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Enregistrement W2585970811 · doi:10.1182/blood.v114.22.2772.2772

Cytogenetic Risk Features in MDS-Update and Present State.

2009· article· en· W2585970811 sur OpenAlexaff
Julie Schanz, Heinz Tuechler, Françesc Solé, Mar Mallo, Barbara Hildebrandt, Marilyn L. Slovak, Kazuma Ohyashiki, Christian Steidl, Christa Fonatsch, Michael Pfeilstöecker, Thomas Noesslinger, Peter Valent, Aristoteles Giagounidis, Michael Luebbert, Reinhard Stauder, Otto Krieger, Michelle M. Le Beau, John M. Bennett, Peter L. Greenberg, Ulrich Germing, Detlef Haase

Notice bibliographique

RevueBlood · 2009
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensBC Cancer Agency
Organismes subventionnairesnon disponible
Mots-clésInternational Prognostic Scoring SystemMultivariate analysisUnivariate analysisMyelodysplastic syndromesUnivariateMedicineInternal medicineOncologyBone marrowCytogeneticsMultivariate statisticsComputer scienceBiology

Résumé

récupéré en direct d'OpenAlex

Abstract Abstract 2772 Poster Board II-748 Introduction: The IPSS-Score, published by Greenberg et al. (1997), defines the gold standard in risk stratification of patients with MDS. Since its implementation in 1997 based on 816 patients with primary MDS, the knowledge concerning the prognostic impact of distinct abnormalities increased extensively. The present study proposes a new and comprehensive cytogenetic scoring system based on an international data collection of 3803 patients, originating from the German-Austrian (GA)-, the International Risk analysis workshop (IMRAW)- and the Spanish Cytogenetics working group (GCECGH). Additionally, 53 cases of rare abnormalities were contributed by the International Cytogenetics Working Group of the MDS Foundation (ICWG), resulting in total number of 3856 pts. As compared to our previous reports, the data set was substantially enlarged by adding the GCECGH cases and data quality was improved by updating the clinical and survival data; allowing the analysis of the prognostic impact for isolated abnormalities exclusively to assure a maximum accurateness. Furthermore, multivariate analysis was refined by including peripheral cytopenias. Materials and Methods: Inclusion criteria were defined as follows: Primary MDS, age >=16, and bone marrow blasts <=30%. Regarding therapy, exclusively patients with primary MDS and supportive care, only allowing short courses of oral chemotherapy or hemopoietic growth factors were included. Based on these criteria, 958 pts. were excluded resulting in 2901 pts. available for final analysis. Univariate and multivariate analysis concerning overall survival (OS) and 25% AML-transformation (AML-t) was performed. In multivariate analysis, age, gender, bone marrow blast count and number of peripheral cytopenias were defined as co-variables. OS and AML-t in distinct cytogenetic abnormalities was only calculated when the abnormality occurred as an isolated aberration with a minimal frequency of n=10. Median observation time was 19.0 months. Clinical follow-up was performed until April 2009. Results: In total, 20 cytogenetic subgroups matching the inclusion criteria were detected. Abnormalities were grouped as normal (n=1522, 52.5% of all cases), single (1 abnormality), double (2 abnormalities) or complex (>=3 abnormalities). Single abnormalities found were: del(5q) (176, 6.1%); -7/7q- (59, 2.0%); +8 (130, 4.5%); del(20q) (48, 1.7%), -Y (46, 2.1%); der(1;7)(q10;p10)/t(1;7)(var;var) (10, 0.3%); der(3)(q21)/der(3)(q26) (10, 0.3%); del(11q) (19, 0.7%); del(12p) (17, 0.6%); i(17)(q10) (11, 0.4%); +19 (10, 0.3%), +21 (10, 0.3%) and any other single (150, 5.2%). Double abnormalities were stratified into 3 subgroups: double including del(5q) (45, 1.6%); double including -7/7q- (31; 1.1%) and any other double (98, 3.4%). As reported (Haase et al. Blood 2008), complex karyotypes were sub-divided into 2 groups: Karyotypes with 3 abnormalities (59, 2.0%) vs. >3 abnormalities (188, 6.5%). Finally, 20 pts. (0.7%) displayed cytogenetically unrelated clones. According to OS and AML-t, abnormalities were classified to 4 prognostic subgroups: good (normal, del(5q), double incl. del(5q), der(1;7)(q10;p10)/t(1;7)(var;var), del(11q), del(12p), +19, del(20q), -Y); int-1 (any other double, +8, i(17)(q10), +21, any other single, independent clones); int-2 (double incl. -7/7q-, der(3)(q21)/der(3)(q26), -7/7q-, complex 3 abnormalities) and poor (complex >3 abnormalities). Median survival was 50.6 months for good (n=1936), 25.7 months for int-1 (n=451), 16.0 months for int-2 (n=177) and 5.7 months for poor (n=188) and AML-t was 71.9 months for good (n=1681), 14.7 months for int-1 (n=384), 9.8 months for int-2 (n=148) and 3.4 months for poor (n=159). Differences in OS and AML-t were highly significant (p<0.0001). Multivariate analysis resulted in a Hazard Ratio of 1.0 for good (reference category), 1.8 for int-1, 2.1 for int-2 and 4.8 for poor concerning OS. Regarding AML-t, HR was 1.0 for good, 2.6 for int-1, 3.1 for int-2 and 5.2 for poor (all p <0.0001 for OS and AML-t). Conclusions: In summary, we were able to generate a solid database for a revised cytogenetic scoring system, which can serve as the cytogenetic model for the upcoming revision of the IPSS. Acknowledgments: The authors like to thank the MDS-Foundation for its support. Disclosures: No relevant conflicts of interest to declare.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,009

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,002
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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.

Tête enseignante Opus0,010
Tête enseignante GPT0,279
Écart entre enseignants0,269 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations11
Publié2009
Routes d'admission1
Résumé présentoui

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