Non-adherence to immunosuppressants in organ transplant patients
- Non-adherence to medication remains a barrier to long-term graft survival in the life of solid organ transplant patients1,2.
- The major risk factors for non-adherence include income, complex regimen, employment status, minority race, illness perception, and mental health2,3.
- Multicomponent interventions tailored to the need of patients appear to be most effective in lowering non-adherence to immunosuppressants4.
Every year about 1,29,681 organs are transplanted worldwide (Source: Global observatory on donation and transplantation)5 adding approximately ~12 years (median survival time) to the recipient’s life as compared to 5.4 years of median survival time for patients on the waitlist6. Due to the rising demand, medical science is also exploring the option of heterografts from other mammals similar to humans. For all such solid organ transplant recipients, immunosuppressants are the ‘magic pills’ that are prerequisites for the survival of the graft after transplantation. Adherence to anti-rejection medicines is vital in the life of organ transplant recipients1,2,7.
Medication adherence is the key determining factor of treatment success. The journey of a patient from total adherence to nonadherence is multifactorial. The World Health Organization recognizes adherence as a multidimensional phenomenon governed by the interplay of five dimensions. These dimensions include sociodemographic, patient-related, disease-related, therapy-related, and healthcare system-related components8. Factors related to transplant treatment, patients’ psychosocial, and the healthcare system are the major challenges for non-adherence towards prescribed immunotherapies in organ transplant patients3.
Non-adherence in post-transplant patients
Immunosuppressives are the nuts and bolts for long-term graft survival in solid organ transplant patients. They shield the grafted organ from the recipient’s immune system, which could manifest as late rejection. Non-adherence to immunosuppressants triggers an increase in cell-mediated and/or antibody-mediated rejection7
Considering the crucial role of immunosuppressives post-transplant, it is astonishing to note an increase in non-adherence in this patient group1. The highest rate of nonadherence for immunosuppressants is reportedly in the kidney transplant recipients averaging 36–55%, while that in adult heart and liver transplant recipients is 34.1–41.1% and 15–40%, respectively2. The disturbing figures raise many questions, chief among them is “What causes nonadherence among the transplant receivers?”, “What are the risk factors for non-adherence in transplant patients?” and “How best to mitigate them?”
The nature of the adherence required for immunosuppressants in solid organ transplants differs from other therapies. Primarily, the medication is prescribed for lifelong without much room for error in dosage to protect the transplanted organ from being rejected. The rate of adherence expected for immunosuppressants is usually very high (>95-100%.) as compared to other medicines (85%) deemed to be essential in non-transplant patients8.
Even with a reasonable understanding of the necessity of the medication for averting graft rejection, patients fail to adhere to the prescription. The major factors that fuel non-adherence in transplant recipients are:
- History of non-adherence- The elephant in the room: Patients with a past of non-adherence to prescribed therapy and clinical visits are recognized as a major determinant for non-adherence to post-transplant medication. As old habits are formed through a lifetime of experiences that patients were exposed to, they are difficult to shake off7.
- Apprehensions about adverse effects: Apprehensions about lifelong lowering of immunity that could result in a higher risk of infectious diseases are common in transplant patients. Additionally, a fear of side effects, difficulty in gaining self-control post-transplantation, and concerns about overmedicalized life also contribute to nonadherent behavior7.
- Socio-demographic factors: Age, gender, marital and employment status, ethnicity, and level of education are other driving forces toward patients’ deliberate refusal to comply with the treatment protocol3.
- Other attributes include psychological factors (patient’s beliefs, social support, and expectation of cure), healthcare-related factors (medication costs, poor access to medications, long treatment duration), and therapy-related factor (complex medication regimen, comorbidities)1,3.
Measuring Adherence: Qualitative and Quantitative Tools
To mitigate the effects of non-adherence, modifiable stakes need to be addressed through targeted interventions. For this, it is imperative to identify the non-adherent behavior and measure them. A combination of multiple strategies from the pre-transplant to post-transplant phase is employed in clinical practice to monitor adherence. These strategies include both direct and indirect measures as mentioned in Table 1 along with their specific advantages and limitations9,10.
Table 1: Methods of measurement to assess nonadherence in organ transplant patients
|– History of compliance to therapy and scheduled visits to the clinics|
– Renal replacement therapy (dialysis sessions)
– Maintenance of medication
– Socioeconomic, cultural, educational, motivational, and emotional assessment
|Provides valuable information with respect to the potential barriers to adherence and past non-adherence|
|Post-transplant: Direct measures|
|Medication intake observation||– Verifies adherence|
– High reliability
|– Requires direct patient-clinician encounters |
– Non-feasible approach to monitoring chronic treatments
– Loss of independence
|Structured interviews||Effective communicative strategy to capture nonadherence||Can underestimate intentional nonadherence|
|Monitoring of drug levels in the blood/urine (Tac level)||– Verifies adherence|
– Easily available at local diagnostic labs and transplant centers
|Results can be influenced by the half-life of drugs, metabolic rates, and white coat adherence (i.e., greater adherence before a clinical visit)|
|Patient self-reports||– Do not obviate the need to communicate with recipients|
– Easy to implement
|Can be biased or tapered|
|Medication refills (medication prescriptions)||Reliable as the data is claimed from insurance companies and pharmacies||Maybe hampered due to uncaptured periods of hospitalization, regular ambulant dose changes, or switching between immunosuppressive drugs|
|Pill counts||– Easy to implement|
– Cost effective
|Can be biased or tapered by the subject|
|Electronic monitoring of nonadherence (MEMS, medication bottles with a microchip-embedded cap)||Provides insights into the pattern of adherence||– Expensive in regular practice|
– Discarded or hoarded doses?
Recent systemic reviews have reported that no single method of adherence assessment is optimum. A multidimensional approach combining subjective and objective measures appears to be effective in the measurement of adherence behavior2,11.
Current status of interventions to improve adherence post-transplant
Several interventions have been employed over the years to improve adherence in transplant recipients. Interventions targeting behavioral changes and health literacy have reported some improvement in adherence rates in transplant recipients4,12. A pilot study that used electronic monitoring to assess non-adherence and provided appropriate counseling for motivation through home visits and telemedicine reported better adherence, although it was not statistically significant13.
A paradigm shift in approach came with the MAGIC (medication adherence given individual SystemCHANGE)study conducted in 201614. Based on the socioecological model at its core, it focused on changing the individual’s environment to change their behavior. The study identified the support system in the patient’s environment that can influence medication intake. It provided appropriate solutions while continuously monitoring adherence data and evaluating them. This was in contrast with the conventional methods of increasing individuals’ motivation and intentions14. The study reported a very significant improvement in patient’s adherence behavior as compared to the control group (difference in medians 0.17, 95% CI 0.06-0.33, P = 0.004)15.
A few ongoing studies like TAKE IT (Transplant Regimen Adherence for Kidney recipients by Engaging Information Technologies) are relying heavily on digital approaches to reduce non-adherence. Specifically, it uses a web-based patient portal along with electronic health records to help educate patients and assist them in scheduling their daily prescriptions. The study also monitored the patient’s medication usage electronically and alerted respective healthcare providers upon detecting non-adherence behavior. This allows for the medical staff to mobilize appropriate care and provide a tailored response to patients’ concerns16.
With the change in time and improvement in technology, our understanding of non-adherence and the behavior that fuels it has improved dramatically. Therefore the interventions targeting it are also improving. In comparison to the socioecological model of the MAGIC study, the TAKE IT trial employs the use of technology to improve adherence. Rightfully so, since nonadherence is a multifaceted problem, the interventions remedying it should be multifactorial too4.
Measuring and addressing nonadherence is challenging, despite being a major threat to long-term graft survival. However, the identification of risk factors may be helpful in early detection and intervention to lower the incidence of non-adherence.The first step to prevent non-adherence begins during the pre-transplant phase. Educational counseling and an encouraging support network for the patient is the foundation for thwarting non-adherence2. Among the many interventions to prevent the course of total adherence to non-adherence, a tailored approach may be more consequential. The use of smartphone apps, pill reminders, and simplified medicine regime based on the patient’s needs, motivation, and specific barriers rather than ‘one size fit all’ approach is the need of the hour to prevent medication nonadherence3. Identifying high-risk patients that could be non-adherent based on prediction models recently proposed could provide a basis for the development of improved measures17.
1. Ng YH, Litvinovich I, Leyva Y, et al. Medication, Healthcare Follow-up, and Lifestyle Nonadherence: Do They Share the Same Risk Factors? Transplant Direct. Jan 2022;8(1):e1256. doi:10.1097/TXD.0000000000001256
2. Shi YX, Liu CX, Liu F, et al. Efficacy of Adherence-Enhancing Interventions for Immunosuppressive Therapy in Solid Organ Transplant Recipients: A Systematic Review and Meta-Analysis Based on Randomized Controlled Trials. Front Pharmacol. 2020;11:578887. doi:10.3389/fphar.2020.578887
3. Zhang M, Zhou H, Nelson RS, et al. Prevalence and Risk Factors of Immunosuppressant Nonadherence in Heart Transplant Recipients: A Single-Center Cross-Sectional Study. Patient Prefer Adherence. 2019;13:2185-2193. doi:10.2147/PPA.S223837
4. De Bleser L, Matteson M, Dobbels F, Russell C, De Geest S. Interventions to improve medication-adherence after transplantation: a systematic review. Transpl Int. Aug 2009;22(8):780-97. doi:10.1111/j.1432-2277.2009.00881.x
5. Global observatory on donation and organ transplant. Global report on organ donation and transplantation 2020. 2020; 1-89
6. Rana A, Godfrey EL. Outcomes in Solid-Organ Transplantation: Success and Stagnation. Tex Heart Inst J. Feb 2019;46(1):75-76. doi:10.14503/THIJ-18-6749
7. Nevins TE, Nickerson PW, Dew MA. Understanding Medication Nonadherence after Kidney Transplant. J Am Soc Nephrol. Aug 2017;28(8):2290-2301. doi:10.1681/ASN.2017020216
8. Alvi Y, Khalique N, Ahmad A, Khan HS, Faizi N. World Health Organization Dimensions of Adherence to Antiretroviral Therapy: A Study at Antiretroviral Therapy Centre, Aligarh. Indian J Community Med. Apr-Jun 2019;44(2):118-124. doi:10.4103/ijcm.IJCM_164_18
9. Moreso FT, I.B.; Costa, G.; Serón, D. Nonadherence to immunosuppression: challenges and solutions. Transplant Research and Risk Management. 2015;7:27-34. doi:https://doi.org/10.2147/TRRM.S50796
10. Gandolfini I, Palmisano A, Fiaccadori E, Cravedi P, Maggiore U. Detecting, preventing and treating non-adherence to immunosuppression after kidney transplantation. Clin Kidney J. Jul 2022;15(7):1253-1274. doi:10.1093/ckj/sfac017
11. Kostalova B, Ribaut J, Dobbels F, et al. Medication adherence interventions in transplantation lack information on how to implement findings from randomized controlled trials in real-world settings: A systematic review. Transplant Rev (Orlando). Jan 2022;36(1):100671. doi:10.1016/j.trre.2021.100671
12. Chisholm-Burns MA, Spivey CA, Pickett LR. Health literacy in solid-organ transplantation: a model to improve understanding. Patient Prefer Adherence. 2018;12:2325-2338. doi:10.2147/PPA.S183092
13. De Geest S, Schafer-Keller P, Denhaerynck K, et al. Supporting medication adherence in renal transplantation (SMART): a pilot RCT to improve adherence to immunosuppressive regimens. Clin Transplant. May-Jun 2006;20(3):359-68. doi:10.1111/j.1399-0012.2006.00493.x
14. Russell CL, Moore S, Hathaway D, Cheng AL, Chen G, Goggin K. MAGIC Study: Aims, Design and Methods using SystemCHANGE to Improve Immunosuppressive Medication Adherence in Adult Kidney Transplant Recipients. BMC Nephrol. Jul 16 2016;17(1):84. doi:10.1186/s12882-016-0285-8
15. Russell CL, Hathaway D, Remy LM, et al. Improving medication adherence and outcomes in adult kidney transplant patients using a personal systems approach: SystemCHANGE results of the MAGIC randomized clinical trial. Am J Transplant. Jan 2020;20(1):125-136. doi:10.1111/ajt.15528
16. Yoon ES, Hur S, Curtis LM, et al. A Multifaceted Intervention to Improve Medication Adherence in Kidney Transplant Recipients: An Exploratory Analysis of the Fidelity of the TAKE IT Trial. JMIR Form Res. May 5 2022;6(5):e27277. doi:10.2196/27277
17. Zhu X, Peng B, Yi Q, Liu J, Yan J. Corrigendum: Prediction model of immunosuppressive medication non-adherence for renal transplant patients based on machine learning technology. Front Med (Lausanne). 2022;9:964157. doi:10.3389/fmed.2022.964157