Incidence and Risk Factors for Nontuberculous Mycobacteria Infection after Allogeneic Hematopoietic Cell Transplantation
Notice bibliographique
Résumé
Abstract Introduction: Nontuberculous mycobacteria (NTM) are ubiquitous environmental organisms that are increasingly recognized as clinically significant pathogens in the allogenic hematopoietic cell transplanted (alloHCT) population. The incidence of NTM infection post alloHCT has increased from 0.49-1.0% in early studies to 2.8-8.7% in more recent investigations, possibly due to improvements in NTM detection, varying pre-transplant conditioning regimens and regional epidemiology of different NTM species. We investigated incidence and risk factors of NTM infection after alloHCT. Methods & Patients: Medical records for 1097 consecutive patients who underwent alloHCT at Princess Margaret Cancer Centre from 2000 to 2013 were reviewed to determine the frequency, risk factors and outcomes associated with NTM infections. Clinically significant NTM infection was differentiated from colonization according to the American Thoracic Society guidelines, and was classified as pulmonary, non-pulmonary, or disseminated. Acute and chronic graft versus host disease (aGVHD and cGVHD) were diagnosed and graded using established and NIH consensus criteria respectively. The cumulative incidence of NTM was calculated considering competing risks of death. Multivariate analysis comprised Cox proportional hazards regression, modeling NTM risk. Statistical analyses were performed using EZR software (Saitama, Japan). Results: Of 1097 patients, NTM were isolated in 45 (4.1%) and judged clinically significant in 30 (2.7%). The incidence of NTM infection by competing risk analysis was 2.8% at 5 years (95% CI, 1.9-4.0%). The median (range) time to diagnosis was 343 (19-1967) days, and in 83% of patients, was diagnosed within 2 years of alloHCT. Of the 30 clinically significant NTM infections, 28 (93.3%) were pulmonary and 2 (6.7%) were disseminated. With respect to the latter group, one patient had NTM isolated from blood, while the second case was presumed disseminated based on characteristic skin findings, but with no confirmed microbiologic diagnosis. The most common species/groups isolated were Mycobacterium avium complex (n=11, 36.7%), M. xenopi (n=5, 16.7%), and M. fortuitum (n=5, 16.7%). 22/30 patients (73.3%) were on systemic immunosuppression at the time of diagnosis, and 95.7% had concurrent infections (30.4% pulmonary, 17.3% extra-pulmonary, and 47.8% both), with fungal infections occurring most frequently (53.3%). Significant risk factors (HR 95% CI) for NTM included aGVHD grades 2-4 (3.25 [1.33-7.96] p=0.036), cGVHD (3.20 [1.06-9.68] p=0.010), age (1.05 [1.02-1.07], p <0.001), and CMV viremia (4.64 [1.90-11.37] p=0.001). 76.7% of patients with clinically significant NTM had a diagnosis of cGVHD (23/30), in comparison to 47.4% (520/1097) of patients without a diagnosis of NTM infection (p=0.003), and cGVHD severity by NIH global score correlated with NTM risk. Among all patients with cGVHD, severe cGVHD was present in 39% (9/23) of NTM patients, versus 17% (89/520) of non-NTM patients (p=0.012). Pre-alloHCT diagnosis (p=0.34), conditioning regimen (p=0.81), T-cell depletion (p=0.66), HLA matching (p=0.62), or donor type (p=0.63), did not reach statistical significance. Median survival duration after a diagnosis of clinically significant NTM was 398 (range, 20-764) days, with a survival rate of 40.8±10.8% at 2 years. Conclusion: Clinically significant NTM infection after alloHCT was relatively common in our study population. GVHD (acute and chronic), age, and CMV bacteremia were significant risk factors. Given a median survival of approximately 1 year following diagnosis, NTM infection may be of greater clinical significance than previously thought. A high index of suspicion for NTM infection in patients with pulmonary symptoms, particularly within 2 years after HCT and in the presence of cGVHD, may lead to prompt diagnosis and treatment, and potentially better outcomes. Disclosures Lipton: Pfizer: Consultancy, Research Funding; Ariad: Consultancy, Research Funding; Teva: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Novartis Pharmaceuticals: Consultancy, Research Funding. Kim:Novartis Pharmaceuticals: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding.
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 | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 ».