Evidence map›Paper›PMID 40315256›Full record

Observational studyTherapeutic drug monitoring2025

Simultaneous Prediction of Area Under the Curves of Mycophenolic Acid and Its Metabolites and Enterohepatic Recirculation in Kidney Transplant Recipients.

Moataz E Mohamed, Abdelrahman Saqr, Guillaume Onyeaghala, Rory P Remmel, Christopher Staley, Casey R Dorr, Levi Teigen, Weihua Guan, Henry Madden, Julia Munoz and 7 more

Registry-linked trialAbstract readMulticenter StudyObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in Therapeutic drug monitoring, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04953715 (Microbiome and Immunosuppression), which is not on this map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04953715 active not recruitingnot on this map

Microbiome and Immunosuppression: The Mission Study

TypeobservationalSponsorThe University of Texas Medical Branch, GalvestonRan2020 to 2033Enrolled140ConditionsKidney Transplant Rejection, Kidney TransplantArmscollection of body microbiome
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Moataz E MohamedDepartment of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota.ORCID 0000-0002-7266-9980
Abdelrahman SaqrDepartment of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota.
Guillaume OnyeaghalaDivision of Nephrology, University of Texas Medical Branch, Galveston, Texas.
Rory P RemmelDepartment of Medicinal Chemistry, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota.
Christopher StaleyDepartment of Surgery, School of Medicine, University of Minnesota, Minneapolis, Minnesota.
Casey R DorrDepartment of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota.
Levi TeigenDepartment of Food Science and Nutrition, University of Minnesota, St. Paul, Minnesota.
Weihua GuanDivision of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, Minnesota.
Henry MaddenDepartment of Surgery, Clinical Trials Office, University of Minnesota, Minneapolis, Minnesota; and.
Julia MunozDepartment of Surgery, Clinical Trials Office, University of Minnesota, Minneapolis, Minnesota; and.
Bryan SanchezDivision of Nephrology, University of Texas Medical Branch, Galveston, Texas.
Duy VoDivision of Nephrology, University of Texas Medical Branch, Galveston, Texas.
Rasha El-RifaiDivision of Nephrology and Hypertension, School of Medicine, University of Minnesota, Minneapolis, Minnesota.
William S OettingDepartment of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota.
Arthur J MatasDepartment of Surgery, School of Medicine, University of Minnesota, Minneapolis, Minnesota.
Ajay K IsraniDivision of Nephrology, University of Texas Medical Branch, Galveston, Texas.
Pamala A JacobsonDepartment of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota.ORCID 0000-0002-4145-7045

Funding

University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UM1TR004405 · NCATS · UNIVERSITY OF MINNESOTA · PI Bruce R Blazar, Damien A Fair · 2023 to 2026
$30.8M
Gut Microbiota and Effect on Immune Suppressants in TransplantationR01AI140303 · NIAID · UNIVERSITY OF TEXAS MED BR GALVESTON · PI ISRANI, AJAY K, JACOBSON, PAMALA A · 2019 to 2024
$3.6M
NCATS NIH HHS UM1 TR004405NIAID NIH HHS R01 AI140303
6 · The paper itself

Abstract

backgroundTherapeutic drug monitoring of mycophenolic acid (MPA) is limited due to the requirement for intensive pharmacokinetic sampling to assess the area under the curve (AUC). Limited sampling strategies (LSS) offer a practical alternative; however, enterohepatic recirculation (EHR) affects prediction accuracy and precision. This study is the first to develop LSS models capable of simultaneously predicting the AUC of MPA, its metabolites [mycophenolic acid glucuronide (MPAG) and acyl mycophenolic acid glucuronide (Acyl-MPAG)], and MPA EHR in kidney transplant recipients (KTRs).

methodsIntensive pharmacokinetic sampling was conducted in 84 adult KTRs receiving mycophenolate mofetil. MPA AUC 0-12 was calculated, and MPA EHR was determined. During the development of the LSS models, a balanced representation of patients with high and low EHR was ensured. Multiple linear regression was used to develop AUC prediction models for MPA, MPAG, and Acyl-MPAG, as well as an EHR prediction model. The best models were selected based on prediction performance, the highest prediction concordance, and the shortest interval between the first and last samples.

resultsThree models for AUC 0-12 prediction were identified, incorporating 4, 5, and 6 concentration timepoints. The LSS model with 6 concentrations demonstrated the best performance, with excellent prediction concordance (100% for MPA and MPAG, and 93% for Acyl-MPAG). The EHR prediction model included 4 concentrations and exhibited an ∼80% prediction concordance. An online calculator was developed for these models.

conclusionsThe developed LSS models simultaneously predict MPA, MPAG, and Acyl-MPAG AUC 0-12 using the same timepoints with high accuracy and precision. MPA EHR can be predicted using 4 concentration timepoints. The inclusion of late concentration timepoints is essential for the high predictive performance of LSS models. CLINICAL TRIAL NOTATION: clinicaltrials.gov, NCT04953715.

Indexed as

Enterohepatic CirculationImmunosuppressive AgentsKidney TransplantationMycophenolic AcidAdultAgedArea Under CurveDrug MonitoringFemaleGlucuronidesHumansMaleMiddle AgedTransplant RecipientsGlucuronidesImmunosuppressive AgentsMycophenolic Acidmycophenolic acid glucuronideAcyl-MPAGkidney transplantlimited sampling strategyMPAGmycophenolate mofetilmycophenolic acidtherapeutic drug monitoring

Identifiers

PMID40315256
PMCPMC12871475

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.