High Risk Multiple Myeloma Cases Are Identified In An MMRC Led Study By The SKY92 Gene Signature (MMprofiler)
Notice bibliographique
Résumé
Abstract Introduction Multiple Myeloma is not a single disease. There is increasing support for risk classification in combination with treatment decision making because of its impact on clinical outcomes. Here we demonstrate additional evidence of the prognostic value of SKY92, an established genetic marker of high risk Multiple Myeloma in a multicenter collection of samples with undisclosed treatments. Materials Methods A public GEP dataset (MMRC, MMGI portal) contained 114 cases of untreated Multiple Myeloma and was used for SKY92 high risk OS prediction (Kuiper et al. Leukemia 2012). In collaboration with MMRC, OS (with a minimum of at least 2 year follow-up) was collected for 91 of 114 cases for the purpose of this analysis. Briefly, CD138-positive plasma cells had been purified prior to total RNA extraction and subsequent gene expression profiling on Affymetrix U133Plus2.0 GeneChips. The 91 cases represented 9 different clinical sites and their CEL files were normalized as a single batch against a reference cohort of 329 cases after which the SKY92 risk scores were determined as either standard risk or high risk. Results SKY92 resulted in 19 high risk (20.9%) versus 72 standard risk (79.1%) cases in the unselected 91 case-cohort. Comparisons with other high risk GEP signatures will be performed. The OS analysis (Figure 1) shows that the HR cases have significantly shorter survival (Hazard Ratio 11, p = 7 x 10-5). Table 1 shows that high risk patients had more elevated B2M (26.3% vs 13.9%), more low albumin (26.3% vs 16.7%) and more high creatinine (26.3% vs 11.0%). There was no difference between high and standard groups in diagnosis dates (not shown). Cause of the 16 (84.2%) deaths among the high risk cases, and 21 (29.1%) deaths among the standard risk cases indicates that high risk contains less disease progression deaths (57.1% vs 31.3%), and more unknown deaths (56.3% vs 23.8%). Conclusions The SKY92 classifier identified 19 of 91 cases (21%) as high risk, recapitulating the percentage of high risk in previously studied cohorts (Kuiper et al. 2012). Moreover the hazard ratio of 11 when events up to 24 months or 8.18 when all events are considered, emphasizes the unmet medical need of high risk cases identified with SKY92 as 69% of all deaths within 2 years (9/13 death events) were in this category. Acknowledgments This research was performed within the framework of CTMM, the Center for Translational Molecular Medicine, project BioCHIP grant 03O-102. Rafael Fonseca is a Clinical Investigator of the Damon Runyon Cancer Research Fund. This work is supported by grants R01 CA83724, ECOG CA 21115T, Predolin Foundation, Mayo Clinic Cancer Center and the Mayo Foundation. Disclosures: van Beers: Skyline Diagnostics: Employment. Van Vliet:Skyline Diagnostics: Employment. Anderson:celgene: Consultancy; onyx: Consultancy; gilead: Consultancy; sanofi aventis: Consultancy; oncopep: Equity Ownership; acetylon: Equity Ownership. Jagannath:Celgene: Honoraria; Millennium: Honoraria. Jakubowiak:BMS: Consultancy, Membership on an entity’s Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau; Millennium: Consultancy, Membership on an entity’s Board of Directors or advisory committees; Onyx: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau. Kumar:Celgene: Clinical Trial Support Other, Membership on an entity’s Board of Directors or advisory committees; Cephalon: Clinical Trial Support, Clinical Trial Support Other; Millennium: Clinical Trial Support, Clinical Trial Support Other, Membership on an entity’s Board of Directors or advisory committees; Novartis: Clinical Trial Support, Clinical Trial Support Other; Onyx: Clinical Trial Support Other, Membership on an entity’s Board of Directors or advisory committees. Lebovic:Celgene: Speakers Bureau; Onyx: Speakers Bureau. Lonial:Millennium: Consultancy; Celgene: Consultancy; Novartis: Consultancy; BMS: Consultancy; Sanofi: Consultancy; Onyx: Consultancy. Reece:Onyx: Honoraria; Novartis: Honoraria; Millennium: Research Funding; Merck: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; BMS: Research Funding. Siegel:Celgene: Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau; Millennium: Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau; Onyx: Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau. Vij:Celgene: Honoraria, Research Funding, Speakers Bureau; Millennium: Honoraria, Speakers Bureau; Onyx: Honoraria, Research Funding, Speakers Bureau. Zimmerman:Celgene: Honoraria; Millennium: Honoraria; Onyx: Honoraria. Fonseca:Medtronic: Consultancy; Otsuka: Consultancy; Celgene: Consultancy; Genzyme: Consultancy; BMS: Consultancy; Lilly: Consultancy; Onyx: Consultancy, Research Funding; Binding Site: Consultancy; Millennium: Consultancy; AMGEN: Consultancy; Cylene: Research Funding; Prognostication of MM based on genetic categorization of the disease: Prognostication of MM based on genetic categorization of the disease, Prognostication of MM based on genetic categorization of the disease Patents & Royalties.
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 | 0,001 |
| 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 | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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.
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 ».