Paraffin-Based 6-Gene Model Predicts Outcome of Diffuse Large B-Cell Lymphoma Patients Treated with R-CHOP.
Notice bibliographique
Résumé
Abstract Background: Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease characterized by highly variable clinical outcomes. It is therefore of paramount importance to be able to predict the outcome of patients at the time of diagnosis. Previously, we constructed a 6 gene model for outcome prediction of DLBCL patients treated with anthracycline-based chemotherapies (Lossos et al NEJM 2004, 350:1829). However, the standard therapy has evolved to rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone (R-CHOP). Subset analyses of clinical trials have suggested that some of the prognostic factors lose their predictive power in R-CHOP treated patients. Consequently, the molecular gold standard for survival prediction in R-CHOP treated patients has not been established. Herein, we evaluated the predictive power of the 6-gene model in R-CHOP treated DLBCL patients. We have employed new methodology that allows quantitation of gene expression from paraffin embedded, fixed tissues. Methods: RNA was extracted from 100 paraffin-embedded specimens (Chen et al Diagn Mol Pathol 2007, 16:61), from patients with DLBCL treated with R-CHOP in British Columbia (73) and at the University of Miami (27). Expression of the 6 genes comprising the model was measured in these samples and the mortality-prediction score was calculated for each patient, as reported previously. Results: The study group consisted of 100 patients with a median age of 58 y (range, 16–92y) that were followed for a median of 2.1 years (range, 0.1–5.6). Distribution according to IPI: 0–1 factor, 42; 2 factors, 24; 3 factors, 19; and ≥4 factors, 14. RNA of sufficient quality and quantity was successfully extracted from all the 100 paraffin embedded specimens tested, some of which had been stored for up to 6 years. The mortality-prediction score derived from the model divided patients into low-risk (50%) and high-risk (50%) subgroups with significantly different overall survival (OS) (p=0.02) and progression free survival (PFS) (p=0.02). Notably the OS was similar between the groups during the 1st year, due to the inclusion of patients with advanced age and poor performance status, but it was markedly different beyond the first 2 years, with the 3 year OS of 80% and 50% in the low risk and high risk groups, respectively. The predictive power of the 6-gene model was independent of the IPI prognostic factors for prediction of OS (P=0.06) and PFS (p=0.01) in these patients. Conclusions: The prognostic value of the 6-gene model remains significant in the era of R-CHOP treatment. Further, using the new RNA extraction methodology, we demonstrate that the model can be applied to routinely available formalin-fixed paraffin blocks from initial diagnostic biopsies, even after long term storage. Following validation in an independent cohort of patients, the six gene model may be practically applied in routine clinical practice.
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 | 0,000 | 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 | 0,000 |
| 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 ».