Long Term Results of Myeloablative Allogeneic Stem Cell Transplantation Using Related and Unrelated Donors in Patients with Relapsed Composite Low and Intermediate Grade (Including Transformed) Lymphoma.
Notice bibliographique
Résumé
Abstract Patients (pts) with relapsed (REL) transformed non-Hodgkin lymphoma (NHL) have poor outcome with conventional therapies. Although the role of autologous (auto) stem cell transplantation (SCT) has been previously described, there is scarce literature about allogeneic (allo) SCT in this setting. Forty pts with REL composite low/intermediate (L/I) NHL (25 transformed, 8 composite (same site) and 7 discordant (different sites)) underwent allo-SCT Jan ’89 to June ’05. Fifteen pts (38%) received stem cells from unrelated donors (UD) (12 matched and 3 with one antigen mis-match [1AgMM]). Six of 15 pts (40%) in the UD group are alive including one pt post 1AgMM SCT. 25 pts (62%) had matched sibling allo-SCT and 5 (20%) pts are still alive. Twenty-nine of 40 pts (73%) died, with REL NHL (n=15, 38%) or treatment related mortality (TRM) (n=14, 35%). The 2 and 5-year probability of OS were 39% [95% CI: 26–58%] and 23% [10–49%] respectively; of EFS 36% [24–55%] and 23% [11–46%]. Univariate analysis (UVA) showed presence of residual (res) NHL prior to allo-SCT as a poor prognostic factor for OS and EFS with p value of 0.029 (HR=2.2) and 0.011 (HR=2.5) respectively. No survival difference was seen between patients treated with related or UD stem cells. On multivariate analysis (MVA), development of aGVHD grades 2–4 had a significantly negative impact on both OS and EFS (for OS: p=0.006, HR=1.46, for EFS: p=0.01, HR=1.37) as did res disease prior to SCT (for OS: p=0.04, HR=2.2, for EFS: p=0.02, HR=2.4). Age >46 years was a significant risk factor for TRM on UVA (p=0.02, HR=3.3) and MVA (p=0.07, HR=2.9). MVA also showed development of cGVHD as a significant risk factor for TRM (p=0.001, HR=1.8). No difference in TRM was seen between related and UD SCT. Pts with res NHL at SCT had a higher risk of REL NHL (p=0.008, HR=5), as did pts who were chemotherapy resistant (no change in the tumor mass) pre-SCT (p=0.002, HR=3.9). Inclusion of TBI in the conditioning regimen significantly reduced the risk of REL NHL (p=0.01, RR=0.22). Prior rituximab therapy was associated with reduced REL risk, although this was not statistically significant (p=0.06, HR=0.82). CGVHD was significantly protective against REL in MVA (p=0.03, HR= 0.8), and res NHL at SCT was associated with increased REL (p=0.003, HR= 7). Stem cell dose (mononuclear cells) >3X108/kg was the only significant risk factor for development of cGVHD in UVA (p=0.04, HR=0.4) and MVA (p=0.05, HR=0.4). In conclusion, this is the largest report on the utility of allo-SCT (inculding UD-SCT) in patients with REL composite L/I-NHL. Survival was similar in pts receiving stem cells from related and unrelated donors. UVA and MVA analysis revealed multiple significant risk factors for survival, TRM, development of cGVHD and relapse which should be taken into consideration for future allo SCT pts. Development of chronic, but not acute GVHD was protective for NHL relapse, supporting the action of a graft vs lymphoma effect in this population.
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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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| 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) | 0,001 | 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 ».