Comparison of different methods to assess tacrolimus concentration intra-patient variability as potential marker of medication non-adherence
Status PubMed-not-MEDLINE Jazyk angličtina Země Švýcarsko Médium electronic-ecollection
Typ dokumentu časopisecké články
PubMed
36313323
PubMed Central
PMC9609782
DOI
10.3389/fphar.2022.973564
PII: 973564
Knihovny.cz E-zdroje
- Klíčová slova
- immunosuppression, intra-patient variability, kidney transplantation, medication adherence, tacrolimus, tacrolimus immunosuppression,
- Publikační typ
- časopisecké články MeSH
Background and objective: Non-adherence to tacrolimus commonly manifests as low drug concentrations and/or high intra-patient variability (IPV) of concentrations across multiple measurements. We aimed to compare several methods of tacrolimus IPV calculation and evaluate how well each reflects blood concentration variation due to medication non-adherence in kidney transplant recipients. Methods: This Czech single-center retrospective longitudinal study was conducted in 2019. All outpatients ≥18 years of age, ≥3 months post-transplant, and on tacrolimus-based regimens were approached. After collecting seven consecutive tacrolimus concentrations we asked participating patients to self-report adherence to immunosuppressants (BAASIS© scale). The IPV of tacrolimus was calculated as the medication level variability index (MLVI), the coefficient of variation (CV), the time-weighted CV, and via nonlinearly modeled dose-corrected trough levels. These patient-level variables were analyzed using regression analysis. Detected nonlinearities in the dose-response curve were controlled for by adding tacrolimus dosing and its higher-order terms as covariates, along with self-reported medication adherence levels. Results: Of 243 patients using tacrolimus, 42% (n = 102) reported medication non-adherence. Non-adherence was associated with higher CVs, higher time-weighted CVs, and lower dose-corrected nonlinearly modeled trough levels; however, it was not associated with MLVIs. All of the significant operationalizations suggested a weak association that was similar across the applied methods. Discussion and conclusion: Implementation non-adherence was reflected by higher CV or time-weighted CV and by lower blood concentrations of tacrolimus. As an additional tool for identifying patients at risk for non-adherence, simple IPV calculations incorporated into medical records should be considered in everyday clinical practice.
Zobrazit více v PubMed
Butler J. A., Roderick P., Mullee M., Mason J. C., Peveler R. C. (2004). Frequency and impact of nonadherence to immunosuppressants after renal transplantation: A systematic review. Transplantation 77 (5), 769–776. 10.1097/01.tp.0000110408.83054.88 PubMed DOI
De Geest S., Burkhalter H., Bogert L., Berben L., Glass T. R., Denhaerynck K., et al. (2014). Psychosocial interest Group, and Swiss transplant cohort StudyDescribing the evolution of medication nonadherence from pretransplant until 3 years post-transplant and determining pretransplant medication nonadherence as risk factor for post-transplant nonadherence to immunosuppressives: The Swiss transplant cohort study. Transpl. Int. 27 (7), 657–666. 10.1111/tri.12312 PubMed DOI
De Geest S., Ribaut J., Denhaerynck K., Dobbels F. (2021). “Adherence management in transplantation”, in Psychosocial aspects of chronic kidney disease: Exploring the impact of ckd, dialysis, and transplantation on patients. Editors Cukor D., Cohen S. D., Kimmel P. L. (Elsevier; ), 409–450.
Dobbels F., Berben L., De Geest S., Drent G., Lennerling A., Whittaker C., et al. Transplant360 Task Force (2010). The psychometric properties and practicability of self-report instruments to identify medication nonadherence in adult transplant patients: A systematic review. Transplantation 90 (2), 205–219. 10.1097/TP.0b013e3181e346cd PubMed DOI
Eliasson L., Clifford S., Mulick A., Jackson C., Vrijens B. (2020). How the EMERGE guideline on medication adherence can improve the quality of clinical trials. Br. J. Clin. Pharmacol. 86 (4), 687–697. 10.1111/bcp.14240 PubMed DOI PMC
Foster B. J., Pai A., Zelikovsky N., Amaral S., Bell L., Dharnidharka V. R., et al. (2018). A randomized trial of a multicomponent intervention to promote medication adherence: The teen adherence in kidney transplant effectiveness of intervention trial (TAKE-IT). Am. J. Kidney Dis. 72 (1), 30–41. 10.1053/j.ajkd.2017.12.012 PubMed DOI PMC
Gonzales H. M., McGillicuddy J. W., Rohan V., Chandler J. L., Nadig S. N., Dubay D. A., et al. (2020). A comprehensive review of the impact of tacrolimus intrapatient variability on clinical outcomes in kidney transplantation. Am. J. Transpl. 20 (8), 1969–1983. 10.1111/ajt.16002 PubMed DOI PMC
Gustavsen M. T., Midtvedt K., Lønning K., Jacobsen T., Reisaeter A. V., De Geest S., et al. (2019). Evaluation of tools for annual capture of adherence to immunosuppressive medications after renal transplantation - a single-centre open prospective trial. Transpl. Int. 32 (6), 614–625. 10.1111/tri.13412 PubMed DOI
Heemann U., Viklicky O. (2017), Is trough level variability the new tool for identifying patients at risk for rejection after transplantation? Nephrol. Dial. Transplant. official publication of the European Dialysis and Transplant Association - European Renal Association, 32. 214–215. 10.1093/ndt/gfw447 PubMed DOI
Herblum J., Dacouris N., Huang M., Zaltzman J., Prasad G. V. R., Nash M., et al. (2021). Retrospective analysis of tacrolimus intrapatient variability as a measure of medication adherence. Can. J. Kidney Health Dis. 8, 20543581211021742. 10.1177/20543581211021742 PubMed DOI PMC
Kidney Disease: Improving Global Outcomes (KDIGO) Transplant Work Group (2009). KDIGO clinical practice guideline for the care of kidney transplant recipients. Am. J. Transpl. 9, S1–S155. 10.1111/j.1600-6143.2009.02834.x PubMed DOI
Kim J., Wilson S., Undre N. A., Shi F., Kristy R. M., Schwartz J. J. (2019). A novel, dose-adjusted tacrolimus trough-concentration model for predicting and estimating variance after kidney transplantation. Drugs R. D. 19 (2), 201–212. 10.1007/s40268-019-0271-2 PubMed DOI PMC
Kostalova B., Mala-Ladova K., Kubena A. A., Horne R., Dusilova Sulkova S., Maly J. (2021). Changes in beliefs about post-transplant immunosuppressants over time and its relation to medication adherence and kidney graft dysfunction: A follow-up study. Patient prefer. Adherence 15, 2877–2887. 10.2147/PPA.S344878 PubMed DOI PMC
Kuypers D. (2020). Intrapatient variability of tacrolimus exposure in solid organ transplantation: A novel marker for clinical outcome. Clin. Pharmacol. Ther. 107 (2), 347–358. 10.1002/cpt.1618 PubMed DOI
Mo H., Kim S. Y., Min S., Han A., Ahn S., Min S. K., et al. (2019). Association of intrapatient variability of tacrolimus concentration with early deterioration of chronic histologic lesions in kidney transplantation. Transplant. direct 5 (6), e455. 10.1097/TXD.0000000000000899 PubMed DOI PMC
Neuberger J. M., Bechstein W. O., Kuypers D. R., Burra P., Citterio F., De Geest S., et al. (2017). Practical recommendations for long-term management of modifiable risks in kidney and liver transplant recipients: A guidance report and clinical checklist by the consensus on managing modifiable risk in transplantation (commit) group. Transplantation 101 (4S Suppl 2), S1–S56. 10.1097/TP.0000000000001651 PubMed DOI
Rozen-Zvi B., Schneider S., Lichtenberg S., Green H., Cohen O., Gafter U., et al. (2017)., Association of the combination of time-weighted variability of tacrolimus blood level and exposure to low drug levels with graft survival after kidney transplantation. Nephrol. Dial. Transplant. official publication of the European Dialysis and Transplant Association - European Renal Association, 32. 393–399. 10.1093/ndt/gfw394 PubMed DOI
Schumacher L., Leino A. D., Park J. M. (2021). Tacrolimus intrapatient variability in solid organ transplantation: A multiorgan perspective. Pharmacotherapy 41 (1), 103–118. 10.1002/phar.2480 PubMed DOI
Shemesh E., Bucuvalas J. C., Anand R., Mazariegos G. V., Alonso E. M., Venick R. S., et al. (2017). The medication level variability index (MLVI) predicts poor liver transplant outcomes: A prospective multi-site study. Am. J. Transpl. 17 (10), 2668–2678. 10.1111/ajt.14276 PubMed DOI PMC
Shneider C., Dunphy C., Shemesh E., Annunziato R. A. (2018). Assessment and treatment of nonadherence in transplant recipients. Gastroenterol. Clin. North Am. 47 (4), 939–948. 10.1016/j.gtc.2018.07.015 PubMed DOI
Shuker N., Shuker L., van Rosmalen J., Roodnat J. I., Borra L. C., Weimar W., et al. (2016). A high intrapatient variability in tacrolimus exposure is associated with poor long-term outcome of kidney transplantation. Transpl. Int. 29 (11), 1158–1167. 10.1111/tri.12798 PubMed DOI
Shuker N., van Gelder T., Hesselink D. A. (2015). Intra-patient variability in tacrolimus exposure: Causes, consequences for clinical management. Transpl. Rev. 29 (2), 78–84. 10.1016/j.trre.2015.01.002 PubMed DOI
Solomon S., Colovai A., Del Rio M., Hayde N. (2020). Tacrolimus variability is associated with de novo donor-specific antibody development in pediatric renal transplant recipients. Pediatr. Nephrol. 35 (2), 261–270. 10.1007/s00467-019-04377-6 PubMed DOI
Vankova B., Mala-Ladova K., Kubena A., Maly J., Sulkova S. D. (2018). Immunosuppressive therapy related adherence, beliefs and self-management in kidney transplant outpatients. Patient Prefer Adherence 12, 2605–2613. 10.2147/PPA.S184166 PubMed DOI PMC
Vrijens B., De Geest S., Hughes D. A., Przemyslaw K., Demonceau J., Ruppar T., et al. ABC Project Team (2012). A new taxonomy for describing and defining adherence to medications. Br. J. Clin. Pharmacol. 73 (5), 691–705. 10.1111/j.1365-2125.2012.04167.x PubMed DOI PMC
Psychometric Properties of the BAASIS: A Meta-analysis of Individual Participant Data