Evaluation of Medication Adherence Over a Decade Following Kidney Transplantation: Integration of Biological and Self-Reported Data

Evaluation of Medication Adherence Over a Decade Following Kidney Transplantation: Integration of Biological and Self-Reported Data | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluation of Medication Adherence Over a Decade Following Kidney Transplantation: Integration of Biological and Self-Reported Data Yaprak Sarıgöl Ordin, Serap Arıcan, Büşra Selma Saha, Hale Turhan Damar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8419420/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Background This study aims to determine the course of immunosuppressive medication adherence (MA) in individuals who have undergone kidney transplantation for over a decade and to identify the demographic and clinical factors affecting this adherence. Methods This retrospective and cross-sectional descriptive study evaluated the biological adherence of 103 kidney transplant recipients (KTRs) at 12 different time points using tacrolimus and cyclosporine blood levels. Self-reported adherence was assessed via the immunosuppresive therapy adherence. Associations between adherence and demographic and clinical variables were also analyzed. Results The mean time since transplantation was 11.77 ± 1.46 years. Biologically, 43.3% of patients had low MA. In contrast, self-reported adherence was 82.52%. No statistically significant correlation was found between biological and self-reported adherence outcomes. Patients with low biological adherence presented increased blood urea nitrogen (BUN) levels at 6 months and 9 years post-transplant. Similarly, patients with low self-reported adherence had increased BUN levels at 10 years. Self-reported adherence scores were significantly lower among patients with a history of graft rejection (p 0.05). Conclusions Immunosuppressive MA in KTRs may fluctuate over time, and varies according to the assessment method. The combined and time-consuming use of biological and self-reported measurements may contribute to a more accurate determination of the risk of non-adherence. Individualized follow-up and support programs should be developed, taking into account the multidimensional factors that influence adherence. biological monitoring follow-up studies kidney transplantation immunosuppressive agents medication adherence self report Figures Figure 1 Figure 2 Background Sufficient immunosuppression is essential for both short- and long-term survival following organ transplantation. Accordingly, adherence to immunosuppressive therapy is critical for preventing organ rejection, graft loss, and posttransplant mortality 1 – 3 . Nonadherence to immunosuppressive medication has been linked to approximately 16% of early graft losses and 20% of antibody-mediated rejections 4 . The prevalence of medication adherence (MA) among kidney transplant recipients (KTRs) varies widely, with a systematic review reporting rates between 36% and 55% 5 , whereas a scoping review revealed an even broader range, from 2% to 89% 6 . Several factors have been associated with nonadherence, including younger age, male sex, low social support, unemployment, lower educational attainment, longer time since transplantation, sirolimus-based therapy, living donor transplantation, high chronic disease burden, polypharmacy, and a history of depression 7 , 8 . Early identification of recipients with these risk factors and the implementation of close, individualized monitoring are critical strategies for improving adherence and ensuring long-term graft survival. Regular assessment of treatment adherence is necessary to ensure that immunosuppressive therapy can be continued safely and effectively. The most commonly used direct method in clinical practice is the measurement of therapeutic drug levels; however, this method reflects only short-term adherence. Indirect methods include patient self-assessment forms, patient diaries, prescription refill records, and electronic medication monitoring technologies 9 . A single adherence assessment method is not sufficient for accurately measuring adherence behavior. Therefore, combining multiple methods and repeated assessments ensures more accurate and reliable results 9 – 11 . In addition, MA is a dynamic process that may vary over time after transplantation 12 . The literature presents conflicting findings on this issue: some studies have shown that adherence decreases over the long term 13 , whereas others have shown that early adherence behavior continues in later periods 14 . On the other hand, some findings report an increase in adaptation between the 3rd and 5th years 15 . These differences highlight the need for an assessment approach that spans time. Kidney transplantation is a highly effective treatment modality that significantly enhances long-term survival in patients with end-stage renal disease. As the number of transplant recipients continues to rise, evaluating long-term MA and identifying the factors that influence it have become increasingly important. Immunosuppressive therapy is essential for maintaining graft function and preventing rejection, yet adherence to these medications can decline over time due to various demographic, clinical, and psychosocial factors. In this context, the present study aims to explore the trajectory of immunosuppressive MA among individuals who have been living with a kidney transplant for 10 years or longer and to identify the demographic and clinical variables that may influence this adherence. Methods Study design and patient population This study was conducted with a retrospective, cross-sectional, descriptive research design. This study was conducted in the kidney transplantation unit of a training and research hospital. The data were collected between June 2023 and July 2024. The study sample consisted of KTRs who had undergone transplantation at least 10 years prior. The inclusion criteria were being willing to participate in the study, being 18 years of age or older, having undergone only kidney transplantation, and being able to speak and understand Turkish. At the time of data collection, 301 KTRs were under follow-up. Among them, 103 patients had undergone kidney transplantation at least 10 years earlier and met the inclusion criteria. Following the independent samples t test, a post hoc power analysis was conducted via G*Power 3.1 to assess the adequacy of the sample size. The analysis revealed that, with 103 participants, a significance level of α = 0.05, and an effect size of d = 0.380, the achieved statistical power (1–β) was 0.98. This finding indicates that the sample size was highly sufficient for detecting the observed effect. Research Questions Is there a significant relationship between biological adherence, assessed through therapeutic drug levels, and self-reported MA in long-term KTRs? Do demographic and clinical characteristics-such as sex, age at transplantation, type of underlying chronic disease, donor type (living or deceased), and the donor-recipient relationship, significantly affect patients’ therapeutic drug levels? How do immunosuppressive drug levels change over time, from the 3rd month to the 10th year post-transplantation, in KTRs? Variables and Measurements Self-reports and biological measurements were used to evaluate MA. Biological MA was assessed on the basis of tacrolimus and cyclosporine plasma levels. The blood plasma levels and protocol modifications over the 10-year post-transplant period were retrospectively obtained from patient medical records. According to the kidney transplantation center’s protocol, the therapeutic plasma range for tacrolimus was defined as 10–12 ng/mL between 1–3 months post-transplant and 5–10 ng/mL thereafter. For cyclosporine, the evaluation was based on the C0 concentration. Given that the number of patients with C2 measurements was limited, these data were excluded from the analysis. The therapeutic C0 range for cyclosporine was defined as 200–400 ng/mL between 1–3 months, 150–300 ng/mL between 4–12 months, and 100–200 ng/mL beyond 12 months. Among the 103 patients who met the inclusion criteria, six (n = 6) were excluded because they were using rapamycin or everolimus because their plasma levels were measured in external laboratories. Therefore, the 10-year biological MA was evaluated for 97 patients. Among these patients, 82 were receiving tacrolimus, and eight were receiving cyclosporine. The MA levels of seven patients who switched between tacrolimus and cyclosporine during the 10-year follow-up period were assessed at 12 measurement points: the 3rd month, the 6th month, and the 1st through 10th years post-transplant. At each measurement, if the tacrolimus and/or cyclosporine plasma level was within the therapeutic range, it was classified as adherent; otherwise, it was classified as nonadherent. As a result of this evaluation, patients were categorized into five groups on the basis of their MA levels: 100% adherent: adherent at all 12 measurement points, 75% adherent: adherent at 8–11 measurement points, 50% adherent: adherent at 5–7 measurement points, 25% adherent: adherent at 1–4 measurement points, 0% adherent: not adherent at any measurement point. Self-reported MA was assessed via the Immunosuppressant Therapy Adherence Scale (ITAS). This study evaluated the MA of patients who had undergone kidney transplantation at least 10 years prior. Self-reported adherence was assessed once at the time of data collection. For example, a patient could have been in their 10th or 17th posttransplant year at the time of assessment; in either case, self-reported adherence was evaluated as a single measurement. The ITAS was originally developed by Morisky et al. (1986) to assess adherence to antihypertensive medications among patients with hypertension. In 2005, Chisholm et al. adapted the scale to organ transplant recipients 16 . The ITAS is composed of four questions regarding immunosuppressive treatment adherence behavior in the prior three months. Each response to the questions is classified as 0%, 1–20%, 21–50%, or greater than 50%. The total score on the scale ranges between 0 and 12, with higher scores indicating better adherence. The original scale demonstrated high validity and reliability. The scale was adapted to Turkish culture by Madran et al. In this study, patients who received the full 12 points on the ITAS were classified as adherent, whereas those with lower scores were considered nonadherent. Sociodemographic and clinical characteristic questionnaires included questions about age, sex, date of transplantation, donor type, relationship of the donor, etiology of kidney transplantation, chronic disease, preemptive transplantation, retransplantation, location of the graft kidney, rejection history, and number. Additionally, patients’ blood urea nitrogen (BUN) and creatinine levels were evaluated at a total of 12 time points: 3 months, 6 months, and annually from year 1 to year 10. Data analysis Statistical analyses were performed via the IBM Statistical Package for the Social Sciences (SPSS) version 29.0 (IBM Corp., Armonk, NY, USA). Descriptive characteristics were evaluated via frequencies, percentages, means, and standard deviations. The Kolmogorov–Smirnov test was applied to assess the normality of the data distribution. Changes in biological MA over time were analyzed via Cochran’s Q test. The relationship between biological and self-reported MA was assessed via the chi-square test. The associations between MA and tacrolimus levels and biochemical parameters such as BUN and creatinine were evaluated via the Mann–Whitney U test. Similarly, the relationships between self-reported MA and BUN and creatinine levels were analyzed via the Mann–Whitney U test. The relationships between MA and variables such as sex, age at transplantation, type of chronic disease, donor type, donor relationship, and history of rejection were analyzed via chi-square, Mann–Whitney U, or Kruskal–Wallis tests, depending on the level of measurement of the variables. Results The mean age of the patients was 52.43 ± 11.76 years, and the mean time elapsed since transplantation was 11.77 ± 1.46 years. Among the patients, 62.1% (n = 64) were male. A total of 76.7% (n = 79) had at least one chronic disease, and 76.7% (n = 73) had hypertension. One patient had undergone preemptive transplantation, and five patients (4.9%) were retransplant recipients. The etiology of kidney disease leading to transplantation was unknown in 24.3% (n = 25) of the patients. The deceased donation rate was 52.43% (n = 53). In addition, 57.3% (n = 59) of the patients underwent left kidney transplantation, 10.7% (n = 11) developed rejection, and the mean time to rejection was 5 ± 4.63 years. Medication adherence Biological medication adherence The distribution of patients' 10-year MA based on tacrolimus and cyclosporine plasma levels is shown in Fig. 1 . When the MA levels were categorized according to the 12 measurements obtained over the 10-year period, 1 patient (1.03%) was 100% adherent, 30 patients (30.93%) were 75% adherent, 24 patients (24.74%) were 50% adherent, 37 patients (38.15%) were 25% adherent, and 5 patients (5.16%) were 0% adherent. Patients demonstrating 0% or 25% adherence were grouped as having low adherence , representing 43.3% of the total sample (n = 42). During the 10-year follow-up period after kidney transplantation, a significant difference in tacrolimus adherence over time was observed, specifically between the 3rd month, 6th month, and 10th year (Cochran's Q = 70.871, p < 0.001). Self-reported medication adherence The mean ITAS score was 11.54 ± 1.15 (min–max = 7–12, n = 103). Patients who received the maximum score on the ITAS were classified as adherent , resulting in an overall adherence rate of 82.52% (n = 85). Relationship between biological and self-reported medication adherence No statistically significant relationship was found between the 10-year biological assessment results and self-reported medication adherence among KTRs (χ²=0.002, p = 0.965). Relationship between biological medication adherence and the BUN-creatinine ratio The 10-year distributiondistributions of patients’ BUN and creatinine levels isare presented in Fig. 2 . Differences in BUN and creatinine levels according to biological MA status are shown in Table 1 . Among patients usingreceiving tacrolimus, at the 6th month, the non-adherentnonadherent group had a significantly highergreater mean BUN level (74.81 ± 44.21) compared withthan did the adherent group (52.39 ± 28.34) (U = 462.000, p = 0.016). Among patients using cyclosporine, at the 9th year, the non-adherentnonadherent group also demonstratedpresented a higher mean BUN level (1.17 ± 0.25) than did the adherent group (0.89 ± 0.19) (U = 0.000, p = 0.046). A statistically significant negative correlation was found between self-reported MA and 10-year BUN levels (U = 329.500, p = 0.001). However, no statistically significant association was found between self-reported MA and 10-year creatinine levels (U = 755.500, p = 0.934) (Table 2 ). Table 1 Effect of Biological Medication Adherence on BUN and Creatinine Levels in Kidney Transplant Recipients Time Tacrolimus Cyclosporine BUN Kreatinin BUN Kreatinin 3rd month U = 166.500 p = 0.897 U = 148.500 p = 0.605 U = 3.000 p = 0.121 U = 2.000 p = 0.071 6th month U = 462.000 p = 0.016* U = 662.500 p = 0.816 U = 12.000 p = 0.917 U = 8.000 p = 0.347 1st year U = 625.000 p = 0.316 U = 687.000 p = 0.719 U = 9.000 p = 0.150 U = 6.000 p = 0.053 2nd year U = 699.000 p = 0.669 U = 734.500 p = 0.947 U = 13.000 p = 0.735 U = 11.500 p = 0.553 3rd year U = 644.000 p = 0.661 U = 576.000 p = 0.176 U = 2.000 p = 0.343 U = 1.000 p = 0.205 4th year U = 693.000 p = 0.863 U = 588.500 p = 0.204 U = 5.000 p = 1.00 U = 2.000 p = 0.337 5th year U = 731.500 p = 0.838 U = 640.000 p = 0.262 U = 6.000 p = 0.770 U = 4.000 p = 0.372 6th year U = 737.500 p = 0.348 U = 639.000 p = 0.063 U = 4.500 p = 0.309 U = 5.500 p = 0.468 7th year U = 855.500 p = 0.826 U = 846.000 p = 0.760 U = 1.000 p = 0.53 U = 2.000 p = 0.101 8th year U = 762.500 p = 0.417 U = 829.500 p = 0.844 U = 2.500 p = 0.134 U = 6.000 p = 0.651 9th year U = 876.500 p = 0.836 U = 874.500 p = 0.822 U = 0.000 p = 0.046* U = 0.500 p = 0.064 10th year U = 887.000 p = 0.746 U = 917.000 p = 0.948 U = 5.500 p = 0.858 U = 6.000 p = 1.00 *p < 0.05, Mann-Whitney U, BUN: blood urea nitrogen Table 2 Effect of Self-reported Medication Adherence on BUN and Creatinine Levels in Kidney Transplant Recipients Parameter Adherent (ITAS = 12) Median (Min–Max) n = 85 Non-adherent (ITAS ≤ 11) Median (Min–Max) n = 18 BUN (mg/dL) (n = 103) 38.00 (18–102) 62.95 (24–141) U = 329.500 p = 0.001* Creatinine (mg/dL) (n = 103) 1.20 (0.60–5.56) 1.15 (0.70-6.00) U = 755.500 p = 0.934 *p < 0.05, Mann-Whitney U, BUN: blood urea nitrogen Factors associated with medication adherence In the analysis of factors affecting MA, no statistically significant relationships were found between sex, age at transplantation, type of chronic disease, donor type, or donor relationship and tacrolimus plasma levels at the 3rd month, 6th month, 1st year, 5th year, or 10th year (p > 0.05). A statistically significant association was observed between sex and tacrolimus plasma level at the 7th year (χ²=4.582, p = 0.032), with female patients exhibiting higher tacrolimus concentrations (U = 648.00, p = 0.033). With respect to self-reported MA, no statistically significant relationships were found with age (r = 0.107, p = 0.28), sex (U = 1201.00, p = 0.63), type of chronic disease (KW = 5.949, p = 0.65), donor type (U = 1313.500, p = 0.91), or donor relationship (KW = 4.007, p = 0.64). Patients who experienced rejection had lower mean self-reported adherence scores (9.73 ± 2.28) than did those without rejection (11.77 ± 0.66) (U = 225.500, p < 0.001). Discussion This study examined immunosuppressive MA and the factors influencing it over a decade among KTRs via both biological and self-reported assessment methods. MA plays a critical role in graft survival and overall patient prognosis 17 . Therefore, evaluating adherence behaviors is particularly important in the long-term management of transplant recipients. In the present study, biological assessment revealed that 43.3% of patients demonstrated low MA, and only one patient achieved full adherence. These rates approach the upper limits of the wide range of nonadherence rates reported in the literature 5 , 6 . The exceptionally low rate of full adherence highlights the challenge of maintaining long-term sustainability to immunosuppressive therapy. Previous studies have similarly reported an association between nonadherence and lower tacrolimus levels 18 , 19 . Accordingly, monitoring therapeutic blood levels and adherence to prescribed regimens should be integrated into routine transplant care. In this study, fluctuations in biological adherence over time were observed on the basis of both tacrolimus and cyclosporine plasma levels. This finding is consistent with the variable results reported in the literature. While some studies have shown that the time elapsed since transplantation does not influence MA 19,20 , others have demonstrated that adherence may decrease or, in some cases, increase during certain post-transplant periods 5 , 7 , 8 , 13 , 21 . This variability may arise not only from temporal factors but also from multidimensional effects such as treatment fatigue, psychological exhaustion, financial burden, and individual risk profiles 15 , 22 . Therefore, MA should be evaluated not only in the early posttransplant stages but also as a long-term process that evolves 6 , 23 . In this study, the self-reported MA rate was relatively high at 82.52%. However, no statistically significant associations were detected between self-reported and biologically measured adherence. This inconsistency has been frequently reported in the literature and is largely attributable to the inherent differences between subjective and objective assessment methods 24 . Self-report questionnaires such as the ITAS primarily reflect patients’ medication-taking behavior within a limited time frame and may therefore be insufficient for evaluating long-term medication adherence. Furthermore, these instruments are susceptible to social desirability bias, leading patients to overreport their adherence levels 25 , 26 . Similarly, therapeutic plasma levels are influenced not only by patient behavior but also by drug–drug or drug–food interactions, and interindividual metabolic differences 24 . Therefore, considering the inherent limitations of both approaches, their combined use at multiple time points would yield a more comprehensive and reliable assessment of MA. The impact of medication nonadherence on clinical biomarkers was evaluated in this study via both biological and self-reported adherence data. Among patients classified as nonadherent on the basis of biological assessment, a significant increase in BUN levels was observed at the 6th month and 9th year. Similarly, patients classified as nonadherent according to self-reported assessment presented elevated BUN levels at the 10th year; however, no significant correlation was found with creatinine levels. These findings suggest that nonadherence may adversely affect renal function over the long term. Previous research has indicated that creatinine levels increase only in advanced allograft damage and have limited sensitivity in detecting early renal damage 27 . Therefore, although conventional biomarkers are widely used for monitoring posttransplant kidney function, they are not considered sufficient predictors on their own. These two markers should instead be interpreted as complementary indicators, particularly for monitoring progressive graft dysfunction. When the relationships between adherence and demographic or clinical factors, no significant associations were examined with sex, age, type of chronic disease, donor type, or donor relationship. This finding is consistent with those of previous studies 5 , 6 , 28 . However, the observation that female patients presented higher tacrolimus levels at the seventh year suggests that such variables may differ contextually. This difference may be related to mediating factors such as educational level, health literacy, or social support. In addition, variations in assessment methods may also contribute to this relationship; therefore, further studies utilizing standardized approaches are needed to clarify this relationship more accurately. The finding that individuals experiencing rejection report lower MA highlights the direct impact of nonadherence on clinical outcomes. This finding also suggests that past complications may create psychological effects in patients, further weakening adherence behavior. Therefore, adherence should be regularly assessed over time in all patients to identify potential nonadherence issues and implement timely, appropriate interventions 12 . This study has several limitations. First, the data were obtained retrospectively from medical records only, and self-reported adherence was assessed at a single time point. Second, the study was conducted at a single center with a relatively limited sample size, potentially restricting the generalizability of the findings. Third, the use of self-reported measures may be susceptible to social desirability bias, possibly resulting in overestimation of actual adherence levels. Finally, psychosocial variables were not evaluated, and detailed adherence-related factors, such as medication timing, were not assessed. Conclusions This study provides a comprehensive analysis of long-term immunosuppressive drug adherence among KTRs by integrating biological and self-reported assessment methods, and including long-term follow up data. The findings indicate fluctuations in adherence levels over a ten-year posttransplant period, with self-reported adherence appearing high, whereas biological indicators suggest lower adherence. The difference between these two assessment methods underscores the necessity of multidimensional evaluation approaches. Furthermore, significantly lower adherence scores in individuals with a history of rejection indicate that nonadherence behaviors have a direct impact on clinical outcomes. In conclusion, the findings suggest that MA may fluctuate over time, that the use of complementary assessment methods is essential, and that nonadherence behaviors can directly influence clinical outcomes. Therefore, regular assessment of MA via multidimensional approaches in long-term transplant recipients is recommended, as this strategy may effectively improve both graft and patient survival. Future multicenter studies employing standardized and multidimensional adherence assessment methods are warranted to provide a more comprehensive understanding of the complex nature of adherence. Abbreviations ITAS Immunosuppressive Therapy Adherence Scale BUN Blood urea nitrogen KTR Kidney transplant recipient MA Medication adherence Declarations Ethics approval and consent to participate All transplanted organs were obtained through legally approved donation procedures in accordance with national regulations and international ethical standards. The authors declare that no organs were obtained from prisoners or other institutionalized individuals. Informed consent was obtained from all the participants prior to data collection for self-reported assessment. The Dokuz Eylul University Non-Invasive Research Ethics Committee (Approval no: 2023/17-08, Date: May 24, 2023) at the authors’ institution approved the study protocol. The study adhered to the ethical principles of the Helsinki Declaration and strictly protected patient confidentiality. Consent for publication Not applicable. Data availability The datasets generated or analyzed during the current study are available from the corresponding author upon reasonable request. Competing interests The authors declare no competing interests. Funding This study did not receive any specific grant or funding. Author Contributions YSO and HTD jointly contributed to the conceptualization of the study. Formal analysis, writing-review and editing, and project administration were performed by YSO and BSS. The original draft of the manuscript was prepared by YSO and BSS. Data curation was conducted by SA and HTD. Visualization was carried out by BSS, and resources were provided by SA and BSS. Acknowledgments The authors would like to thank the participants who voluntarily participated in the study. References Lieber SR, Helcer J, Shemesh E. Monitoring drug adherence. Trans plant Rev (Orlando). 2015;29(2):73–7. Zhu Y, Zhou Y, Zhang L, Zhang J, Lin J. Efficacy of interventions for adherence to the immunosuppressive therapy in kidney transplant recipients: a meta-analysis and systematic review. J Investig Med. 2017;65(7):1049–56. 10.1136/jim-2016-000265 . Torres-Gutiérrez M, Lozano-Suárez N, Burgos-Camacho VA, et al. Is Non-Adherence Associated with Adverse Outcomes in Kidney Transplant Recipients? The Role of Non-Adherence as a Risk and Predictor Factor for Graft Loss and Death. Patient Prefer Adherence. 2023;17:2915–25. 10.2147/PPA.S436833 . Gandolfini I, Palmisano A, Fiaccadori E, Cravedi P, Maggiore U. Detecting, preventing and treating non-adherence to immunosuppression after kidney transplantation. Clin Kidney J. 2022;15(7):1253–74. Gokoel SRM, Gombert-Handoko KB, Zwart TC, van der Boog PJM, Moes DJAR, de Fijter JW. Medication non-adherence after kidney transplantation: A critical appraisal and systematic review. Transpl Rev (Orlando). 2020;34(1):100511. 10.1016/j.trre.2019.100511 . Corr M, Walker A, Maxwell AP, McKay GJ. Non-adherence to immunosuppressive medications in kidney transplant recipients- a systematic scoping review. Transpl Rev (Orlando). 2025;39(1):100900. 10.1016/j.trre.2024.100900 . Belaiche S, Décaudin B, Dharancy S, Noel C, Odou P, Hazzan M. Factors relevant to medication non-adherence in kidney transplant: a systematic review. Int J Clin Pharm. 2017;39(3):582–93. 10.1007/s11096-017-0436-4 . Lorenz EC, Smith BH, Cosio FG, Schinstock CA, Shah ND, Groehler PN, Verdick JS, Park WD, Stegall MD. Long-retm immunosupprssion adherence after kidney transplant and relationship to allograft histology. Tranpslantation Direct. 2018;4:e392. 10.1097/TXD.0000000000000824 . Anghel LA, Farcas AM, Oprean RN. An overview of the common methods used to measure treatment adherence. Med Pharm Rep. 2019;92(2):117–22. 10.15386/mpr-1201 . Sarıgöl Ordin Y, Karayurt O, Ertan N, Yıldız S. Böbrek nakli alıcılarında immünosupresif tedaviye uyumun farklı yöntemlerle değerlendirilmesi. Turk Neph Dial Transpl. 2018;27(3):254–61. 10.5262/tndt.2018.3147 . De Geest S, Ribaut J, Denhaerynck K, Dobbels F. Adherence management in transplantation. In: Daniel C, Scott DC, Paul LK, editors. Psychosocial aspects of chronic kidney disease. Academic Press. 2021;409–448. 10.1016/B978-0-12-817080-9.00019-1 Villeneuve C, Rousseau A, Rerolle JP, et al. Adherence profiles in kidney transplant patients: Causes and consequences. Patient Educ Couns. 2020;103(1):189–98. 10.1016/j.pec.2019.08.002 . Liu H, Shang Y, Du C, Wu S. Immunosuppressive Medication Adherence and its Associated Factors in Renal Transplant Recipients. Transplantation. 2018;102:S68. 10.1097/01.tp.0000542646.11124.c8 . Gibson TB. A dynamic analysis of medication adherence. J managed care specialty Pharm. 2022;28(12):1392–9. 10.18553/jmcp.2022.28.12.1392 . Lorenz EC, Egginton JS, Stegall MD, et al. Patient experience after kidney transplant: a conceptual framework of treatment burden. J Patient Rep Outcomes. 2019;3:8. 10.1186/s41687-019-0095-4 . Chisholm MA, Lance CE, Williamson GM, Mulloy LL. Development and validation of the immunosuppressant therapy adherence instrument (ITAS). Patient Educ Couns. 2005;59(1):13–20. 10.1016/j.pec.2004.09.007 . Low JK, Crawford K, Manias E, Walker R. Quantifying the medication burden of kidney transplant recipients in the first year post-transplantation. Int J Clin Pharm. 2018;40(6):1242–9. 10.1007/s11096-018-0678-9 . Tecen-Yucel K, Bayraktar-Ekincioglu A, Yıldırım T, Demirkan K, Erdem Y. Assessment of adherence to immunosuppressive treatment in kidneytransplant patients: A descriptive study. Turk J Nephrol. 2023;32(3):241–8. Lalić J, Veličković-Radovanović R, Mitić B, Paunović G, Cvetković T. Immunosuppressive medication adherence in kidney transplant patients. Med Princ Pract. 2014;23(4):351–6. 10.1159/000362792 . Russell CL, Ashbaugh C, Peace L, et al. Time-in-a-bottle (TIAB): a longitudinal, correlational study of patterns, potential predictors, and outcomes of immunosuppressive medication adherence in adult kidney transplant recipients. Clin Transpl. 2013;27(5):E580–90. Tatoğlu N, Karayurt Ö, Öğce F. Factors affecting adherence of recipients to immunosuppressive therapy after liver and kidney transplantation. J Educ Res Nurs. 2023;20(1):20–7. Zachciał J, Uchmanowicz I, Krajewska M, Banasik M. Adherence to Immunosuppressive Therapies after Kidney Transplantation from a Biopsychosocial Perspective: A Cross-Sectional Study. J Clin Med. 2022;11(5):1381. 10.3390/jcm11051381 . Bendersky VA, Saha A, Sidoti CN, et al. Factors impacting the medication Adherence Landscape for transplant patients. Clin Transpl. 2023;37:e14962. 10.1111/ctr.14962 . Scheel J, Reber S, Stoessel L, Waldmann E, Jank S, Eckardt KU, et al. Patient-reported non-adherence and immunosuppressant trough levels are associated with rejection after renal transplantation. BMC Nephrol. 2017;18(1):107. 10.1186/s12882-017-0517-6 . Lieb M, Hepp T, Schiffer M, et al. Accuracy and concordance of measurement methods to assess non-adherence after renal transplantation - a prospective study. BMC Nephrol. 2020;21:114. 10.1186/s12882-020-01781-1 . Herblum J, Dacouris N, Huang M, et al. Retrospective Analysis of Tacrolimus Intrapatient Variability as a Measure of Medication Adherence. Can J Kidney Health Disease. 2021;8. 10.1177/20543581211021742 . Salvadori M, Tsalouchos A. Biomarkers in renal transplantation: An updated review. World J Transpl. 2017;7(3):161–78. 10.5500/wjt.v7.i3.161 . Melilli E, Díaz MI, Gomis-Pastor M, et al. Predictors of Treatment Adherence in Kidney Transplant Patients: A Systematic Review of the Literature. J Clin Med. 2025;14(5):1622. 10.3390/jcm14051622 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 31 Jan, 2026 Reviews received at journal 31 Jan, 2026 Reviews received at journal 31 Jan, 2026 Reviews received at journal 22 Jan, 2026 Reviewers agreed at journal 10 Jan, 2026 Reviewers agreed at journal 08 Jan, 2026 Reviewers agreed at journal 08 Jan, 2026 Reviewers invited by journal 08 Jan, 2026 Editor invited by journal 27 Dec, 2025 Editor assigned by journal 27 Dec, 2025 Submission checks completed at journal 24 Dec, 2025 First submitted to journal 24 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Hospital","correspondingAuthor":false,"prefix":"","firstName":"Serap","middleName":"","lastName":"Arıcan","suffix":""},{"id":572858272,"identity":"0a784671-1b42-404e-887a-0ef57563980a","order_by":2,"name":"Büşra Selma Saha","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIiWNgGAWjYBACAygtAyKYGRhsgBRj4wFitPBAtaSBtDSQpOUwmIdXi7lE+rMPP/7Y8Oi2H3/4uaDmvN3a9sNAW2psonFpsZyRYzyzty2Nx+xMjrH0jGO3k7edSQRqOZaW24DLYTdymBl4Gw7zmB3IYZDmYbudbHYAqIWx4TAeLemPGf/8+c9jdv754988/84lm51/SEhLgjEzD9sBHrMbCWbSvG0H7MxuELDFsueNMbNsWzJQyxsza96+5ASzG0BbEvD4xZwd6LA3f+zkzM6nP77N883OHsh4+OBDjQ1OLRggEawygVjlIGBPiuJRMApGwSgYGQAA2Qxi2lhO4rcAAAAASUVORK5CYII=","orcid":"","institution":"Dokuz Eylül University","correspondingAuthor":true,"prefix":"","firstName":"Büşra","middleName":"Selma","lastName":"Saha","suffix":""},{"id":572858274,"identity":"4a93bd15-0ed8-4d70-875c-864578e1c782","order_by":3,"name":"Hale Turhan Damar","email":"","orcid":"","institution":"Izmir Democracy University","correspondingAuthor":false,"prefix":"","firstName":"Hale","middleName":"Turhan","lastName":"Damar","suffix":""}],"badges":[],"createdAt":"2025-12-21 20:53:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8419420/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8419420/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":100363453,"identity":"32c40947-5dc1-452d-8ee1-805781b31970","added_by":"auto","created_at":"2026-01-16 07:49:49","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":115576,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.docx","url":"https://assets-eu.researchsquare.com/files/rs-8419420/v1/2e8a4155963bac2bbb9af763.docx"},{"id":100067977,"identity":"c3fb12e4-5b3b-47d0-8fb7-79e3e647d0bf","added_by":"auto","created_at":"2026-01-12 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15:57:00","extension":"xml","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":89305,"visible":true,"origin":"","legend":"","description":"","filename":"03cdf29d8a994f77b8471b6c704c7b701structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8419420/v1/1b072402c5fb06340ae384e5.xml"},{"id":100067983,"identity":"f6b831fe-d241-4184-9124-65895c9b849e","added_by":"auto","created_at":"2026-01-12 15:57:00","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":99138,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8419420/v1/d47c2908c834936b2d730b76.html"},{"id":100364133,"identity":"d5359ddf-c907-4cfa-b38c-e4fdc83a3d9e","added_by":"auto","created_at":"2026-01-16 07:52:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":36404,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of 10-year immunosuppressive medication adherence among kidney transplant recipients. a. Tacrolimus b. Cyclosporine\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8419420/v1/a586bc1662acf1a65024c63a.png"},{"id":100067973,"identity":"ee933fc1-2588-444e-8e67-e29fe2bcf475","added_by":"auto","created_at":"2026-01-12 15:56:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":23269,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of blood plasma BUN and creatinine levels over a 10-year period. a. Blood Urea Nitrogen (BUN) b. Creatinine\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8419420/v1/ab13f78c820600f29b62ede5.png"},{"id":100382032,"identity":"b4f19a46-2aa2-45bb-8769-fdd867b9cf4c","added_by":"auto","created_at":"2026-01-16 10:40:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":799716,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8419420/v1/a42275e8-bc7d-4e80-888c-73258238d20d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluation of Medication Adherence Over a Decade Following Kidney Transplantation: Integration of Biological and Self-Reported Data","fulltext":[{"header":"Background","content":"\u003cp\u003eSufficient immunosuppression is essential for both short- and long-term survival following organ transplantation. Accordingly, adherence to immunosuppressive therapy is critical for preventing organ rejection, graft loss, and posttransplant mortality \u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Nonadherence to immunosuppressive medication has been linked to approximately 16% of early graft losses and 20% of antibody-mediated rejections \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. The prevalence of medication adherence (MA) among kidney transplant recipients (KTRs) varies widely, with a systematic review reporting rates between 36% and 55% \u003csup\u003e5\u003c/sup\u003e, whereas a scoping review revealed an even broader range, from 2% to 89% \u003csup\u003e6\u003c/sup\u003e. Several factors have been associated with nonadherence, including younger age, male sex, low social support, unemployment, lower educational attainment, longer time since transplantation, sirolimus-based therapy, living donor transplantation, high chronic disease burden, polypharmacy, and a history of depression \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Early identification of recipients with these risk factors and the implementation of close, individualized monitoring are critical strategies for improving adherence and ensuring long-term graft survival.\u003c/p\u003e \u003cp\u003eRegular assessment of treatment adherence is necessary to ensure that immunosuppressive therapy can be continued safely and effectively. The most commonly used direct method in clinical practice is the measurement of therapeutic drug levels; however, this method reflects only short-term adherence. Indirect methods include patient self-assessment forms, patient diaries, prescription refill records, and electronic medication monitoring technologies \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. A single adherence assessment method is not sufficient for accurately measuring adherence behavior. Therefore, combining multiple methods and repeated assessments ensures more accurate and reliable results \u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. In addition, MA is a dynamic process that may vary over time after transplantation \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. The literature presents conflicting findings on this issue: some studies have shown that adherence decreases over the long term \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, whereas others have shown that early adherence behavior continues in later periods \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. On the other hand, some findings report an increase in adaptation between the 3rd and 5th years \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. These differences highlight the need for an assessment approach that spans time.\u003c/p\u003e \u003cp\u003eKidney transplantation is a highly effective treatment modality that significantly enhances long-term survival in patients with end-stage renal disease. As the number of transplant recipients continues to rise, evaluating long-term MA and identifying the factors that influence it have become increasingly important. Immunosuppressive therapy is essential for maintaining graft function and preventing rejection, yet adherence to these medications can decline over time due to various demographic, clinical, and psychosocial factors. In this context, the present study aims to explore the trajectory of immunosuppressive MA among individuals who have been living with a kidney transplant for 10 years or longer and to identify the demographic and clinical variables that may influence this adherence.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and patient population\u003c/h2\u003e \u003cp\u003eThis study was conducted with a retrospective, cross-sectional, descriptive research design. This study was conducted in the kidney transplantation unit of a training and research hospital. The data were collected between June 2023 and July 2024. The study sample consisted of KTRs who had undergone transplantation at least 10 years prior. The inclusion criteria were being willing to participate in the study, being 18 years of age or older, having undergone only kidney transplantation, and being able to speak and understand Turkish.\u003c/p\u003e \u003cp\u003eAt the time of data collection, 301 KTRs were under follow-up. Among them, 103 patients had undergone kidney transplantation at least 10 years earlier and met the inclusion criteria. Following the independent samples t test, a post hoc power analysis was conducted via G*Power 3.1 to assess the adequacy of the sample size. The analysis revealed that, with 103 participants, a significance level of α\u0026thinsp;=\u0026thinsp;0.05, and an effect size of d\u0026thinsp;=\u0026thinsp;0.380, the achieved statistical power (1\u0026ndash;β) was 0.98. This finding indicates that the sample size was highly sufficient for detecting the observed effect.\u003c/p\u003e \u003cp\u003e \u003cb\u003eResearch Questions\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIs there a significant relationship between biological adherence, assessed through therapeutic drug levels, and self-reported MA in long-term KTRs?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDo demographic and clinical characteristics-such as sex, age at transplantation, type of underlying chronic disease, donor type (living or deceased), and the donor-recipient relationship, significantly affect patients\u0026rsquo; therapeutic drug levels?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eHow do immunosuppressive drug levels change over time, from the 3rd month to the 10th year post-transplantation, in KTRs?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eVariables and Measurements\u003c/h3\u003e\n\u003cp\u003eSelf-reports and biological measurements were used to evaluate MA. Biological MA was assessed on the basis of tacrolimus and cyclosporine plasma levels. The blood plasma levels and protocol modifications over the 10-year post-transplant period were retrospectively obtained from patient medical records. According to the kidney transplantation center\u0026rsquo;s protocol, the therapeutic plasma range for tacrolimus was defined as 10\u0026ndash;12 ng/mL between 1\u0026ndash;3 months post-transplant and 5\u0026ndash;10 ng/mL thereafter. For cyclosporine, the evaluation was based on the C0 concentration. Given that the number of patients with C2 measurements was limited, these data were excluded from the analysis. The therapeutic C0 range for cyclosporine was defined as 200\u0026ndash;400 ng/mL between 1\u0026ndash;3 months, 150\u0026ndash;300 ng/mL between 4\u0026ndash;12 months, and 100\u0026ndash;200 ng/mL beyond 12 months.\u003c/p\u003e \u003cp\u003eAmong the 103 patients who met the inclusion criteria, six (n\u0026thinsp;=\u0026thinsp;6) were excluded because they were using rapamycin or everolimus because their plasma levels were measured in external laboratories. Therefore, the 10-year biological MA was evaluated for 97 patients. Among these patients, 82 were receiving tacrolimus, and eight were receiving cyclosporine. The MA levels of seven patients who switched between tacrolimus and cyclosporine during the 10-year follow-up period were assessed at 12 measurement points: the 3rd month, the 6th month, and the 1st through 10th years post-transplant. At each measurement, if the tacrolimus and/or cyclosporine plasma level was within the therapeutic range, it was classified as adherent; otherwise, it was classified as nonadherent. As a result of this evaluation, patients were categorized into five groups on the basis of their MA levels:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e100% adherent: adherent at all 12 measurement points,\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e75% adherent: adherent at 8\u0026ndash;11 measurement points,\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e50% adherent: adherent at 5\u0026ndash;7 measurement points,\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e25% adherent: adherent at 1\u0026ndash;4 measurement points,\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e0% adherent: not adherent at any measurement point.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eSelf-reported MA was assessed via the Immunosuppressant Therapy Adherence Scale (ITAS). This study evaluated the MA of patients who had undergone kidney transplantation at least 10 years prior. Self-reported adherence was assessed once at the time of data collection. For example, a patient could have been in their 10th or 17th posttransplant year at the time of assessment; in either case, self-reported adherence was evaluated as a single measurement.\u003c/p\u003e \u003cp\u003eThe ITAS was originally developed by Morisky et al. (1986) to assess adherence to antihypertensive medications among patients with hypertension. In 2005, Chisholm et al. adapted the scale to organ transplant recipients \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. The ITAS is composed of four questions regarding immunosuppressive treatment adherence behavior in the prior three months. Each response to the questions is classified as 0%, 1\u0026ndash;20%, 21\u0026ndash;50%, or greater than 50%. The total score on the scale ranges between 0 and 12, with higher scores indicating better adherence. The original scale demonstrated high validity and reliability. The scale was adapted to Turkish culture by Madran et al. In this study, patients who received the full 12 points on the ITAS were classified as adherent, whereas those with lower scores were considered nonadherent.\u003c/p\u003e \u003cp\u003eSociodemographic and clinical characteristic questionnaires included questions about age, sex, date of transplantation, donor type, relationship of the donor, etiology of kidney transplantation, chronic disease, preemptive transplantation, retransplantation, location of the graft kidney, rejection history, and number. Additionally, patients\u0026rsquo; blood urea nitrogen (BUN) and creatinine levels were evaluated at a total of 12 time points: 3 months, 6 months, and annually from year 1 to year 10.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed via the IBM Statistical Package for the Social Sciences (SPSS) version 29.0 (IBM Corp., Armonk, NY, USA). Descriptive characteristics were evaluated via frequencies, percentages, means, and standard deviations. The Kolmogorov\u0026ndash;Smirnov test was applied to assess the normality of the data distribution. Changes in biological MA over time were analyzed via Cochran\u0026rsquo;s Q test. The relationship between biological and self-reported MA was assessed via the chi-square test. The associations between MA and tacrolimus levels and biochemical parameters such as BUN and creatinine were evaluated via the Mann\u0026ndash;Whitney U test. Similarly, the relationships between self-reported MA and BUN and creatinine levels were analyzed via the Mann\u0026ndash;Whitney U test. The relationships between MA and variables such as sex, age at transplantation, type of chronic disease, donor type, donor relationship, and history of rejection were analyzed via chi-square, Mann\u0026ndash;Whitney U, or Kruskal\u0026ndash;Wallis tests, depending on the level of measurement of the variables.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe mean age of the patients was 52.43\u0026thinsp;\u0026plusmn;\u0026thinsp;11.76 years, and the mean time elapsed since transplantation was 11.77\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46 years. Among the patients, 62.1% (n\u0026thinsp;=\u0026thinsp;64) were male. A total of 76.7% (n\u0026thinsp;=\u0026thinsp;79) had at least one chronic disease, and 76.7% (n\u0026thinsp;=\u0026thinsp;73) had hypertension. One patient had undergone preemptive transplantation, and five patients (4.9%) were retransplant recipients. The etiology of kidney disease leading to transplantation was unknown in 24.3% (n\u0026thinsp;=\u0026thinsp;25) of the patients. The deceased donation rate was 52.43% (n\u0026thinsp;=\u0026thinsp;53). In addition, 57.3% (n\u0026thinsp;=\u0026thinsp;59) of the patients underwent left kidney transplantation, 10.7% (n\u0026thinsp;=\u0026thinsp;11) developed rejection, and the mean time to rejection was 5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.63 years.\u003c/p\u003e\n\u003ch3\u003eMedication adherence\u003c/h3\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBiological medication adherence\u003c/h2\u003e \u003cp\u003eThe distribution of patients' 10-year MA based on tacrolimus and cyclosporine plasma levels is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. When the MA levels were categorized according to the 12 measurements obtained over the 10-year period, 1 patient (1.03%) was 100% adherent, 30 patients (30.93%) were 75% adherent, 24 patients (24.74%) were 50% adherent, 37 patients (38.15%) were 25% adherent, and 5 patients (5.16%) were 0% adherent. Patients demonstrating 0% or 25% adherence were grouped as having \u003cem\u003elow adherence\u003c/em\u003e, representing 43.3% of the total sample (n\u0026thinsp;=\u0026thinsp;42). During the 10-year follow-up period after kidney transplantation, a significant difference in tacrolimus adherence over time was observed, specifically between the 3rd month, 6th month, and 10th year (Cochran's Q\u0026thinsp;=\u0026thinsp;70.871, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSelf-reported medication adherence\u003c/h3\u003e\n\u003cp\u003eThe mean ITAS score was 11.54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.15 (min\u0026ndash;max\u0026thinsp;=\u0026thinsp;7\u0026ndash;12, n\u0026thinsp;=\u0026thinsp;103). Patients who received the maximum score on the ITAS were classified as \u003cem\u003eadherent\u003c/em\u003e, resulting in an overall adherence rate of 82.52% (n\u0026thinsp;=\u0026thinsp;85).\u003c/p\u003e\n\u003ch3\u003eRelationship between biological and self-reported medication adherence\u003c/h3\u003e\n\u003cp\u003eNo statistically significant relationship was found between the 10-year biological assessment results and self-reported medication adherence among KTRs (χ\u0026sup2;=0.002, p\u0026thinsp;=\u0026thinsp;0.965).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRelationship between biological medication adherence and the BUN-creatinine ratio\u003c/h2\u003e \u003cp\u003eThe 10-year distributiondistributions of patients\u0026rsquo; BUN and creatinine levels isare presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Differences in BUN and creatinine levels according to biological MA status are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Among patients usingreceiving tacrolimus, at the 6th month, the non-adherentnonadherent group had a significantly highergreater mean BUN level (74.81\u0026thinsp;\u0026plusmn;\u0026thinsp;44.21) compared withthan did the adherent group (52.39\u0026thinsp;\u0026plusmn;\u0026thinsp;28.34) (U\u0026thinsp;=\u0026thinsp;462.000, p\u0026thinsp;=\u0026thinsp;0.016). Among patients using cyclosporine, at the 9th year, the non-adherentnonadherent group also demonstratedpresented a higher mean BUN level (1.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25) than did the adherent group (0.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19) (U\u0026thinsp;=\u0026thinsp;0.000, p\u0026thinsp;=\u0026thinsp;0.046). A statistically significant negative correlation was found between self-reported MA and 10-year BUN levels (U\u0026thinsp;=\u0026thinsp;329.500, p\u0026thinsp;=\u0026thinsp;0.001). However, no statistically significant association was found between self-reported MA and 10-year creatinine levels (U\u0026thinsp;=\u0026thinsp;755.500, p\u0026thinsp;=\u0026thinsp;0.934) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of Biological Medication Adherence on BUN and Creatinine Levels in Kidney Transplant Recipients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTime\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eTacrolimus\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eCyclosporine\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBUN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKreatinin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBUN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eKreatinin\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3rd month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;166.500\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;148.500\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;3.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;2.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.071\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6th month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;462.000\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.016*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;662.500\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;12.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;8.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.347\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1st year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;625.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;687.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.719\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;9.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;6.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2nd year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;699.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.669\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;734.500\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.947\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;13.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.735\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;11.500\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.553\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3rd year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;644.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.661\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;576.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;2.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;1.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.205\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4th year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;693.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;588.500\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;5.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;2.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.337\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5th year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;731.500\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.838\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;640.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;6.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.770\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;4.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.372\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6th year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;737.500\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;639.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;4.500\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;5.500\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.468\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7th year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;855.500\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.826\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;846.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.760\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;1.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;2.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.101\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8th year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;762.500\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;829.500\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;2.500\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;6.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.651\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9th year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;876.500\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;874.500\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;0.000\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.046*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;0.500\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.064\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10th year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;887.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.746\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;917.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;5.500\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;6.000\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Mann-Whitney U, BUN: blood urea nitrogen\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of Self-reported Medication Adherence on BUN and Creatinine Levels in Kidney Transplant Recipients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdherent (ITAS\u0026thinsp;=\u0026thinsp;12)\u003c/p\u003e \u003cp\u003eMedian (Min\u0026ndash;Max)\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;85\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-adherent (ITAS\u0026thinsp;\u0026le;\u0026thinsp;11)\u003c/p\u003e \u003cp\u003eMedian (Min\u0026ndash;Max)\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;18\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBUN (mg/dL) (n\u0026thinsp;=\u0026thinsp;103)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38.00 (18\u0026ndash;102)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62.95 (24\u0026ndash;141)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;329.500\u003c/p\u003e \u003cp\u003e\u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine (mg/dL) (n\u0026thinsp;=\u0026thinsp;103)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.20 (0.60\u0026ndash;5.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.15 (0.70-6.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;755.500\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.934\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Mann-Whitney U, BUN: blood urea nitrogen\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eFactors associated with medication adherence\u003c/h2\u003e \u003cp\u003eIn the analysis of factors affecting MA, no statistically significant relationships were found between sex, age at transplantation, type of chronic disease, donor type, or donor relationship and tacrolimus plasma levels at the 3rd month, 6th month, 1st year, 5th year, or 10th year (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). A statistically significant association was observed between sex and tacrolimus plasma level at the 7th year (χ\u0026sup2;=4.582, p\u0026thinsp;=\u0026thinsp;0.032), with female patients exhibiting higher tacrolimus concentrations (U\u0026thinsp;=\u0026thinsp;648.00, p\u0026thinsp;=\u0026thinsp;0.033). With respect to self-reported MA, no statistically significant relationships were found with age (r\u0026thinsp;=\u0026thinsp;0.107, p\u0026thinsp;=\u0026thinsp;0.28), sex (U\u0026thinsp;=\u0026thinsp;1201.00, p\u0026thinsp;=\u0026thinsp;0.63), type of chronic disease (KW\u0026thinsp;=\u0026thinsp;5.949, p\u0026thinsp;=\u0026thinsp;0.65), donor type (U\u0026thinsp;=\u0026thinsp;1313.500, p\u0026thinsp;=\u0026thinsp;0.91), or donor relationship (KW\u0026thinsp;=\u0026thinsp;4.007, p\u0026thinsp;=\u0026thinsp;0.64). Patients who experienced rejection had lower mean self-reported adherence scores (9.73\u0026thinsp;\u0026plusmn;\u0026thinsp;2.28) than did those without rejection (11.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66) (U\u0026thinsp;=\u0026thinsp;225.500, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined immunosuppressive MA and the factors influencing it over a decade among KTRs via both biological and self-reported assessment methods. MA plays a critical role in graft survival and overall patient prognosis \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Therefore, evaluating adherence behaviors is particularly important in the long-term management of transplant recipients.\u003c/p\u003e \u003cp\u003eIn the present study, biological assessment revealed that 43.3% of patients demonstrated low MA, and only one patient achieved full adherence. These rates approach the upper limits of the wide range of nonadherence rates reported in the literature \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. The exceptionally low rate of full adherence highlights the challenge of maintaining long-term sustainability to immunosuppressive therapy. Previous studies have similarly reported an association between nonadherence and lower tacrolimus levels \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Accordingly, monitoring therapeutic blood levels and adherence to prescribed regimens should be integrated into routine transplant care.\u003c/p\u003e \u003cp\u003eIn this study, fluctuations in biological adherence over time were observed on the basis of both tacrolimus and cyclosporine plasma levels. This finding is consistent with the variable results reported in the literature. While some studies have shown that the time elapsed since transplantation does not influence MA \u003csup\u003e19,20\u003c/sup\u003e, others have demonstrated that adherence may decrease or, in some cases, increase during certain post-transplant periods \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. This variability may arise not only from temporal factors but also from multidimensional effects such as treatment fatigue, psychological exhaustion, financial burden, and individual risk profiles \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Therefore, MA should be evaluated not only in the early posttransplant stages but also as a long-term process that evolves \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this study, the self-reported MA rate was relatively high at 82.52%. However, no statistically significant associations were detected between self-reported and biologically measured adherence. This inconsistency has been frequently reported in the literature and is largely attributable to the inherent differences between subjective and objective assessment methods \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Self-report questionnaires such as the ITAS primarily reflect patients\u0026rsquo; medication-taking behavior within a limited time frame and may therefore be insufficient for evaluating long-term medication adherence. Furthermore, these instruments are susceptible to social desirability bias, leading patients to overreport their adherence levels \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Similarly, therapeutic plasma levels are influenced not only by patient behavior but also by drug\u0026ndash;drug or drug\u0026ndash;food interactions, and interindividual metabolic differences \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Therefore, considering the inherent limitations of both approaches, their combined use at multiple time points would yield a more comprehensive and reliable assessment of MA.\u003c/p\u003e \u003cp\u003eThe impact of medication nonadherence on clinical biomarkers was evaluated in this study via both biological and self-reported adherence data. Among patients classified as nonadherent on the basis of biological assessment, a significant increase in BUN levels was observed at the 6th month and 9th year. Similarly, patients classified as nonadherent according to self-reported assessment presented elevated BUN levels at the 10th year; however, no significant correlation was found with creatinine levels. These findings suggest that nonadherence may adversely affect renal function over the long term. Previous research has indicated that creatinine levels increase only in advanced allograft damage and have limited sensitivity in detecting early renal damage \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Therefore, although conventional biomarkers are widely used for monitoring posttransplant kidney function, they are not considered sufficient predictors on their own. These two markers should instead be interpreted as complementary indicators, particularly for monitoring progressive graft dysfunction.\u003c/p\u003e \u003cp\u003eWhen the relationships between adherence and demographic or clinical factors, no significant associations were examined with sex, age, type of chronic disease, donor type, or donor relationship. This finding is consistent with those of previous studies \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. However, the observation that female patients presented higher tacrolimus levels at the seventh year suggests that such variables may differ contextually. This difference may be related to mediating factors such as educational level, health literacy, or social support. In addition, variations in assessment methods may also contribute to this relationship; therefore, further studies utilizing standardized approaches are needed to clarify this relationship more accurately.\u003c/p\u003e \u003cp\u003eThe finding that individuals experiencing rejection report lower MA highlights the direct impact of nonadherence on clinical outcomes. This finding also suggests that past complications may create psychological effects in patients, further weakening adherence behavior. Therefore, adherence should be regularly assessed over time in all patients to identify potential nonadherence issues and implement timely, appropriate interventions \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, the data were obtained retrospectively from medical records only, and self-reported adherence was assessed at a single time point. Second, the study was conducted at a single center with a relatively limited sample size, potentially restricting the generalizability of the findings. Third, the use of self-reported measures may be susceptible to social desirability bias, possibly resulting in overestimation of actual adherence levels. Finally, psychosocial variables were not evaluated, and detailed adherence-related factors, such as medication timing, were not assessed.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study provides a comprehensive analysis of long-term immunosuppressive drug adherence among KTRs by integrating biological and self-reported assessment methods, and including long-term follow up data. The findings indicate fluctuations in adherence levels over a ten-year posttransplant period, with self-reported adherence appearing high, whereas biological indicators suggest lower adherence. The difference between these two assessment methods underscores the necessity of multidimensional evaluation approaches. Furthermore, significantly lower adherence scores in individuals with a history of rejection indicate that nonadherence behaviors have a direct impact on clinical outcomes. In conclusion, the findings suggest that MA may fluctuate over time, that the use of complementary assessment methods is essential, and that nonadherence behaviors can directly influence clinical outcomes. Therefore, regular assessment of MA via multidimensional approaches in long-term transplant recipients is recommended, as this strategy may effectively improve both graft and patient survival. Future multicenter studies employing standardized and multidimensional adherence assessment methods are warranted to provide a more comprehensive understanding of the complex nature of adherence.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eITAS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eImmunosuppressive Therapy Adherence Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBUN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBlood urea nitrogen\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKTR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKidney transplant recipient\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMedication adherence\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll transplanted organs were obtained through legally approved donation procedures in accordance with national regulations and international ethical standards. The authors declare that no organs were obtained from prisoners or other institutionalized individuals. Informed consent was obtained from all the participants prior to data collection for self-reported assessment. The Dokuz Eylul University Non-Invasive Research Ethics Committee (Approval no: 2023/17-08, Date: May 24, 2023) at the authors\u0026rsquo; institution approved the study protocol.\u0026nbsp;The study adhered to the ethical principles of the Helsinki Declaration and strictly protected patient confidentiality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe datasets generated or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not receive any specific grant or funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYSO and HTD jointly contributed to the conceptualization of the study. Formal analysis, writing-review and editing, and project administration were performed by YSO and BSS. The original draft of the manuscript was prepared by YSO and BSS. Data curation was conducted by SA and HTD. Visualization was carried out by BSS, and resources were provided by SA and BSS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the participants who voluntarily participated in the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLieber SR, Helcer J, Shemesh E. Monitoring drug adherence. Trans plant Rev (Orlando). 2015;29(2):73\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu Y, Zhou Y, Zhang L, Zhang J, Lin J. Efficacy of interventions for adherence to the immunosuppressive therapy in kidney transplant recipients: a meta-analysis and systematic review. J Investig Med. 2017;65(7):1049\u0026ndash;56. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/jim-2016-000265\u003c/span\u003e\u003cspan address=\"10.1136/jim-2016-000265\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTorres-Guti\u0026eacute;rrez M, Lozano-Su\u0026aacute;rez N, Burgos-Camacho VA, et al. Is Non-Adherence Associated with Adverse Outcomes in Kidney Transplant Recipients? The Role of Non-Adherence as a Risk and Predictor Factor for Graft Loss and Death. Patient Prefer Adherence. 2023;17:2915\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2147/PPA.S436833\u003c/span\u003e\u003cspan address=\"10.2147/PPA.S436833\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGandolfini I, Palmisano A, Fiaccadori E, Cravedi P, Maggiore U. Detecting, preventing and treating non-adherence to immunosuppression after kidney transplantation. Clin Kidney J. 2022;15(7):1253\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGokoel SRM, Gombert-Handoko KB, Zwart TC, van der Boog PJM, Moes DJAR, de Fijter JW. Medication non-adherence after kidney transplantation: A critical appraisal and systematic review. Transpl Rev (Orlando). 2020;34(1):100511. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.trre.2019.100511\u003c/span\u003e\u003cspan address=\"10.1016/j.trre.2019.100511\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCorr M, Walker A, Maxwell AP, McKay GJ. Non-adherence to immunosuppressive medications in kidney transplant recipients- a systematic scoping review. Transpl Rev (Orlando). 2025;39(1):100900. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.trre.2024.100900\u003c/span\u003e\u003cspan address=\"10.1016/j.trre.2024.100900\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBelaiche S, D\u0026eacute;caudin B, Dharancy S, Noel C, Odou P, Hazzan M. Factors relevant to medication non-adherence in kidney transplant: a systematic review. Int J Clin Pharm. 2017;39(3):582\u0026ndash;93. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11096-017-0436-4\u003c/span\u003e\u003cspan address=\"10.1007/s11096-017-0436-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLorenz EC, Smith BH, Cosio FG, Schinstock CA, Shah ND, Groehler PN, Verdick JS, Park WD, Stegall MD. Long-retm immunosupprssion adherence after kidney transplant and relationship to allograft histology. Tranpslantation Direct. 2018;4:e392. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/TXD.0000000000000824\u003c/span\u003e\u003cspan address=\"10.1097/TXD.0000000000000824\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnghel LA, Farcas AM, Oprean RN. An overview of the common methods used to measure treatment adherence. Med Pharm Rep. 2019;92(2):117\u0026ndash;22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.15386/mpr-1201\u003c/span\u003e\u003cspan address=\"10.15386/mpr-1201\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSarıg\u0026ouml;l Ordin Y, Karayurt O, Ertan N, Yıldız S. B\u0026ouml;brek nakli alıcılarında imm\u0026uuml;nosupresif tedaviye uyumun farklı y\u0026ouml;ntemlerle değerlendirilmesi. Turk Neph Dial Transpl. 2018;27(3):254\u0026ndash;61. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5262/tndt.2018.3147\u003c/span\u003e\u003cspan address=\"10.5262/tndt.2018.3147\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Geest S, Ribaut J, Denhaerynck K, Dobbels F. Adherence management in transplantation. In: Daniel C, Scott DC, Paul LK, editors. Psychosocial aspects of chronic kidney disease. Academic Press. 2021;409\u0026ndash;448. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/B978-0-12-817080-9.00019-1\u003c/span\u003e\u003cspan address=\"10.1016/B978-0-12-817080-9.00019-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVilleneuve C, Rousseau A, Rerolle JP, et al. Adherence profiles in kidney transplant patients: Causes and consequences. Patient Educ Couns. 2020;103(1):189\u0026ndash;98. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.pec.2019.08.002\u003c/span\u003e\u003cspan address=\"10.1016/j.pec.2019.08.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu H, Shang Y, Du C, Wu S. Immunosuppressive Medication Adherence and its Associated Factors in Renal Transplant Recipients. Transplantation. 2018;102:S68. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/01.tp.0000542646.11124.c8\u003c/span\u003e\u003cspan address=\"10.1097/01.tp.0000542646.11124.c8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGibson TB. A dynamic analysis of medication adherence. J managed care specialty Pharm. 2022;28(12):1392\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.18553/jmcp.2022.28.12.1392\u003c/span\u003e\u003cspan address=\"10.18553/jmcp.2022.28.12.1392\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLorenz EC, Egginton JS, Stegall MD, et al. Patient experience after kidney transplant: a conceptual framework of treatment burden. J Patient Rep Outcomes. 2019;3:8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s41687-019-0095-4\u003c/span\u003e\u003cspan address=\"10.1186/s41687-019-0095-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChisholm MA, Lance CE, Williamson GM, Mulloy LL. Development and validation of the immunosuppressant therapy adherence instrument (ITAS). Patient Educ Couns. 2005;59(1):13\u0026ndash;20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.pec.2004.09.007\u003c/span\u003e\u003cspan address=\"10.1016/j.pec.2004.09.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLow JK, Crawford K, Manias E, Walker R. Quantifying the medication burden of kidney transplant recipients in the first year post-transplantation. Int J Clin Pharm. 2018;40(6):1242\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11096-018-0678-9\u003c/span\u003e\u003cspan address=\"10.1007/s11096-018-0678-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTecen-Yucel K, Bayraktar-Ekincioglu A, Yıldırım T, Demirkan K, Erdem Y. Assessment of adherence to immunosuppressive treatment in kidneytransplant patients: A descriptive study. Turk J Nephrol. 2023;32(3):241\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLalić J, Veličković-Radovanović R, Mitić B, Paunović G, Cvetković T. Immunosuppressive medication adherence in kidney transplant patients. Med Princ Pract. 2014;23(4):351\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1159/000362792\u003c/span\u003e\u003cspan address=\"10.1159/000362792\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRussell CL, Ashbaugh C, Peace L, et al. Time-in-a-bottle (TIAB): a longitudinal, correlational study of patterns, potential predictors, and outcomes of immunosuppressive medication adherence in adult kidney transplant recipients. Clin Transpl. 2013;27(5):E580\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTatoğlu N, Karayurt \u0026Ouml;, \u0026Ouml;ğce F. Factors affecting adherence of recipients to immunosuppressive therapy after liver and kidney transplantation. J Educ Res Nurs. 2023;20(1):20\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZachciał J, Uchmanowicz I, Krajewska M, Banasik M. Adherence to Immunosuppressive Therapies after Kidney Transplantation from a Biopsychosocial Perspective: A Cross-Sectional Study. J Clin Med. 2022;11(5):1381. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/jcm11051381\u003c/span\u003e\u003cspan address=\"10.3390/jcm11051381\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBendersky VA, Saha A, Sidoti CN, et al. Factors impacting the medication Adherence Landscape for transplant patients. Clin Transpl. 2023;37:e14962. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/ctr.14962\u003c/span\u003e\u003cspan address=\"10.1111/ctr.14962\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScheel J, Reber S, Stoessel L, Waldmann E, Jank S, Eckardt KU, et al. Patient-reported non-adherence and immunosuppressant trough levels are associated with rejection after renal transplantation. BMC Nephrol. 2017;18(1):107. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12882-017-0517-6\u003c/span\u003e\u003cspan address=\"10.1186/s12882-017-0517-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLieb M, Hepp T, Schiffer M, et al. Accuracy and concordance of measurement methods to assess non-adherence after renal transplantation - a prospective study. BMC Nephrol. 2020;21:114. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12882-020-01781-1\u003c/span\u003e\u003cspan address=\"10.1186/s12882-020-01781-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHerblum J, Dacouris N, Huang M, et al. Retrospective Analysis of Tacrolimus Intrapatient Variability as a Measure of Medication Adherence. Can J Kidney Health Disease. 2021;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/20543581211021742\u003c/span\u003e\u003cspan address=\"10.1177/20543581211021742\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSalvadori M, Tsalouchos A. Biomarkers in renal transplantation: An updated review. World J Transpl. 2017;7(3):161\u0026ndash;78. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5500/wjt.v7.i3.161\u003c/span\u003e\u003cspan address=\"10.5500/wjt.v7.i3.161\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMelilli E, D\u0026iacute;az MI, Gomis-Pastor M, et al. Predictors of Treatment Adherence in Kidney Transplant Patients: A Systematic Review of the Literature. J Clin Med. 2025;14(5):1622. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/jcm14051622\u003c/span\u003e\u003cspan address=\"10.3390/jcm14051622\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"biological monitoring, follow-up studies, kidney transplantation, immunosuppressive agents, medication adherence, self report","lastPublishedDoi":"10.21203/rs.3.rs-8419420/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8419420/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThis study aims to determine the course of immunosuppressive medication adherence (MA) in individuals who have undergone kidney transplantation for over a decade and to identify the demographic and clinical factors affecting this adherence.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective and cross-sectional descriptive study evaluated the biological adherence of 103 kidney transplant recipients (KTRs) at 12 different time points using tacrolimus and cyclosporine blood levels. Self-reported adherence was assessed via the immunosuppresive therapy adherence. Associations between adherence and demographic and clinical variables were also analyzed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe mean time since transplantation was 11.77\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46 years. Biologically, 43.3% of patients had low MA. In contrast, self-reported adherence was 82.52%. No statistically significant correlation was found between biological and self-reported adherence outcomes. Patients with low biological adherence presented increased blood urea nitrogen (BUN) levels at 6 months and 9 years post-transplant. Similarly, patients with low self-reported adherence had increased BUN levels at 10 years. Self-reported adherence scores were significantly lower among patients with a history of graft rejection (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). No significant associations were found between MA and variables such as sex, donor type, or age (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eImmunosuppressive MA in KTRs may fluctuate over time, and varies according to the assessment method. The combined and time-consuming use of biological and self-reported measurements may contribute to a more accurate determination of the risk of non-adherence. Individualized follow-up and support programs should be developed, taking into account the multidimensional factors that influence adherence.\u003c/p\u003e","manuscriptTitle":"Evaluation of Medication Adherence Over a Decade Following Kidney Transplantation: Integration of Biological and Self-Reported Data","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-12 15:56:54","doi":"10.21203/rs.3.rs-8419420/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-31T22:32:35+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-31T22:27:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-31T07:54:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-23T04:38:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"255751307245703739816687987603487903482","date":"2026-01-10T07:28:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"157775456255674483765069285593729699","date":"2026-01-08T06:43:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"326654374719724672981760339357975846412","date":"2026-01-08T05:53:38+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-08T05:20:17+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-27T16:25:24+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-27T16:22:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-24T21:31:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nephrology","date":"2025-12-24T21:27:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f9437cba-cff5-498d-a4d4-66b634856e03","owner":[],"postedDate":"January 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-28T09:23:54+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-12 15:56:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8419420","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8419420","identity":"rs-8419420","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}