Risk Factor Analysis for the Development of Large Granular Lymphocytosis after Allogeneic Hematopoietic Cell Transplantation: Randomized Stratification and Propensity Score Analysis
Notice bibliographique
Résumé
Abstract Introduction Large granular lymphocytes (LGL) are a morphologically recognizable subpopulation of lymphocytes comprising an immunophenotypically heterogeneous population of activated CD3+ T cells and CD3- natural killer (NK) cells that mediate non-MHC-restricted cytotoxicity. Increased number of circulating LGL can be found as a response to viral infections, autoimmune disease or malignant neoplasms, as a result of chronic antigenic stimulation. Of interest, LGL lymphocytosis has been reported to occur following hematopoietic cell transplantation (HCT), with a variable incidence of up to 20%. This population display improved transplant outcomes with a lower incidence of non-relapse mortality and relapse (Kim, BMT, 2013; Nann-Rütti, BBMT, 2012). The aim of the present study is to determine the risk factors associated with the development of LGL lymphocytosis after allogeneic HCT. Methods A total of 826 patients who underwent an allogeneic HCT at Princess Margaret Cancer Centre, Toronto, Canada from 2000 to 2012 were retrospectively analyzed. LGL lymphocytosis was defined as the presence of at least two of the followings: 1) Sustained peripheral blood lymphocyte count ≥3.0 x 109/L observed in at least three consecutive determinations over a period of 2-3 months; 2) Predominance (≥30%) of LGL lymphocytes in the peripheral blood, as assessed by morphologic or immunophenotypic criteria; 3) T-cell receptor monoclonality assessed by PCR. The patient population was divided into discovery and replication sets using 2 different methods: stratified randomization and propensity score matching, using relevant baseline variables such as donor type, CMV serostatus, conditioning, T-cell depletion. Results No significant imbalances were found between the discovery and replication sets in terms of relevant baseline characteristics and clinical outcomes, for both the randomly divided patients and the propensity score matched groups. The overall incidence of LGL lymphocytosis was 14.5% at 3 years. The incidence of LGL lymphocytosis was similar across all subgroups of patients, both for the randomly divided groups and the propensity score matching (P-value not significant). A multivariable analysis of the risk factors for the development of LGL lymphocytosis was performed, including the following variables: grades 3-4 acute graft-versus-host-disease (GVHD), chronic GVHD, CMV viremia, CMV serostatus of the recipient, donor type, transplant year and T-cell depletion (TCD) for GVHD prophylaxis. In the stratified randomization analysis, the following risk factors were identified: 1) Discovery set: chronic GVHD (Hazard Ratio: 8.3, 95% CI: 3.1-22.6, P<0.001), CMV viremia (HR: 2.7, 95% CI: 1.5-4.7, P<0.001) and use of an unrelated donor (HR: 2.1, 95% CI: 1.2-3.7, P=0.01). 2) Replication set: chronic GVHD (HR: 38.9, 95% CI: 5.3-284.9, P<0.001) and CMV viremia (HR 3.8, 95% CI: 2.2-6.6, P<0.001). For the propensity score matching analysis the risk factors for the development of LGL lymphocytosis were the following: 1) Discovery set: chronic GVHD (HR: 22.9, 95% CI: 3.2-169.3, P=0.002) and CMV viremia (HR: 2.2, 95% CI: 1.1-4.2, P=0.02). 2) Replication set: chronic GVHD (HR: 28.9, 95% CI: 3.9-212.5, P<0.001), CMV viremia (HR: 3.6, 95% CI: 1.9-6.7, P<0.001). Conclusions Chronic GVHD and CMV viremia are strongly associated with the development of LGL lymphocytosis following allogeneic HCT. This may reflect a chronic antigenic stimulation in the setting of GVHD and CMV infection, leading to the expansion of LGL. However, the underlying mechanisms of LGL activation and expansion in the allogeneic HCT setting still remain unclear. Thus, further investigations are needed to elucidate these mechanisms in particular in the setting of GVHD. 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:Bristol-Myers Squibb: Consultancy, Research Funding; Novartis Pharmaceuticals: Consultancy, Research Funding.
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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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| 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 | 0,001 |
| 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 ».