ReviewMolecular diagnosis & therapy2012
Pharmacogenetics in kidney transplantation: recent updates and potential clinical applications.
Review in Molecular diagnosis & therapy, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Whole-Exome Sequencing Followed by dPCR-Based Personalized Genetic Approach in Solid Organ Transplantation: A Study Protocol and Preliminary Results.Methods and protocols · 2025Article
- Drug-induced Fanconi syndrome in patients with kidney allograft transplantation.Frontiers in immunology · 2022Article
- Personalizing initial calcineurin inhibitor dosing by adjusting to donor CYP3A-status in liver transplant patients.British journal of clinical pharmacology · 2015Article
- Pharmacogenetics and drug-induced nephrotoxicity in renal transplant recipients.BioImpacts : BI · 2015Review
- Clinical implementation of pharmacogenetics in kidney transplantation: calcineurin inhibitors in the starting blocks.British journal of clinical pharmacology · 2014Review
- The role of pharmacogenetics in the disposition of and response to tacrolimus in solid organ transplantation.Clinical pharmacokinetics · 2014Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Every month, new releases on the relationship between pharmacogenetic biomarkers and immunosuppressive drug therapy in kidney transplantation are published. However, the systematic clinical application of these discoveries occurs at a very slow pace, and the usefulness of knowing a patient's genotype remains an important matter of debate. This can be partially ascribed to the lack of consistency when looking at the different associations reported across several studies but also the need for a broad-spectrum view and a rigorous analysis of the relevance of the different associations observed to date. For that purpose, we performed a comprehensive analysis of the strength of the different reported genetic associations, and in this article we discuss their potential for clinical implementation in kidney transplantation. For tacrolimus, it is likely that a genotype-based drug dosage can benefit patient outcome, while for ciclosporin A, the data appear less convincing. For the mammalian target of rapamycin inhibitors, sirolimus and everolimus - given the lack of data and the absence of large prospective studies - it is premature to implement pharmacogenetics, but some novel and promising leads have recently been reported. For mycophenolate mofetil, the complex metabolic pathways of its active moiety, mycophenolic acid, complicate analysis of the various published associations. However, at present, some interesting findings can be highlighted and offer potential value to assist clinicians in decision making.
Indexed as
Identifiers
23192462What OpenQuestion holds
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.