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      Clinical Utility of the OmniGraf Biomarker Panel in the Care of Kidney Transplant Recipients (CLARITY): Protocol for a Prospective, Multisite Observational Study

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          Abstract

          Background

          Death with a functioning allograft has become the leading category of graft loss in kidney transplant recipients at all time points. Previous analyses have demonstrated that causes of death in kidney transplant recipients are predominated by comorbidities strongly associated with immunosuppressant medications. Adverse drug events (ADEs) have been strongly associated with nonadherence, health care utilization, and graft loss; clinicians face a difficult decision on whether making immunosuppressant adjustments in the face of ADEs will improve symptomology or simply increase the risk of acute rejection. Clinicians also face a treatment quandary in 50% of kidney transplant recipients with stage 3 or worse chronic kidney disease at 1 year post transplantation, as progressive decline in renal function has been strongly associated with inferior allograft survival.

          Objective

          The primary objective of the CLinical Utility of the omnigrAf biomarkeR Panel In The Care of kidneY Transplant Recipients (CLARITY) trial is to evaluate change in renal function over time in kidney transplant recipients who are undergoing OmniGraf monitoring in conjunction with monitoring of their medication-related symptom burden (MRSB). A secondary objective of this study is to identify the impact of OmniGraf use in conjunction with patient-reported MRSB as part of clinical care on patients’ self-efficacy and quality of life.

          Methods

          CLARITY is a 3-year prospective, multisite, observational study of 2000 participants with a matched control, measuring the impact of real-time patients’ MRSB and the OmniGraf biomarker panel on change in renal function over time. Secondary outcome measures include the Patient-Reported Outcomes Measurement Information System (PROMIS) Self-Efficacy for Managing Chronic Conditions–Managing Medications and Treatment–Short Form 4a; the PROMIS-29 Profile (version 2.1); the PROMIS Depression Scale, hospitalizations—subcategorized for hospitalizations owing to infections; treated rejections, MRSB, and proportion of participants with overall graft survival at year 3 post transplantation; graft loss or death during the 3-year study follow-up period; and change in provider satisfaction.

          Results

          The primary outcome measure of the study will be a comparison of the slope change in estimated glomerular filtration rate from baseline to the end of follow-up between study participants and a matched control group. Secondary outcome measures include changes over time in PROMIS Self-Efficacy for Managing Chronic Conditions–Managing Medications and Treatment–Short Form 4a, the PROMIS-29 Profile (version 2.1), and PROMIS Depression Scale in the study group, as well as a comparison of hospitalizations and causes, rejections, and graft and patient survival compared between participants and a matched cohort. The anticipated first enrollment in the study is October 2022 with data analysis and publication expected in October 2027.

          Conclusions

          Through this report, we describe the study design, methods, and outcome measures that will be utilized in the ongoing CLARITY trial.

          Trial Registration

          ClinicalTrials.gov NCT05482100; https://clinicaltrials.gov/ct2/show/NCT05482100

          International Registered Report Identifier (IRRID)

          PRR1-10.2196/41020

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          Most cited references20

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          A new equation to estimate glomerular filtration rate.

          Andrew Levey, Lesley Stevens, Christopher H Schmid … (2009)
          Equations to estimate glomerular filtration rate (GFR) are routinely used to assess kidney function. Current equations have limited precision and systematically underestimate measured GFR at higher values. To develop a new estimating equation for GFR: the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. Cross-sectional analysis with separate pooled data sets for equation development and validation and a representative sample of the U.S. population for prevalence estimates. Research studies and clinical populations ("studies") with measured GFR and NHANES (National Health and Nutrition Examination Survey), 1999 to 2006. 8254 participants in 10 studies (equation development data set) and 3896 participants in 16 studies (validation data set). Prevalence estimates were based on 16,032 participants in NHANES. GFR, measured as the clearance of exogenous filtration markers (iothalamate in the development data set; iothalamate and other markers in the validation data set), and linear regression to estimate the logarithm of measured GFR from standardized creatinine levels, sex, race, and age. In the validation data set, the CKD-EPI equation performed better than the Modification of Diet in Renal Disease Study equation, especially at higher GFR (P < 0.001 for all subsequent comparisons), with less bias (median difference between measured and estimated GFR, 2.5 vs. 5.5 mL/min per 1.73 m(2)), improved precision (interquartile range [IQR] of the differences, 16.6 vs. 18.3 mL/min per 1.73 m(2)), and greater accuracy (percentage of estimated GFR within 30% of measured GFR, 84.1% vs. 80.6%). In NHANES, the median estimated GFR was 94.5 mL/min per 1.73 m(2) (IQR, 79.7 to 108.1) vs. 85.0 (IQR, 72.9 to 98.5) mL/min per 1.73 m(2), and the prevalence of chronic kidney disease was 11.5% (95% CI, 10.6% to 12.4%) versus 13.1% (CI, 12.1% to 14.0%). The sample contained a limited number of elderly people and racial and ethnic minorities with measured GFR. The CKD-EPI creatinine equation is more accurate than the Modification of Diet in Renal Disease Study equation and could replace it for routine clinical use. National Institute of Diabetes and Digestive and Kidney Diseases.
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            A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group.

            A S Levey, J P Bosch, J B Lewis … (1999)
            Serum creatinine concentration is widely used as an index of renal function, but this concentration is affected by factors other than glomerular filtration rate (GFR). To develop an equation to predict GFR from serum creatinine concentration and other factors. Cross-sectional study of GFR, creatinine clearance, serum creatinine concentration, and demographic and clinical characteristics in patients with chronic renal disease. 1628 patients enrolled in the baseline period of the Modification of Diet in Renal Disease (MDRD) Study, of whom 1070 were randomly selected as the training sample; the remaining 558 patients constituted the validation sample. The prediction equation was developed by stepwise regression applied to the training sample. The equation was then tested and compared with other prediction equations in the validation sample. To simplify prediction of GFR, the equation included only demographic and serum variables. Independent factors associated with a lower GFR included a higher serum creatinine concentration, older age, female sex, nonblack ethnicity, higher serum urea nitrogen levels, and lower serum albumin levels (P < 0.001 for all factors). The multiple regression model explained 90.3% of the variance in the logarithm of GFR in the validation sample. Measured creatinine clearance overestimated GFR by 19%, and creatinine clearance predicted by the Cockcroft-Gault formula overestimated GFR by 16%. After adjustment for this overestimation, the percentage of variance of the logarithm of GFR predicted by measured creatinine clearance or the Cockcroft-Gault formula was 86.6% and 84.2%, respectively. The equation developed from the MDRD Study provided a more accurate estimate of GFR in our study group than measured creatinine clearance or other commonly used equations.
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              Systematic review: kidney transplantation compared with dialysis in clinically relevant outcomes.

              M. Tonelli, N. Wiebe, G. Knoll … (2011)
              Individual studies indicate that kidney transplantation is associated with lower mortality and improved quality of life compared with chronic dialysis treatment. We did a systematic review to summarize the benefits of transplantation, aiming to identify characteristics associated with especially large or small relative benefit. Results were not pooled because of expected diversity inherent to observational studies. Risk of bias was assessed using the Downs and Black checklist and items related to time-to-event analysis techniques. MEDLINE and EMBASE were searched up to February 2010. Cohort studies comparing adult chronic dialysis patients with kidney transplantation recipients for clinical outcomes were selected. We identified 110 eligible studies with a total of 1 922 300 participants. Most studies found significantly lower mortality associated with transplantation, and the relative magnitude of the benefit seemed to increase over time (p < 0.001). Most studies also found that the risk of cardiovascular events was significantly reduced among transplant recipients. Quality of life was significantly and substantially better among transplant recipients. Despite increases in the age and comorbidity of contemporary transplant recipients, the relative benefits of transplantation seem to be increasing over time. These findings validate current attempts to increase the number of people worldwide that benefit from kidney transplantation. ©2011 The Authors Journal compilation©2011 The American Society of Transplantation and the American Society of Transplant Surgeons.
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                Author and article information

                Contributors
                James N Fleming:
                ORCID: https://orcid.org/0000-0001-9686-3107
                Transplant Genomics, Inc175 Crossing BlvdFramingham, MA, 01702United States1 816 905 4699jamesfleming@eurofins-tgi.com
                Journal
                Journal ID (nlm-ta): JMIR Res Protoc
                Journal ID (iso-abbrev): JMIR Res Protoc
                Journal ID (publisher-id): ResProt
                Title: JMIR Research Protocols
                Publisher: JMIR Publications (Toronto, Canada )
                ISSN (Electronic): 1929-0748
                Publication date Collection: December 2022
                Publication date (Electronic): 14 December 2022
                Volume: 11
                Issue: 12
                Electronic Location Identifier: e41020
                Affiliations
                [1 ] Transplant Genomics, Inc Framingham, MA United States
                Author notes
                Corresponding Author: James N Fleming jamesfleming@ 123456eurofins-tgi.com
                Author information
                https://orcid.org/0000-0001-9686-3107
                https://orcid.org/0000-0002-0222-6586
                https://orcid.org/0000-0001-9799-8361
                https://orcid.org/0000-0002-3340-3282
                https://orcid.org/0000-0002-1381-456X
                https://orcid.org/0000-0003-1133-2644
                https://orcid.org/0000-0003-3289-6967
                https://orcid.org/0000-0002-8638-6738
                https://orcid.org/0000-0001-7607-6085
                https://orcid.org/0000-0002-8288-5732
                Article
                Publisher ID: v11i12e41020
                DOI: 10.2196/41020
                PMC ID: 9798265
                PubMed ID: 36515980
                SO-VID: 1bfa08cf-d316-428d-bf23-f4e438b6b714
                Copyright © ©James N Fleming, Timothy Cober, Janelle Hickey, Leslie Stach, Allison Kawano, Amanda Szczepanik, Alicia Watson, Yuka Imamura, Juston Weems, Patricia West-Thielke. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 14.12.2022.
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on https://www.researchprotocols.org, as well as this copyright and license information must be included.

                History
                Date received : 12 July 2022
                Date revision requested : 8 August 2022
                Date revision received : 23 August 2022
                Date accepted : 30 September 2022
                Categories
                Subject: Protocol
                Subject: Protocol

                Keywords: kidney transplant,biomarker,adverse event,adverse drug event,renal function,egfr,clinical trial,allograft,nephrology,patient outcome,renal,kidney,transplant,observational study,medication monitoring,quality of life,chronic condition,medication management
                Data availability:
                Keywords: kidney transplant, biomarker, adverse event, adverse drug event, renal function, egfr, clinical trial, allograft, nephrology, patient outcome, renal, kidney, transplant, observational study, medication monitoring, quality of life, chronic condition, medication management

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