Identification of Prognostic Immunophenotypes at First Diagnosis in Patients with Acute Myeloid Leukemia (AML) By a Standardized Multicolor Flow Cytometry (MFC) Panel Originally Designed to Detect Measurable Residual Disease (MRD) at Follow-up
Notice bibliographique
Résumé
Aims In AML, several risk factors obtained at first diagnosis (FD) have been reported to be associated with shorter RFS and OS. The primary prognostic relevance of multicolour flow cytometry (MFC) has been a matter of debate for years. During follow-up (FU), the prognostic relevance of MRD as detected by MFC is less controversial and MFC is recommended in particular (but not exclusive) for those patients (pts) with no reliable genetic marker. We thought to evaluate the prognostic value at FD of a recently established antigen panel and a corresponding analysis strategy, which had been originally developed for MRD-detection. Methods Based on an 8-colour antibody panel (CD45, CD34, CD117, HLA-DR, CD13, CD33, CD7, CD56), we have developed a hierarchical gating strategy with mainly fixed gates. That allows to detect MRD with a high level of standardization and inter-observer reliability (Röhnert M., et al. 25th EHA 2020). Four distinct categories of aberrations (deficiency of CD13 or CD33, cross-lineage expression of CD7 or CD56) detectable on at least 10% of the myeloid blast population were used to define aberrant phenotypes termed leukemia associated immunophenotypes (LAIP) at FD. These categories were also chosen to define MRD during FU. MRDpos by LAIP was defined as the (re-)occurrence of an aberrant category already detectable at FD, while MRDpos by DfN (different from normal) was defined by the de-novo detection of an aberrant category at FU. The prognostic value of the aberrant phenotypes at FD was examined in a cohort of 528 pts. In 122 pts, we further analysed MRD (LAIP/DfN) after completion of intensive induction chemotherapy (IT). Consolidation therapy consisted of allogeneic hematopoietic stem cell transplantation (n=77) or chemotherapy (n=45). The bone marrow samples were measured centrally and analysed independently by three different investigators. Results The probability to achieve a complete remission (CR) varied between the different aberrant phenotypes (LAIP) at FD. Compared to pts without aberrant phenotype (CR rate=68%, n/N=100/148), pts with CD56only (the sole aberrant category was a cross-lineage expression of CD56=only) had a significantly lower CR rate (46%, n/N=15/33, p=0.019). The other exclusive aberrant categories did not significantly influence CR rates compared to pts without LAIP: CD13only (75%, n/N=53/71, p=0.286), CD33only (64%, n/N=59/97, p=0.28) and CD7only (62%, n/N=31/50, p=0.472). In pts with possibly co-occurring aberrant categories (compound aberrant phenotype=comp), the CR rate was significantly higher in CD13comp compared to all other patients (75% vs. 64%, 107/143 vs. 246/385, p=0.018). The other compound aberrancies did not significantly influence CR rates: CD33comp (63% vs. 68%, 90/143 vs. 263/385, p=0.244), CD7comp (66% vs. 67%, 72/109 vs. 281/419, p=0.842) and CD56comp (68% vs. 66%, 84/123 vs. 269/405, p=0.699). Regarding overall survival (OS), just CD56only retained its statistical significance (HR 2.5, CI 1.4-4.7, p=0.004). CD13comp was associated with favourable outcome but without reaching statistical significance (HR 0.7, CI 0.4-1.0, p=0.059). In the cohort of pts with MRD assessment at the end of IT, 67% were classified as responders (CR n=62, CRi n=19) and 33% as non-responders (PR n=14, refractory n=26) by cytomorphology. By MFC, 71% of these pts were classified as MRDpos (n=51/36 responders/non-responders) and 29% as MRDneg (n=30/4). MRDpos was defined by LAIP only (23%), DfN only (44%) or concordantly by LAIP+DfN (33%). OS of MRDneg pts was significantly longer compared to MRDpos patients (HR 4.3, CI 1.0-18.1, p=0.033). Conclusions Using our analysis approach originally developed for MRD monitoring, MFC could provide additional information for initial risk stratification. The presence of an isolated cross-lineage expression of CD56 (CD56only) was associated with a lower CR rate and significant shorter OS. In contrast, CD13comp (CD13 deficiency ± other aberrant categories) was associated with a higher CR rate and prolonged OS. Furthermore, MRDpos as defined by the combined LAIP/DfN strategy provided significant prognostic information. The presented results are currently refined and validated using genetically defined subcategories. The approach has to be confirmed in an independent cohort of pts. Disclosures Rollig: Amgen, Astellas, BMS, Daiichi Sankyo, Janssen, Roche: Consultancy; Abbvie, Novartis, Pfizer: Consultancy, Research Funding. Buecklein:Pfizer: Consultancy; Novartis: Research Funding; Celgene: Research Funding; Amgen: Consultancy; Gilead: Consultancy, Research Funding. Subklewe:Novartis: Consultancy, Research Funding; Janssen: Consultancy; Roche AG: Consultancy, Research Funding; AMGEN: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria; Morphosys: Research Funding; Seattle Genetics: Research Funding; Pfizer: Consultancy, Honoraria; Gilead Sciences: Consultancy, Honoraria, Research Funding. Krause:Pfizer: Honoraria; MSD: Honoraria; Takeda: Honoraria; Gilead: Other: Travel Support; Celgene: Other: Travel Support; Siemens: Research Funding. Schlenk:Roche: Research Funding; AstraZeneca: Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; PharmaMar: Research Funding; Daiichi Sankyo: Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accomodations, Expenses, Research Funding, Speakers Bureau; Novartis: Speakers Bureau.
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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 | 0,000 |
| Bibliométrie | 0,001 | 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) | 0,000 | 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 ».