Letters to the Editor
* 2014 Lippincott Williams & Wilkins
6. 7.
Chapman JR, Webster AC, Wong G. Cancer in the transplant recipient. Cold Spring Harb Perspect Med 2013;3: a015677. Taeger D, Sun Y, Keil U, et al. A stand-alone windows applications for computing exact
8.
person-years, standardized mortality ratios and confidence intervals in epidemiological studies. Epidemiology 2000; 11: 607. Mohammadi S, Silvaggio G, Bonnet N, et al. Prostate cancer after heart transplantation:
e73
unicenter case-control study. J Heart Lung Transplant 2005; 24: 995. Engels EA, Pfeiffer RM, Fraumeni JF Jr, et al. Spectrum of cancer risk among US solid organ transplant recipients. JAMA 2011; 306: 1891.
9.
Medication Regimen Complexity in Kidney and Liver Transplant Recipients rgan transplantation is the optimal and most cost-effective treatment for patients with end-stage renal and liver disease. To maintain long-term graft function, patients must take lifelong immunosuppression in addition to multidrug regimens to manage comorbid conditions. Previous studies show that the prevalence of nonadherence in solid organ transplant recipients is about 23 cases per 100 patients per year across organ types (1). Immunosuppression nonadherence is associated with posttransplant complications including graft rejection, graft loss, and increased medical costs (2). Medication regimen complexity is one of the major determinants of medication nonadherence in the general chronic disease population (3). Although data in transplantation are limited, regimen complexity is likely to be high because of multidrug regimens and frequent medication and dosing changes. The Medication Regimen Complexity Index (MRCI) is a validated tool to quantify medication complexity beyond the number of drugs a patient is taking (4). The MRCI accounts for the number of medications, number of daily doses, dosing form (e.g., tablet vs. injection), frequency, and specific instructions such as ‘‘take with food’’ (5). The
O
MRCI can be a useful clinical tool in transplantation to identify patients at risk for overcomplicating regimens, medication errors, and nonadherence, which increase the risk of negative health outcomes. Previous research has quantified disease-specific MRCI for geriatric depression (M = 3.0 [standard deviation {SD}=1.1], diabetes (M = 6.3 [SD = 3.1]), HIV (M = 4.9 [SD = 2.1]), and hypertension (M = 3.5 [SD = 1.5]) (see Fig. 1) (4). The MRCI has not been previously quantified in a transplant population. Using data from a cross-sectional study at two large transplant centers in Chicago, IL, and Atlanta, GA, we report MRCI scores for a sample of kidney and liver transplant recipients. A total of 204 (kidney n = 99; liver n = 105) patients were recruited. Each medication was initially identified as ‘‘transplant-related’’ or ‘‘other’’ (e.g., for a comorbidity). The average transplant-related MRCI score for our sample was 18.0 (SD = 8.5), with patients taking on average 8.5 (SD = 3.7) transplant-specific medications. Transplantrelated MRCI scores did not vary by organ type (kidney: M = 17.9 [SD = 8.1]; liver: M = 18.1 [SD = 8.8] (P = 0.84) or time since transplantation (e12 months: M = 19.1 [SD = 8.0]; 912 months: M = 17.4 [SD = 8.6], (P = 0.18).
These data are the first to quantify medication regimen complexity in kidney and liver transplant patients. Our data support the generally accepted notion that medication regimen complexity is high in transplantation because of the presence of multiple transplant-specific medications and others needed to manage chronic disease. The MRCI may be a useful tool to quantify complexity beyond just the number of medications a transplant recipient may be taking because it accounts for other factors, such as frequency and route of administration. Further studies should validate the MRCI among a larger cohort of transplant recipients and investigate the association between MRCI, medication adherence, and transplant-specific outcomes. Strategies aimed at reducing treatment complexity by consolidating regimens, synchronizing medication refills, and providing patients with reminders may be effective at improving posttransplant adherence and clinical outcomes.
Przytula Kamila1 Samuel G. Smith1 Rachel Patzer2 Michael S. Wolf1 Serper Marina3 1
FIGURE 1. Disease-specific MRCI score. MRCI, Medication Regimen Complexity Index.
Health Literacy and Learning Program Division of General Internal Medicine Northwestern University Chicago, IL 2 Division of Transplantation Department of Surgery Emory University Atlanta, GA 3 Division of Gastroenterology and Hepatology University of Pennsylvania Philadelphia, PA
Project was funded by Award Number T32DK077662 from the National Institute of Diabetes and Digestive and Kidney Diseases.
Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
e74
www.transplantjournal.com
The authors declare no conflicts of interest. Address correspondence to: Marina Serper, M.D., Hospital of the University of Pennsylvania, 3400 Spruce St, 2 Dulles, Philadelphia, PA 19104. E-mail: [email protected] Received 7 July 2014. Accepted 10 July 2014. Copyright * 2014 by Lippincott Williams & Wilkins ISSN: 0041-1337/14/9807-e73 DOI: 10.1097/TP.0000000000000403
Transplantation
& Volume 98, Number 7, October 15, 2014
REFERENCES 1.
2.
Dew MA, et al. Rates and risk factors for nonadherence to the medical regimen after adult solid organ transplantation. Transplantation 2007; 83: 858. Chisholm-Burns MA, et al. Immunosuppressant therapy adherence and graft failure among pediatric renal transplant recipients. Am J Transplant 2009; 9: 2497.
3.
4. 5.
Ingersoll KS, Cohen J. The impact of medication regimen factors on adherence to chronic treatment: a review of literature. J Behav Med 2008; 31: 213. Libby AM, et al. Patient-level medication regimen complexity across populations with chronic disease. Clin Ther 2013; 35: 385. George J, et al. Development and validation of the medication regimen complexity index. Ann Pharmacother 2004; 38: 1369.
Belatacept Maintenance in a Heart Transplant Recipient elatacept is a selective T-cell costimulation blocker indicated for prophylaxis of organ rejection in EpsteinBarr virus seropositive kidney transplant recipients 1Y3. Published reports have described use in liver and islet cell transplant recipients 4, 5. Currently, there is no published information on the use of belatacept in heart transplant recipients. We describe the case of a heart transplant recipient who received belatacept in addition to traditional maintenance immunosuppressive therapy.
B
CASE A 26-year-old female with postpartum cardiomyopathy received an orthotopic heart transplantation on July 2011. She received rabbit antithymocyte globulin (rATG) induction and was initiated on tacrolimus, mycophenolate mofetil, and prednisone. Her tacrolimus trough levels were erratic and many times below the level of detection, so there were major concerns about her compliance with her immunosuppressive medications. The patient had multiple episodes of mild and moderate rejections, persistent International Society for Heart and Lung Transplantation
grade 1R, starting from the 4-week biopsy after transplantation. On November 2011, the patient had severe grade 3R rejection with left ventricular ejection fraction decreasing to 29%. She was treated with rATG, high-dose methylprednisolone, addition of sirolimus, and two photopheresis treatments, resulting in improved left ventricular systolic function. On December 2011, the patient received methylprednisolone and rATG for the treatment of grade 3R rejection. On July 2012, the patient was readmitted for grade 3R rejection and antibody-mediated rejection with hemodynamic compromise. She received plasmapheresis for 5 days and alemtuzumab. On October 2012, she developed grade 3R rejection with low tacrolimus and sirolimus levels and was treated with methylprednisolone for 3 days. Followup biopsy was grade 1R 2 weeks later. On January 2013, she developed grade 3R rejection with acceptable tacrolimus and sirolimus levels and was treated with methylprednisolone. On February 2013, she was admitted again for grade 3R rejection with low levels of tacrolimus and was treated with high-dose methylprednisolone.
Tacrolimus target levels were 8 to 12 ng/mL for the first 6 months after transplantation, with target levels of 6 to 8 ng/mL thereafter. Sirolimus target levels were 4 to 6 ng/mL throughout the whole posttransplant period. From July 2011 through mid-March 2013, a total of 89 tacrolimus levels were taken; of ‘those, 37% were subtherapeutic or below the level of detection. Similarly, a total of 55 sirolimus levels were taken during this period, and 47% of those were subtherapeutic or below the level of detection. The patient developed human leukocyte antigen classes I and II donorspecific antibodies (DSA) and non-DSA by Luminex single antigen bead testing as well as virtual cross-match, which remained persistently positive after transplantation. All of her complement-dependent cytotoxicity (CDC) panel-reactive antibody assays for complement-fixing antibody were negative. She developed positive C4d binding in her biopsies beginning in July 2012 despite having a normal ejection fraction. In November 2011, C4dj, CDC 0, single antigen beadYpanel reactive antibody (SAB-PRA) 79%, and +DSA+nonDSA. In December 2011, C4dj, CDC 0, and SAB-PRA 86%. In July 2012, C4d+,
FIGURE 1. Date of transplant, belatacept initiation, death, and ISHLT 2004 grade 3R rejection episodes and dates are shown along the timeline. ISHLT 2004 grade 1R rejection episodes and grade 0 are marked with a short line. ISHLT, International Society for Heart and Lung Transplantation; EF, ejection fraction.
Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
* 2014 Lippincott Williams & Wilkins
6. 7.
Chapman JR, Webster AC, Wong G. Cancer in the transplant recipient. Cold Spring Harb Perspect Med 2013;3: a015677. Taeger D, Sun Y, Keil U, et al. A stand-alone windows applications for computing exact
8.
person-years, standardized mortality ratios and confidence intervals in epidemiological studies. Epidemiology 2000; 11: 607. Mohammadi S, Silvaggio G, Bonnet N, et al. Prostate cancer after heart transplantation:
e73
unicenter case-control study. J Heart Lung Transplant 2005; 24: 995. Engels EA, Pfeiffer RM, Fraumeni JF Jr, et al. Spectrum of cancer risk among US solid organ transplant recipients. JAMA 2011; 306: 1891.
9.
Medication Regimen Complexity in Kidney and Liver Transplant Recipients rgan transplantation is the optimal and most cost-effective treatment for patients with end-stage renal and liver disease. To maintain long-term graft function, patients must take lifelong immunosuppression in addition to multidrug regimens to manage comorbid conditions. Previous studies show that the prevalence of nonadherence in solid organ transplant recipients is about 23 cases per 100 patients per year across organ types (1). Immunosuppression nonadherence is associated with posttransplant complications including graft rejection, graft loss, and increased medical costs (2). Medication regimen complexity is one of the major determinants of medication nonadherence in the general chronic disease population (3). Although data in transplantation are limited, regimen complexity is likely to be high because of multidrug regimens and frequent medication and dosing changes. The Medication Regimen Complexity Index (MRCI) is a validated tool to quantify medication complexity beyond the number of drugs a patient is taking (4). The MRCI accounts for the number of medications, number of daily doses, dosing form (e.g., tablet vs. injection), frequency, and specific instructions such as ‘‘take with food’’ (5). The
O
MRCI can be a useful clinical tool in transplantation to identify patients at risk for overcomplicating regimens, medication errors, and nonadherence, which increase the risk of negative health outcomes. Previous research has quantified disease-specific MRCI for geriatric depression (M = 3.0 [standard deviation {SD}=1.1], diabetes (M = 6.3 [SD = 3.1]), HIV (M = 4.9 [SD = 2.1]), and hypertension (M = 3.5 [SD = 1.5]) (see Fig. 1) (4). The MRCI has not been previously quantified in a transplant population. Using data from a cross-sectional study at two large transplant centers in Chicago, IL, and Atlanta, GA, we report MRCI scores for a sample of kidney and liver transplant recipients. A total of 204 (kidney n = 99; liver n = 105) patients were recruited. Each medication was initially identified as ‘‘transplant-related’’ or ‘‘other’’ (e.g., for a comorbidity). The average transplant-related MRCI score for our sample was 18.0 (SD = 8.5), with patients taking on average 8.5 (SD = 3.7) transplant-specific medications. Transplantrelated MRCI scores did not vary by organ type (kidney: M = 17.9 [SD = 8.1]; liver: M = 18.1 [SD = 8.8] (P = 0.84) or time since transplantation (e12 months: M = 19.1 [SD = 8.0]; 912 months: M = 17.4 [SD = 8.6], (P = 0.18).
These data are the first to quantify medication regimen complexity in kidney and liver transplant patients. Our data support the generally accepted notion that medication regimen complexity is high in transplantation because of the presence of multiple transplant-specific medications and others needed to manage chronic disease. The MRCI may be a useful tool to quantify complexity beyond just the number of medications a transplant recipient may be taking because it accounts for other factors, such as frequency and route of administration. Further studies should validate the MRCI among a larger cohort of transplant recipients and investigate the association between MRCI, medication adherence, and transplant-specific outcomes. Strategies aimed at reducing treatment complexity by consolidating regimens, synchronizing medication refills, and providing patients with reminders may be effective at improving posttransplant adherence and clinical outcomes.
Przytula Kamila1 Samuel G. Smith1 Rachel Patzer2 Michael S. Wolf1 Serper Marina3 1
FIGURE 1. Disease-specific MRCI score. MRCI, Medication Regimen Complexity Index.
Health Literacy and Learning Program Division of General Internal Medicine Northwestern University Chicago, IL 2 Division of Transplantation Department of Surgery Emory University Atlanta, GA 3 Division of Gastroenterology and Hepatology University of Pennsylvania Philadelphia, PA
Project was funded by Award Number T32DK077662 from the National Institute of Diabetes and Digestive and Kidney Diseases.
Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
e74
www.transplantjournal.com
The authors declare no conflicts of interest. Address correspondence to: Marina Serper, M.D., Hospital of the University of Pennsylvania, 3400 Spruce St, 2 Dulles, Philadelphia, PA 19104. E-mail: [email protected] Received 7 July 2014. Accepted 10 July 2014. Copyright * 2014 by Lippincott Williams & Wilkins ISSN: 0041-1337/14/9807-e73 DOI: 10.1097/TP.0000000000000403
Transplantation
& Volume 98, Number 7, October 15, 2014
REFERENCES 1.
2.
Dew MA, et al. Rates and risk factors for nonadherence to the medical regimen after adult solid organ transplantation. Transplantation 2007; 83: 858. Chisholm-Burns MA, et al. Immunosuppressant therapy adherence and graft failure among pediatric renal transplant recipients. Am J Transplant 2009; 9: 2497.
3.
4. 5.
Ingersoll KS, Cohen J. The impact of medication regimen factors on adherence to chronic treatment: a review of literature. J Behav Med 2008; 31: 213. Libby AM, et al. Patient-level medication regimen complexity across populations with chronic disease. Clin Ther 2013; 35: 385. George J, et al. Development and validation of the medication regimen complexity index. Ann Pharmacother 2004; 38: 1369.
Belatacept Maintenance in a Heart Transplant Recipient elatacept is a selective T-cell costimulation blocker indicated for prophylaxis of organ rejection in EpsteinBarr virus seropositive kidney transplant recipients 1Y3. Published reports have described use in liver and islet cell transplant recipients 4, 5. Currently, there is no published information on the use of belatacept in heart transplant recipients. We describe the case of a heart transplant recipient who received belatacept in addition to traditional maintenance immunosuppressive therapy.
B
CASE A 26-year-old female with postpartum cardiomyopathy received an orthotopic heart transplantation on July 2011. She received rabbit antithymocyte globulin (rATG) induction and was initiated on tacrolimus, mycophenolate mofetil, and prednisone. Her tacrolimus trough levels were erratic and many times below the level of detection, so there were major concerns about her compliance with her immunosuppressive medications. The patient had multiple episodes of mild and moderate rejections, persistent International Society for Heart and Lung Transplantation
grade 1R, starting from the 4-week biopsy after transplantation. On November 2011, the patient had severe grade 3R rejection with left ventricular ejection fraction decreasing to 29%. She was treated with rATG, high-dose methylprednisolone, addition of sirolimus, and two photopheresis treatments, resulting in improved left ventricular systolic function. On December 2011, the patient received methylprednisolone and rATG for the treatment of grade 3R rejection. On July 2012, the patient was readmitted for grade 3R rejection and antibody-mediated rejection with hemodynamic compromise. She received plasmapheresis for 5 days and alemtuzumab. On October 2012, she developed grade 3R rejection with low tacrolimus and sirolimus levels and was treated with methylprednisolone for 3 days. Followup biopsy was grade 1R 2 weeks later. On January 2013, she developed grade 3R rejection with acceptable tacrolimus and sirolimus levels and was treated with methylprednisolone. On February 2013, she was admitted again for grade 3R rejection with low levels of tacrolimus and was treated with high-dose methylprednisolone.
Tacrolimus target levels were 8 to 12 ng/mL for the first 6 months after transplantation, with target levels of 6 to 8 ng/mL thereafter. Sirolimus target levels were 4 to 6 ng/mL throughout the whole posttransplant period. From July 2011 through mid-March 2013, a total of 89 tacrolimus levels were taken; of ‘those, 37% were subtherapeutic or below the level of detection. Similarly, a total of 55 sirolimus levels were taken during this period, and 47% of those were subtherapeutic or below the level of detection. The patient developed human leukocyte antigen classes I and II donorspecific antibodies (DSA) and non-DSA by Luminex single antigen bead testing as well as virtual cross-match, which remained persistently positive after transplantation. All of her complement-dependent cytotoxicity (CDC) panel-reactive antibody assays for complement-fixing antibody were negative. She developed positive C4d binding in her biopsies beginning in July 2012 despite having a normal ejection fraction. In November 2011, C4dj, CDC 0, single antigen beadYpanel reactive antibody (SAB-PRA) 79%, and +DSA+nonDSA. In December 2011, C4dj, CDC 0, and SAB-PRA 86%. In July 2012, C4d+,
FIGURE 1. Date of transplant, belatacept initiation, death, and ISHLT 2004 grade 3R rejection episodes and dates are shown along the timeline. ISHLT 2004 grade 1R rejection episodes and grade 0 are marked with a short line. ISHLT, International Society for Heart and Lung Transplantation; EF, ejection fraction.
Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
