225.5: Quantiferon®-monitor as a biomarker of immunosuppression and predictor of infection: A scoping review.
Bibliographic record
Abstract
Introduction: Quantiferon®-Monitor (QFM) is a novel immune function assay that measures plasma interferon- γ levels after stimulation with innate and adaptive immune antigens. Clinical studies of this promising biomarker are emerging, exploring its role as a measure of the net state of immunosuppression and predictor of infections. The aim of this study is to synthesize the currently available published evidence regarding the use of QFM in transplant recipients, inform the feasibility of a systematic review, and identify knowledge gaps for future studies. Methods: We performed a systematic literature search that considered all primary study types. Studies had to involve human participants aged ≥18 years who received a solid organ or bone marrow transplant, with QFM testing performed at least once before/after transplant. Data were collected regarding study type, patient population, QFM testing and results, outcomes assessed, and other key findings. Results: Our search identified 13 published studies, of which 4 were available as conference abstracts only. The 9 manuscripts published from 2014-2023 all describe observational studies, including 7 prospective cohorts and 2 cross-sectional studies. Five studies were performed in Australia, 2 in Europe, 1 in Canada and 1 in Jordan. In total, QFM was assessed in 580 transplant recipients, 505 solid organ (223 liver, 151 kidney, 130 lung and 1 small bowel) and 75 allogeneic bone marrow transplant recipients. Most studies measured QFM longitudinally with multiple measurements over the first 6-12 months post-transplant. There was significant heterogeneity amongst values obtained and analyses performed. The main outcomes assessed were associations with immunosuppression (n=6), infections (n=8) and rejection (n=3) or graft versus host disease (n=2). Four studies identified relationships between higher immunosuppression doses and lower QFM values, 7 studies described increased risks of infection in patients testing low, and one study identified a link with QFM results and rejection. Conclusion: Global immune assays such as QFM have the potential to provide a measure of the net state of immunosuppression and identify overly immunosuppressed patients at high risk for infections. This could inform personalized interventions such as reductions in immunosuppression, more intensive clinical monitoring, or targeted antimicrobial prophylaxis. The current evidence is limited to observational studies, with significant heterogeneity in methodology that makes direct comparison difficult, rendering a meta-analysis/systematic review challenging. Ultimately, these assays could improve our ability to predict and prevent infections in transplant recipients, reduce hospitalizations, minimize adverse events of immunosuppression, improve quality of life and increase survival. Carefully planned interventional trials are needed to further evaluate these novel biomarkers.
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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 | 0.012 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.026 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".