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Record W2125018526 · doi:10.1345/aph.1k628

Corticosteroid Interactions with Cyclosporine, Tacrolimus, Mycophenolate, and Sirolimus: Fact or Fiction?

2008· article· en· W2125018526 on OpenAlexaff
Stefanie Lam, N. Partovi, Mary H. H. Ensom

Bibliographic record

VenueAnnals of Pharmacotherapy · 2008
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTacrolimusMedicineSirolimusMycophenolatePharmacologyMycophenolic acidCalcineurinDrug interactionCYP3A4CorticosteroidImmunosuppressive drugTrough levelOrgan transplantationTransplantationDrugInternal medicineCytochrome P450Metabolism

Abstract

fetched live from OpenAlex

OBJECTIVE: To review the current clinical evidence on the effects of corticosteroid interactions with the immunosuppressive drugs cyclosporine, tacrolimus, mycophenolate, and sirolimus. DATA SOURCES: Articles were retrieved through MEDLINE (1966-February 2008) using the terms corticosteroids, glucocorticoids, immunosuppressants, cyclosporine, tacrolimus, mycophenolate, sirolimus, drug interactions, CYP3A4, P-glycoprotein, and UDP-glucuronosyltransferases. Bibliographies were manually searched for additional relevant articles. STUDY SELECTION AND DATA EXTRACTION: All English-language studies dealing with drug interactions between corticosteroids and cyclosporine, tacrolimus, mycophenolate, and sirolimus were reviewed. DATA SYNTHESIS: Corticosteroids share common metabolic and transporter pathways, the cytochrome P450 and P-glycoprotein (P-gp/ABCB1) systems, respectively, with cyclosporine, tacrolimus, and sirolimus. As a group, corticosteroids induce the CYP3A4 and P-gp pathways; however, a few exceptions exist and the impact on a patient's immunosuppressant regimen may be critical. Corticosteroids also have demonstrated an induction effect on the uridine diphosphate-glucuronosyltransferase enzymes and multidrug resistance-associated protein 2 involved in mycophenolate's disposition. Successful corticosteroid withdrawal regimens have been reported; however, only few studies have examined the effects of steroid withdrawal on the remaining immunosuppressive regimens. To date, the clinical impact of steroid withdrawal on disposition of other immunosuppressive agents is not well characterized, and reports of such drug-drug interactions are conflicting. CONCLUSIONS: While our understanding of the clinical impact of steroid-immunosuppressant interactions is limited, it remains a fact that corticosteroids have complex induction and inhibition interactions with common metabolic and transport pathways. Given the complex interaction of corticosteroids on crucial metabolic enzymes and transporter proteins, monitoring of immunosuppressive agents during steroid withdrawal is warranted to ensure optimal treatment outcomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.796

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.093
GPT teacher head0.390
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations93
Published2008
Admission routes1
Has abstractyes

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