Determining the Optimal Use of Antibiotics in Hematopoietic Stem Cell Transplant Recipients
Notice bibliographique
Résumé
This study by Rashidi and colleagues 1 sought to characterize the association of antibiotic exposure and timing of the exposure relative to allogeneic hematopoietic stem cell transplantation (allo-HCT) with the hazard of developing acute graft-vs-host disease (aGVHD), which is one of the most common complications of allo-HCT.Rashidi et al 1 applied 3 orthogonal methods (conventional Cox proportional-hazards regression, marginal structural models, and machine learning) to analyze data collected from 2023 patients who underwent their first T-replete allo-HCT at a single center between 2010 and 2021.Each of the included analytical methods has its own strengths and weaknesses, but together they provided a comprehensive perspective.Rashidi et al 1 reported that weeks 1 and 2 after allo-HCT were the highest-risk intervals, with several antibiotic exposures associated with higher risk of subsequent aGVHD.Of note, carbapenems exposure weeks 1 and 2 after allo-HCT was associated with a minimum hazard ratio (HR) of 2.75 (95% CI, 1.77-4.28),whereas week 1 after allo-HCT exposure to penicillins with β-lactamase inhibitors was associated with a minimum HR of 6.55 (95% CI, 2.35-18.20).Across all 3 methods, the data from the study by Rashidi et al 1 also suggest that pre-allo-HCT exposure to penicillins with β-lactamase inhibitors was associated with a lower risk of aGVHD.These findings have implications on patient care, as penicillins with β-lactamase inhibitor (eg, piperacillin-tazobactam) and carbapenems (eg, meropenem) are broad-spectrum antibiotics with antipseudomonal activity commonly administered during pre-engraftment, when the patient is most at risk of infections due to profound and prolonged neutropenia.Although there was some variability in the results among the 3 analytical methods, taken together, they suggest that a thoughtful and judicious approach to antibiotic prescribing during the critical periods during and immediately after allo-HCT is warranted to mitigate against aGVHD.In addition to the significant morbidity affecting the skin, gastrointestinal tract, and liver, treatment for aGVHD commonly involves escalating the dose of immunosuppression plus systemic corticosteroids.In turn, these interventions create additional risks for infections and perpetuate the cycle for more antimicrobials.Determining the optimal use of antibiotics is a topic of interest to both allo-HCT clinicians and the antimicrobial stewardship team.In the past decade, cancer therapy underwent dramatic advances through the discovery of targeted small-molecule therapies, novel application of stem cell transplant techniques, and the emerging use of cellular therapy, such as chimeric antigen receptor T-cell therapy.However, infectious complications and antimicrobial resistance continue to pose significant threats to clinical success. 2 Compared with cancer treatment, the antimicrobial pipeline has made modest progress in the availability of new classes of antibiotics, although not nearly as prolific.Thus, preserving the effectiveness of antibiotics and mitigating against antibiotic resistance remain integral to supporting patients throughout their cancer treatment.Antimicrobial stewardship interventions for the prevention and management of neutropenic fever in patients receiving treatment for hematological malignant neoplasms is gaining momentum.3 For patients undergoing allo-HCT, the role of antibiotics, regimen selection, and timing of antibiotic administration during the peritransplant periods (ie, pretransplant conditioning regimen and pre-engraftment after HCT) is less well understood.Furthermore, there is a lack of consensus framework to assess the likelihood of benefit vs the potential harms from antibiotic exposure in the immediate, medium, and long term after allo-HCT, making implementation of antimicrobial stewardship more challenging.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,005 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».