A prospective cohort conversion study of twice-daily to once-daily extended-release tacrolimus: role of ethnicity
Bibliographic record
Abstract
BACKGROUND: Tacrolimus is a widely used calcineurin inhibitor in kidney transplantation. It is available as twice-daily Prograf® (Tac-BID) and once-daily Advagraf® (Tac-OD). Although therapeutically equivalent, some patients require dose adjustments to achieve similar trough concentrations [C0] after conversion. Tacrolimus exposure is affected by ethnicity in the de novo setting but the role of ethnicity in determining dose requirements and adjustments after conversion is unknown. METHODS: In this study, 496 renal transplant recipients (RTRs) were prospectively converted from Tac-BID to Tac-OD, with dose adjustments targeted to achieve similar [C0] at 12 months post-conversion. Renal function, acute rejection and Tac dose adjustments by ethnicity were analyzed. RESULTS: There were similar numbers of recipients from living and deceased donors. The mean transplant duration was 7 years. Of the RTRs, 60% were Caucasian and 40% were identified as belonging to an ethnic minority. There was no change in estimated renal function (eGFR) post-conversion to Tac-OD. At 12 months, 35/488 (7%) RTRs were receiving a reduced dose, 101/488 (21%) required a dose increase of which 77 (16%) were receiving at least a 30% increase in dose over baseline. The percentage of those in ethnic groups requiring a dose increase of >30% varied from 8.0% for South Asians to 27.5% for East Asians (P = 0.03), despite East Asians having a similar baseline dose of Tac-BID (3.59 mg/day) compared to the entire cohort (3.53 mg/day). CONCLUSIONS: Ethnicity may play an important role in dosing requirements when converting from Tac-BID to Tac-OD, unrelated to baseline dose. Further investigation is required to determine the reasons for ethnic variability when patients are converted between tacrolimus preparations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".