Transplantation-Specific Cytogenetics Grouping Scheme for Patients with Myelodysplastic Syndromes: A Multicenter Validation Study
Notice bibliographique
Résumé
Abstract Cytogenetics are an important prognostic factor for patients with myelodysplastic syndromes (MDS). However, the most commonly employed cytogenetics grouping scheme, as used in the IPSS, was derived from a cohort of patients who primarily received supportive care. This scheme may therefore not be optimal for stratifying patients undergoing aggressive therapy such as allogeneic stem cell transplantation (SCT). We previously proposed an SCT-specific cytogenetics grouping scheme for patients with MDS and AML arising from MDS (mAML), based on single-institution data. That scheme allowed for better prognostic stratification than the IPSS scheme. We undertook the present retrospective multicenter study to validate those results. Included were 546 patients with MDS or mAML from the Fred Hutchinson Cancer Center, the M.D. Anderson Cancer Center, and Princess Margaret Hospital. The median age was 53 years (range 18–74). 27% of patients had high-risk MDS (RAEB 1 or 2), and 43% had mAML; 17% had therapy-related disease. Overall 61% of patients were untreated at the time of SCT, while 12% were in CR following treatment. 68% received a conventional intensity conditioning regimen, and 65% were transplanted with peripheral blood stem cells. Donors were matched related (46%), matched unrelated (36%), or mismatched (18%). Cytogenetics were available for 86% of patients. Of those, 47% had favorable, 25% intermediate, and 28% adverse cytogenetics, when grouped by IPSS category. With a median follow-up of 48 months, 4-year relapse-free and overall survivals were 36% and 40%, respectively. In multivariate analyses, variables significantly associated with overall survival were cytogenetics, disease type and stage, patient age, donor match, and year of transplantation. Notably, therapy-related disease was not associated with increased mortality in this model. The optimal cytogenetics grouping scheme comprised two groups, with abnormalities of chromosome 7 and complex karyotype being adverse, and all other abnormalities (including normal karyotype, del(5q), and del(20q)) being standard risk. Adverse cytogenetics was the strongest prognostic factor for SCT outcome in this cohort, with a hazard ratio for mortality of 2.1 (p<0.0001). Four-year relapse-free and overall survivals were 42% and 46%, respectively, in the standard risk group, versus 21% and 23% in the adverse group (p<0.0001 for both comparisons). These differences were solely due to an increased risk of relapse in the adverse group (with a 4-year cumulative relapse incidence of 41%, versus 24% in the standard risk group (p<0.0001)), while non-relapse mortality was the same for both groups (38% and 38%, p=0.6). This grouping scheme retained its prognostic significance irrespective of patient age, disease type (low-risk versus high-risk MDS versus mAML), therapy-related or de novo disease, and conditioning intensity. Based on this multicenter validation, we propose that this SCT-specific cytogenetics grouping scheme be used for patients with MDS or mAML who are considering or undergoing SCT, for prognostication, patient selection, outcome reporting, or clinical trial stratification purposes.
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 | 0,008 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 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 ».