vancouver, Canada.

5 Department of Pediatrics and Child Health, Health Sciences Centre Winnipeg, Winnipeg, Manitoba, Canada.

6 Division of Nephrology, Alberta Children's Hospital, University of Calgary, Calgary, Canada.

7 Division of Nephrology, Department of Pediatrics, Centre Hospitalier Universitaire Sainte-Justine, Montreal, Quebec, Canada.

8 Division of Hematology Oncology and Bone Marrow Transplantation, Hospital for Sick Children, Toronto, Ontario, Canada.

9 Division of Pediatric Cardiology, University of Alberta, Edmonton, Alberta, Canada.

10 Division of Nephrology, Montreal Children's Hospital, McGill University Health Centre, Montreal, Quebec, Canada.

Published online 27 November, 2018.

Received 22 August 2018. Revision requested 18 June 2018.

Accepted 15 September 2018.

The authors declare no conflicts of interest.

This work is part of the Canadian National Transplant Research Program (CNTRP) and was supported by the Canadian Institutes for Health Research (CIHR) and partners (grant TFU 127880). Support was also provided by Astellas Pharma Canada, Inc.

S.M., B.J.F., U.A., and S.U. are study investigator scientific leads who have contributed to the research design, analysis and interpretation of data for the project. Study investigators, T.B.-H., V.P., P.E.B, L.H., T.S., and D.A.W., have contributed to the design of the work. T.P. and S.Min. contributed toward data acquisition and analysis. The article was drafted by T.P. and S.M. All authors have approved of the final version to be published.

Trial Registration: ClinicalTrials.gov registration NCT02318030. Registered November 25, 2014.

Correspondence: Seema Mital, MD, Hospital for Sick Children, 555 University Avenue, Toronto, ON, Canada M5G 1X8. (seema.mital@sickkids.ca).

This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

Pediatric transplantation represents up to 15% of all solid organ transplants (SOTs) performed in Canada (14% heart, 10% liver, 3% renal, 1% lung as of 2015 statistics),1 and approximately 18% of hematopoietic stem cell transplants (HSCT).2 Immunosuppression management is challenging with the interval from birth to young adulthood seeing profound changes in physiological processes, body size, and immune maturation. Infancy and adolescence are the periods of most rapid and dramatic change.3-16 Three pivotal factors affect immunosuppression requirements in the young: (1) age-dependent variation in drug metabolism; (2) developmental changes in immune function with increased childhood susceptibility to infections, in particular viruses; and (3) behavioral changes in adolescence and young adulthood leading to poor treatment adherence.

The Pediatric Outcomes in Transplant: PersOnaliSing Immunosuppression To ImproVe Efficacy (POSITIVE) Study is a national collaborative research study that was launched to address the challenges faced by this underrepresented population with unique needs. The Clinical Trials in Organ and Transplantation in Children (CTOT-C) network (ctotc.org) sponsored by the National Institute of Allergy and Infectious Diseases in the US is an example of a multicenter network that supports organ-specific projects.17 Unlike consortia that are age- or organ-specific, the POSITIVE network includes participants across all ages and transplant types with the goal of developing strategies to individualize immunosuppression tailored to the unique biological and behavioral attributes of the growing child.18,19 The POSITIVE network was launched as part of the Canadian National Transplant Research Program funded by the Canadian Institutes for Health Research.20 The purpose of this article is to describe the design of the study and how this unique collaborative will generate a new paradigm for application of precision medicine in the posttransplant care of children and young adults.

The specific aims are to: (1) develop age-appropriate calcineurin inhibitor dosing for pediatric SOT recipients, (2) develop risk prediction tools based on viral genotype and viral-host interactions that predispose to Epstein-Barr virus (EBV) and/or posttransplant lymphoproliferative disorders (PTLD) in SOT and HSCT recipients, (3) develop healthcare delivery strategies to enhance medication adherence in adolescent and young adult SOT recipients (POSITIVE-Adherence study). Figure 1 shows the various disciplines involved in each study aim.

FIGURE 1

FIGURE 1

Back to Top | Article Outline

MATERIALS AND METHODS

Study Design

This was a prospective cohort study involving 14 transplant centers across Canada which included 7 pediatric (including 6 HSCT programs) and 7 adult SOT centers. Incident (listed or newly transplanted) and prevalent (previously transplanted) SOTs were recruited. HSCTs were recruited only for study aim 2. Living transplant donors were recruited where applicable. For deceased transplant donors who had consented to research at the time of donation, samples were obtained through participating histocompatibility (HLA) laboratories (Figure 2). The protocol was approved by the local or central Research Ethics Boards at pediatric (Vancouver: H15-02562; Edmonton: Pro00053576; Calgary: REB15-1876; Winnipeg: HS14051 (H2011:321); Toronto: 1000045186; Montreal: MP-CUSM-14-174-PED) and adult transplant centers (Vancouver: H14-03020; Toronto: 14-8220-AE; Ottawa: 20150393-01H; Montreal: 14.126) and local Organ Procurement Organizations. Written informed consent was obtained from each participant and/or parent/legal guardian and study protocols adhered to the Declaration of Helsinki.

FIGURE 2

FIGURE 2

Back to Top | Article Outline

Study Participants

Aim 1

For the incident cohort, patients 0 to 18 years of age at the time of listing for SOT (heart, liver, kidney, or lung) were approached for consent to participate which included 2-year prospective data collection, self-reported questionnaires, and blood collection for genetic studies and biobanking, and for serial immune function and future biomarker assays (at pretransplant, 3 ± 1 month and 12 ± 3 months posttransplant). Retransplants were excluded. For the prevalent cohort, all patients 0 to 18 years of age who had undergone an SOT were consented for retrospective data collection, and blood or saliva collection for genetic studies. Living donors were approached for blood or saliva collection for genetic studies. For deceased donors who consented to research, leftover DNA available through HLA laboratories was accessed. Target enrollment for incident and prevalent patients was 800.

Back to Top | Article Outline

Aim 2

The SOT recipients who developed new EBV infection ie, seronegative patients who became EBV polymerase chain reaction–positive or developed PTLD during 1-year posttransplant follow-up were eligible for this aim. The HSCT recipients who developed new or secondary EBV infection and/or PTLD were eligible. Eligible retransplants were included. Consented patients were administered an EBV illness severity questionnaire and provided a blood sample for EBV sequencing and immune function assays within 3 weeks of diagnosis (acute phase) and 8 ± 2 weeks later (convalescent phase). Target enrollment was 150 patients including 50 EBV+ SOT recipients, 50 EBV+ HSCT recipients and 50 with PTLD. A schedule of study procedures for aims 1 and 2 are shown in Table 1.

TABLE 1

TABLE 1

Back to Top | Article Outline

Aim 3 (POSITIVE-Adherence Study)

Adolescent and young adult kidney, liver, and heart recipients, 14 to 25 years of age, who were at least 3 months posttransplant with intact graft function and receiving maintenance immunosuppression were eligible for participation in Aim 3. Patients who underwent retransplant or multiorgan transplant, or could not independently complete study questionnaires due to neurocognitive disabilities or language barriers were excluded. Study participation included serial questionnaires (at enrollment, 3 months, and 6 months), manual pill count by study coordinator during follow-up visits, and collection of pharmacy refill records. Within 3 months of the first participant enrolled, transplant directors and nurses were asked to complete questionnaires on care processes and structures in their transplant program. Target enrollment was 300 participants. The schedule of study procedures is detailed in Table 2.

TABLE 2

TABLE 2

Back to Top | Article Outline

Study Procedures, Outcomes, and Planned Analyses

Aim 1

For genetic studies, DNA was extracted from blood from participants for genotyping using the Axiom Transplant Genotyping Array (Thermo Fisher) designed by the iGeneTRAiN international consortium.21,22 The array has 782 000 single-nucleotide polymorphisms (SNPs), copy number variants, and insertion/deletion markers that also include content relevant to transplantation, including HLA and killer immunoglobulin-like receptors markers, phenotype associations, expression quantitative trait loci, pharmacogenomics, ancestry markers and markers related to transplant relevant outcomes. The array includes a comprehensive genomewide imputation grid for major populations, including European, Asian, and African ancestry. The planned approach is a genomewide association study to identify SNPs in recipients and donors associated with variability in tacrolimus trough concentrations after transplant and to combine genetic-, age- and organ-specific factors to develop individualized tacrolimus dosing to achieve and maintain therapeutic drug levels. We will apply principal component analysis to the genotype data for race and other clinical variables to explore unmeasured subpopulations or population structure further. To account for intersubject variation, a linear mixed-effect model, including subject as a random effect, will be applied to the data. Clinical covariates associated with pharmacological outcome will be first identified using univariate models, tacrolimus dose will also be included along with clinical covariates in the model. In addition, the impact of these factors on clinical outcomes will be assessed as described in Tables 3, 4.

TABLE 3

TABLE 3

TABLE 4

TABLE 4

For immune function and maturation assays, peripheral blood mononuclear cells are isolated from heparinized blood samples collected pretransplant, and at 3 and 12 months posttransplant. Immune phenotyping is performed using multicolor flow cytometry with 5 panels of up to 10 surface markers using BD Fortessa and Beckman Coulter Navios flow cytometers. Besides the global phenotyping, T and B cell populations are assessed for specific subtypes. T cells are assessed for naive versus memory/effector, regulatory, recent thymic emigrant, and “exhausted” phenotypes. B cell subanalysis measures (switched) memory phenotypes, transitional, splenic marginal zone and “B-10” cells. To assess the capability of activation and proliferation, peripheral blood mononuclear cells are stimulated with global mitogens and specific antigens, including EBV and cytomegalovirus surface structures and cell lysates. Activation is measured by fluorescence-activated cell sorting via expression of CD69 and quantification of intracellular cytokines. Proliferation is measured after 5 days of stimulation to determine which cells have proliferated and to which generation they have grown and whether memory or naive cells mounted the response. Antigen stimulation provides information specifically with regard to the response to the respective virus and possibly prediction of the risk for persisting infection and development of PTLD. Immune function assays will be compared between patients in different age groups relative to tacrolimus levels. This will help to define the optimum target range of tacrolimus for patients in different age groups and will assist in developing age-appropriate dosing that is targeted to immune function.

Back to Top | Article Outline

Aim 2

Infants and children after SOT or HSCT transplant are at high risk for EBV/PTLD because they are often EBV naive at the time of transplant and therefore lack immunity to EBV.28,29 Higher intensity of immunosuppression also predisposes to EBV. However, little is known about how EBV strains may interact with an immature host system to predispose to disease.30-32 In this aim, blood samples from patients with new and secondary EBV infection will be analyzed using next-generation sequencing to identify EBV genotypes circulating in peripheral blood during acute and convalescent phases. Known EBV subtypes, based on the major latent genes, will be determined in addition to novel subtypes.33 Our primary analysis will be the relationship between major EBV subtypes and clinical and virologic outcomes (illness severity, viral loads, PTLD), evaluated in different age groups. We will assess the interaction between EBV genetic diversity and host immunologic factors (age, immunologic maturation, lymphocyte memory, EBV-specific T cells) that influence host susceptibility to EBV. We will identify whether there is a correlation between lack of immune memory and a higher risk of PTLD in patients with low T cell proliferative capacity. The results will be used to develop an EBV genotyping panel to screen patients with EBV infections to determine which patients exposed should receive EBV therapy.

Back to Top | Article Outline

Aim 3

In addition to biological factors being investigated in aims 1 and 2, psychosocial and organizational factors may influence transplant outcomes in adolescence and young adulthood. To assess this, eligible participants complete a questionnaire assessing factors associated with adherence including health literacy, self-efficacy, trust in the care team, social supports, attitudes toward taking immunosuppression medications, and intention to adhere. Participants also complete the standardized Adolescent Medication Barriers Scale questionnaire.34 A separate set of questions is administered to participants by coordinators to assess socioeconomic status and family structure and support, accessibility to care, and treatment characteristics. Participants from adult centers (>18 years) are also asked to report individual sociocultural, education and labor market activity-related questions. A validated adherence self-report tool, the Basel Assessment of Adherence to Immunosuppressive Medications, is administered at enrollment, 3 and 6 months.35 Medication adherence is also assessed using the combination of a pill count at baseline and pill count and pharmacy refill records over the 6 months of observation. Transplant program directors at each site completed a questionnaire about the characteristics of their program, including factors such as program size, care team composition, care organization, and frequency of routine follow-up. Similarly, transplant nurses at each site complete a questionnaire assessing care processes such as average time spent with patients during clinic visits, methods of assessing and supporting adherence, expertise and competency of team members, and chronic illness management strategies used.36,37

The primary outcome is “taking adherence,” defined as the proportion of prescribed immunosuppressive medication doses taken. The secondary outcomes are “timing adherence,” defined as the proportion of doses taken late, and the rate of “drug holidays,” defined as a period during which 2 or more consecutive doses were missed. Variability in tacrolimus/sirolimus trough levels are assessed as a measure of timing adherence.38-42 Clinic attendance and clinical monitoring tests attended versus expected (based on routine follow-up protocols) are captured and used as an additional predictor of adherence. Graft outcomes and other clinical complications are also collected as secondary outcome measures (Table 3). Although not sufficiently powered due to incomplete overlap of participants in aims 1 and 3, secondary analysis will be performed to assess the relationship between adherence (aim 3) and immunosuppression levels and outcomes (aim 1).

Back to Top | Article Outline

Power Considerations

For genomewide association study analysis in aim 1, assuming minor allele frequency of significant SNPs ranges from 0.04 to 0.23, a sample size of 500 is sufficient to detect a mean additive SNP effect of 1.7 for a SNP having a minor allele frequency of 0.17 in controlling an error rate of 0.05 with 80% power. For aim 2, in a group of 50 participants (100 samples), precision levels from whole genome shotgun sequencing are ±3.5% with 95% confidence to accurately reflect EBV subtypes associated with disease with a minimum prevalence of 5% in the proposed study cohort of 300 samples. For aim 3, based on pilot studies indicating ~78% taking adherence with a SD of 30, we estimate that 300 patients will provide 80% power to detect a correlation between adherence and any continuous variable accounting for 2.5% or greater of the variance in adherence. For categorical variables with a frequency of 10%, we will have 80% power to detect a 20% difference in adherence for that factor. These sample size estimates assume that the small amount of between-program variability in adherence will be explained by between program differences in measured healthcare systems factors.

Back to Top | Article Outline

STUDY PROGRESS

Enrollment for aims 1 and 3 was completed in September 2017 and December 2017 respectively. Enrollment for aim 2 and follow-up of enrolled patients will continue until December 2018. From 2015 to 2018, 1662 new and prevalent transplant recipients were screened, 1166 were recruited across the various aims. This included 370 liver, 445 kidney, 277 heart, 19 lung, 19 multiple, and 36 HSCT transplants. Twelve percent were younger than 2 years, 30% were 2 to 10 years, 42% were 10 to 18 years, and 16% were 18 to 24 years at enrollment. Nine hundred thirty-one consented to participation in aims 1 and 2 (90% consent rate), 287 in aim 3 (82% consent rate). The number of biospecimens collected included 898 for DNA, 276 for immunoassays, and 717 for biomarker studies. Approximately 70% participants have completed the follow-up, and 30% are pending study completion. Figure 3 shows the number of incident, and prevalent patients who were screened, enrolled, and completed 1 year follow-up. Patient characteristics at enrollment and at 1-year follow-up are shown in Table 4.

FIGURE 3

FIGURE 3

Back to Top | Article Outline

DISCUSSION

The goals of precision medicine are to individualize management based on the unique clinical and biological profiles of individuals or groups of individuals. The management of transplant recipients centers around standardized immunosuppression protocols that try to optimize dosing while minimizing immunosuppression-related side effects. However, transplant recipients are clinically and biologically heterogeneous. Yet, individualized approaches are applied very selectively in the transplant field. For example, HLA matching of donor and recipient is used to individualize donor choice.37 There are recommendations to individualize tacrolimus dosing by the recipient CYP3A5 genotype published by the Clinical Pharmacogenetics Implementation Consortium.43 However, these have not had wide uptake and these guidelines do not adjust for age-related differences in pharmacogenetic influences.15 Developing a precision medicine approach that incorporates the clinical and biological heterogeneity of different organ groups across different ages requires access to large patient cohorts to achieve sufficient power. The POSITIVE study enabled us to recruit a large patient cohort to achieve power for these analyses by unifying the various transplant populations for this study. Preliminary results from the various aims are being generated that attest to the power to achieve the study goals.44-48

At completion of analyses, the POSITIVE study will deliver tacrolimus dosing guidelines based on age, organ type and pharmaco-genotype for pediatric SOT patients. This will be complemented by the development of age-appropriate immunosuppression targets based on immune function and maturation at different ages including a better understanding of the specific aspects of the immature immune system that contribute to better graft tolerance in infants. Another important deliverable is an EBV genotype screening panel that will identify EBV strains that are likely to lead to disease through interaction with the host immune system. It will identify high risk patients who would benefit from timely treatment with antiviral therapies or lowering of immunosuppression. In adolescents and young adults who are at high risk for nonadherence, it will identify healthcare processes and structures that can be modified to improve medication adherence. Finally, collaboration with health economists will be used to analyze cost effectiveness of proposed changes to care organization to support advocacy for these changes as part of public health policy.

Several features make the POSITIVE collaboration unique. Leveraging commonalities across SOT and HSCT recipients, we were able to prospectively recruit patients across Canada to achieve larger sample sizes than otherwise possible. Recruiting not just children but also young adults allowed us to compare variability in care processes and structures between pediatric and adult centers, whereas donor recruitment provided us with the ability to incorporate donor characteristics into precision medicine approaches for recipients. Finally, including researchers and clinicians with expertise in transplant medicine, immunology, genetics, pharmacogenetics, precision medicine, virology, epidemiology and healthcare economics will help us to translate discoveries from this study into changes in clinical practice. The longer-term impact of these changes will be assessed through linkage with external administrative databases such as provincial health databases, Canadian Blood Services or the Canadian Institute for Health Information to access long-term outcomes. This is made possible because participants in POSITIVE consented to participate in the Canadian National Transplant Research Program Patient Registration Database. Thus, our efforts at unifying the various transplant communities will help us to change our approach to the care of the transplanted patient across all ages and organ groups.

Back to Top | Article Outline

ACKNOWLEDGMENTS

The authors acknowledge the Canadian Institutes of Health Research, the SickKids Transplant and Regenerative Medicine Centre, and Astellas for funding for this project.

Back to Top | Article Outline

REFERENCES

1. Canadian Institutes for Health Information (CIHI). Canadian organ replacement register (CORR). Available at: https://www.cihi.ca/en/corr-annual-statistics-2017. Published 2017.
2. D'Souza AFC. Current uses and outcomes of hematopoietic cell transplantation (hct): CIBMTR summary slides. Available at: http://www.cibmtr.org. Published 2017.
3. Fan X, Ang A, Pollock-Barziv SM, et al. Donor-specific b-cell tolerance after abo-incompatible infant heart transplantation. Nat Med. 2004;10:1227–1233.
4. Kirk R, Edwards LB, Kucheryavaya AY, et al. The registry of the international society for heart and lung transplantation: fourteenth pediatric heart transplantation report—2011. J Heart Lung Transplant. 2011;30:1095–1103.
5. Urschel S, Cremer S, Birnbaum J, et al. Lack of serologic immunity against vaccine-preventable diseases in children after thoracic transplantation. Transpl Int. 2010;23:619–627.
6. Urschel S, Rieck BD, Birnbaum J, et al. Impaired cellular immune response to diphtheria and tetanus vaccines in children after thoracic transplantation. Pediatr Transplant. 2011;15:272–280.
7. Pollock-Barziv SM, Finkelstein Y, Manlhiot C, et al. Variability in tacrolimus blood levels increases the risk of late rejection and graft loss after solid organ transplantation in older children. Pediatr Transplant. 2010;14:968–975.
8. Foster BJ, Dahhou M, Zhang X, et al. Association between age and graft failure rates in young kidney transplant recipients. Transplantation. 2011;92:1237–1243.
9. Berquist RK, Berquist WE, Esquivel CO, et al. Non-adherence to post-transplant care: prevalence, risk factors and outcomes in adolescent liver transplant recipients. Pediatr Transplant. 2008;12:194–200.
10. Chisholm-Burns MA, Spivey CA, Rehfeld R, et al. Immunosuppressant therapy adherence and graft failure among pediatric renal transplant recipients. Am J Transplant. 2009;9:2497–2504.
11. Feinstein S, Keich R, Becker-Cohen R, et al. Is noncompliance among adolescent renal transplant recipients inevitable? Pediatrics. 2005;115:969–973.
12. Hsu DT. Biological and psychological differences in the child and adolescent transplant recipient. Pediatr Transplant. 2005;9:416–421.
13. Keith DS, Cantarovich M, Paraskevas S, et al. Recipient age and risk of chronic allograft nephropathy in primary deceased donor kidney transplant. Transpl Int. 2006;19:649–656.
14. Takemoto SK, Pinsky BW, Schnitzler MA, et al. A retrospective analysis of immunosuppression compliance, dose reduction and discontinuation in kidney transplant recipients. Am J Transplant. 2007;7:2704–2711.
15. Gijsen V, Mital S, van Schaik RH, et al. Age and cyp3a5 genotype affect tacrolimus dosing requirements after transplant in pediatric heart recipients. J Heart Lung Transplant. 2011;30:1352–1359.
16. Thervet E, Loriot MA, Barbier S, et al. Optimization of initial tacrolimus dose using pharmacogenetic testing. Clin Pharmacol Ther. 2010;87:721–726.
17. Clinical trials in organ transplantation in children (CTOT-C). Available at: http://www.ctotc.org. Published 2009.
18. McCarty TP, Baddley JW, Walsh TJ, et al. Phaeohyphomycosis in transplant recipients: results from the transplant associated infection surveillance network (transnet). Med Mycol. 2015;53:440–446.
19. GiaQuinta S, Michaels MG, McCullers JA, et al. Randomized, double-blind comparison of standard-dose vs. high-dose trivalent inactivated influenza vaccine in pediatric solid organ transplant patients. Pediatr Transplant. 2015;19:219–228.
20. Hebert MJ, Hartell D, West L. Transdisciplinary tour-de-force: the Canadian national transplant research program. Transplantation. 2016;100:466–470.
21. International Genetics & Translational Research in Transplantation Network (iGeneTRAiN). Design and implementation of the international genetics and translational research in transplantation network. Transplantation. 2015;99:2401–2412.
22. Li YR, van Setten J, Verma SS, et al. Concept and design of a genome-wide association genotyping array tailored for transplantation-specific studies. Genome Med. 2015;7:90.
23. Solez K, Colvin RB, Racusen LC, et al. Banff ’05 Meeting Report: differential diagnosis of chronic allograft injury and elimination of chronic allograft nephropathy (‘CAN’). Am J Transplant. 2007;7:518–526.
    24. Costanzo MR, Dipchand A, Starling R, et al. The International Society of Heart and Lung Transplantation Guidelines for the care of heart transplant recipients. J Heart Lung Transplant. 2010;29:914–956.
      25. Ormonde DG, de Boer WB, Kierath A, et al. Banff schema for grading liver allograft rejection: utility in clinical practice. Liver Transpl Surg. 1999;5:261–268.
        26. Stewart S, Fishbein MC, Snell GI, et al. Revision of the 1996 working formulation for the standardization of nomenclature in the diagnosis of lung rejection. J Heart Lung Transplant. 2007;26:1229–1242.
          27. Schwartz GJ, Work DF. Measurement and estimation of GFR in children and adolescents. J Am Soc Nephrol. 2009;4:1832–1643.
            28. Kangro HO, Osman HK, Lau YL, et al. Seroprevalence of antibodies to human herpesviruses in England and Hong Kong. J Med Virol. 1994;43:91–96.
            29. Jeong HJ, Ahn YH, Park E, et al. Posttransplantation lymphoproliferative disorder after pediatric solid organ transplantation: experiences of 20 years in a single center. Korean J Pediatr. 2017;60:86–93.
            30. Barton M, Wasfy S, Hebert D, et al. Exploring beyond viral load testing for EBV lymphoproliferation: role of serum il-6 and IgE assays as adjunctive tests. Pediatr Transplant. 2010;14:852–858.
            31. Allen UD, Farkas G, Hebert D, et al. Risk factors for post-transplant lymphoproliferative disorder in pediatric patients: a case-control study. Pediatr Transplant. 2005;9:450–455.
            32. Chang CM, Yu KJ, Mbulaiteye SM, et al. The extent of genetic diversity of Epstein-Barr virus and its geographic and disease patterns: a need for reappraisal. Virus Res. 2009;143:209–221.
            33. Simons LE, Blount RL. Identifying barriers to medication adherence in adolescent transplant recipients. J Pediatr Psychol. 2007;32:831–844.
            34. C.D.A. The spectrum of adherence among hemodialysis patients. J Nephrol Soc Work. 1998;18:53–65.
            35. De Geest S, Sabate E. Adherence to long-term therapies: evidence for action. Eur J Cardiovasc Nurs. 2003;2:323.
            36. Berben L, Dobbels F, Engberg S, et al. An ecological perspective on medication adherence. West J Nurs Res. 2012;34:635–653.
            37. Held PJ, Kahan BD, Hunsicker LG, et al. The impact of HLA mismatches on the survival of first cadaveric kidney transplants. N Engl J Med. 1994;331:765–770.
            38. Pai AL, Rausch J, Tackett A, et al. System for integrated adherence monitoring: real-time non-adherence risk assessment in pediatric kidney transplantation. Pediatr Transplant. 2012;16:329–334.
            39. Shemesh E, Shneider BL, Savitzky JK, et al. Medication adherence in pediatric and adolescent liver transplant recipients. Pediatrics. 2004;113:825–832.
            40. Shemesh E, Annunziato RA, Shneider BL, et al. Improving adherence to medications in pediatric liver transplant recipients. Pediatr Transplant. 2008;12:316–323.
            41. Schafer-Keller P, Steiger J, Bock A, et al. Diagnostic accuracy of measurement methods to assess non-adherence to immunosuppressive drugs in kidney transplant recipients. Am J Transplant. 2008;8:616–626.
            42. Miloh T, Annunziato R, Arnon R, et al. Improved adherence and outcomes for pediatric liver transplant recipients by using text messaging. Pediatrics. 2009;124:e844–e850.
            43. Birdwell KA, Decker B, Barbarino JM, et al. Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for cyp3a5 genotype and tacrolimus dosing. Clin Pharmacol Ther. 2015;98:19–24.
            44. Min S, Daljevic T, Lee O, et al. Variability in tacrolimus concentrations across pediatric solid organ transplants. Am J Transplant. 2017;17(suppl 3).
            45. Min S, Papaz T, Blydt-Hansen T, et al. Genome-wide association study of tacrolimus dose in pediatric solid organ transplant recipients in the CNTRP positive study. Am J Transplant. 2017;17(suppl 3).
            46. Papaz T, Min S, Lee O, et al. Genome-wide association study assessing risk of rejection in pediatric transplant recipients. Am J Transplant. 2017;17(suppl 3).
            47. Urschel S, Ionescu L, Blydt-Hansen T, et al. Immune phenotyping in a pediatric multicenter transplant study: suitability of a pre-formulated dry antibody panel system. Am J Transplant. 2017;17(suppl 3).
            48. Ionescu L, Blydt-Hansen T, Foster B, et al. The impact of childhood solid organ transplantation on b-cell maturation. Am J Transplant. 2017;17(suppl 3).
            © 2018 The Authors. Published by Wolters Kluwer Health, Inc.