VARIATIONS IN TACROLIMUS WHOLE BLOOD CONCENTRATIONS DURING PREGNANCY AND ITS IMPLICATIONS FOR THERAPEUTIC DRUG MONITORING: A SYSTEMATIC REVIEW AND META-ANALYSIS
Bibliographic record
Abstract
PV255 / #550 Poster Topic: AS24 - SLE-Treatment Background/Purpose Tacrolimus is a pregnancy-compatible immunosuppressive increasingly used in systemic lupus erythematosus (SLE) pregnancies. Physiological changes throughout pregnancy impact tacrolimus pharmacokinetics, altering the drug’s whole blood concentrations during gestation. However, data is very limited to guide clinicians caring for pregnant women receiving tacrolimus in interpreting tacrolimus trough levels and adjusting the dosage. We completed a systematic review focusing on the variations of maternal tacrolimus trough levels and dosage during SLE and non-SLE pregnancies. Methods Using a combination of relevant search terms and keywords, we systematically searched Embase, Ovid, PubMed, Web of Science and Cochrane Library up to January 2024. All observational studies which measured whole blood tacrolimus trough levels during pregnancy were included without language or date restriction. Studies which were reviews, case reports, abstracts only, non-human, and had no tacrolimus levels during pregnancy were excluded from the review. We then used random-effects models to estimate standardized mean differences (SMD) or mean differences (MD), with 95% confidence intervals (CI) of tacrolimus trough levels and doses before and during pregnancy and in the postpartum. Results: Of 404 publications identified, 124 duplicates were excluded and 282 were screened based on title and abstract, of which 53 full-text articles were assessed for eligibility. Eighteen articles were included in the systematic review and 13 in the meta-analysis. Only 2 studies assessed tacrolimus levels in SLE pregnancies, while the remainder were in pregnant organ transplant recipients (Figure 1). Tacrolimus levels significantly decreased during pregnancy compared to prepregnancy (SMD -1.05; 95% CI -1.72, -0.37), and significantly increased in the postpartum compared to levels during gestation (SMD 0.87; 95% CI 0.37, 1.37) (Figure 2A,B). Mean differences in tacrolimus trough levels were -1.56 ng/ml (95% CI -2.82, -0.31) between first trimester and before pregnancy, -0.49 ng/ml (95% CI -1.04, -0.07) between second and first trimesters, 0.63 ng/ml (95% CI 0.30, 0.96) between third and second trimesters, and 1.28 ng/ml (95% CI 0.60, 1.96) between the postpartum and third trimester. The variation in tacrolimus levels during pregnancy was usually addressed by increasing the dose during pregnancy vs prepregnancy (MD 1.35 mg/day, 95% CI 0.23, 2.48) and decreasing the dose in the postpartum vs pregnancy (MD -0.92 mg/day; 95% CI -1.8, -0.01) (Figure 2C,D). Figure 1. Flow-chart of study selection. Figure 2. (A) Forest plot of the standardized mean difference between tacrolimus whole blood concentrations during pregnancy (second or third trimester) and before pregnancy. (B) Forest plot of the standardized mean difference between tacrolimus whole blood concentrations in the post-partum and during pregnancy (second or third trimester). (C) Forest plot of the mean difference in mg/day between tacrolimus doses during pregnancy (second or third trimester) and before pregnancy. (D) Forest plot of the mean difference in mg/day between tacrolimus doses in the post-partum and during pregnancy (third trimester). Conclusions Tacrolimus whole-blood levels decrease in the first and second trimesters, then increase back to prepregnancy levels in the postpartum. Tacrolimus dosage in pregnancy is typically increased to maintain tacrolimus trough levels within usual therapeutic ranges. Increasing drug dosage could elevate the bio-effective fraction of tacrolimus (not measured by trough levels), raising concerns for safety and efficacy of dose augmentation during pregnancy. Further research is needed to guide clinicians in adjusting tacrolimus in SLE and non-SLE pregnancies to optimize therapeutic drug monitoring in high-risk populations.
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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 | 0.016 | 0.045 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.045 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".