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Enregistrement W2558638322 · doi:10.1182/blood.v120.21.1867.1867

Secondary Myelodysplastic Syndrome/Acute Myeloblastic Leukemia During Lenalidomide-Based Regimens in Relapsed and/or Refractory Multiple Myeloma Patients: Single Center Experience

2012· article· en· W2558638322 sur OpenAlexaff
Rouslan Kotchetkov, Esther Masih‐Khan, Chia‐Min Chu, Young Trieu, Saima Dean, Manjula Maganti, Christine I. Chen, Vishal Kukreti, Suzanne Trudel, Donna Reece

Notice bibliographique

RevueBlood · 2012
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensUniversity Health NetworkPrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineLenalidomideMultiple myelomaInternal medicineCyclophosphamideMelphalanPrednisoneSurgeryOncologyGastroenterologyChemotherapy

Résumé

récupéré en direct d'OpenAlex

Abstract Abstract 1867 Secondary myelodysplastic syndrome and acute myelogenous leukemia (2° MDS/AML) are well-known complications that can occur after alkylating agent therapy for multiple myeloma (MM) or other cancers. However, until recently, the survival of MM pts was relatively short, a feature which may have contributed to a relatively low reported incidence of this complication in MM. The introduction of novel agents has improved survival rates of MM pts; lenalidomide (len) + dexamethasone–currently approved for MM after one prior therapy– is one of the main regimens that has contributed to this finding. Since alkylating agents, either given orally or as part of high-dose melphalan + ASCT, still remain an important component of MM therapy, more pts may survive to be at risk for 2° MDS/AML. Using the MM database at PMH, we retrospectively reviewed the charts of patients with relapsed/refractory (rel/ref) MM treated with len-based regimens (>1 cycle) to determine the incidence and characteristics of 2° MDS/AML that developed during this therapy. Between 06/2006 and 08/2012 we identified 230 patients having received len-based therapy: len + corticosteroids 222 patients, len alone 8 patients, cyclophosphamide + len + prednisone (CPR) 32 patients. 2° MDS/AML developed in 9 patients (3.9%) at a median of 89.6 months (range 30–188) from the time of diagnosis of MM and 22.4 (2–56.6) months from the time of initiation of len regimens. The median follow-up from start of len was 1.6 years, and from the start of diagnosis 7.5 years. The median duration of len treatment was 9.4 months. The MDS/AML cytogenetic changes were variable, but four patients had deletions of all or part of chromosome 5. None of the 2° MDS/AML had translocation t(4;14), as compared to 5.9% in (−) MDS/AML subgroup. The characteristics of patients at the time of starting len, in those who later developed (+) or did not develop (−) 2° MDS/AML during therapy, are shown in Table 1. Cumulative incidence of 2° AML/MDS from time of diagnosis to time of 2° AML/MDS is 4.5% [95% CI 2.2–9.2%] at 15 years. Cumulative incidence of 2° AML/MDS from starting time of len to time of AML/MDS is 5% [95% CI 2.4–10.4%] at 5 years. The incidence of 2° MDS/AML among those who had prior oral alkylators (OA) and/or concomitant OA was 10.5% (2/19 patients), concomitant cyclophosphamide only 7.6% (1/13), prior OA only 1.9% (3/152), and 6.5% for those who did not receive prior/concomitant OA (3/46). Grade 3–4 neutropenia occurred during len in 44% versus 58% in those with and without 2° MDS/AML, respectively. G-CSF was used in 56% of pts who developed MDS compared with 53% who did not. We conclude: 1) The cumulative incidence of MDS/AML from starting len to time of 2° AML/MDS was 5% at 5 years; 2) patients who developed 2° MDS/AML while on len regimens were slightly older, had slight male predominance, higher beta-2-microglobulin, creatinine and platelet count, less often received prior ASCT, thalidomide, and bortezomib, but had longer exposure to len; 3) the relationship with OA is not entirely certain, but it appears that those with prior and concomitant exposure to OA have the highest incidence of this complication, which is most often seen in prolonged len treatment. Table 1. Patient characteristics (n=230) Feature ALL patients (+) MDS/AML (–) MDS/AML Number of patients 230 9 221 Median age, years 61 (31–80) 68 (53–76) 61 (3–80) Male 134 (58%) 6 (67%) 128 (56%) Median baseline ANC, × 109/L 2.8 (0.9–61.4) 3.0 (1.5–5.1) 2.8 (0.9–61.4) Median baseline β-2 microglobulin (nmol/L) 222 (43–1695) 300 (133–481) 222 (43–1695) Median baseline pl count, × 109/L 156 (5–479) 200 (43–277) 156 (5–479) Median baseline creatinine, μmol/L 87 (39–515) 97 (56–117) 86 (39–515) Median # prior regimens 2 (0–6) 2 (1–5) 2 (0–6) Prior alkylating agents (all) 218 (95%) 9 (100%) 209 (95%) Prior oral alkylators 167 (73%) 6 (67%) 162 (73%) Prior ASCT 187 (81%) 2 (78%) 180 (81%) Prior thalidomide 132 (57%) 3 (33%) 129 (58%) Prior bortezomib 109 (47%) 3 (33%) 106 (48%) Concomitant cyclophosphamide 32 (13.9%) 3 (33%) 29 (13%) G-CSF use 123 (53%) 5 (56%) 118 (53.39%) Median duration of Len (mo, range) 9.4 (0.1–67.2) 22.8 (6.6–56.6) 6.8 (0.1–67.2) Disclosures: Chen: Johnson & Johnson, Lundbeck, Celgene: Consultancy; Roche: Honoraria; Johnson & Johnson, Celgene, GlaxoSmithKline: Research Funding. Kukreti:Roche: Consultancy, Honoraria; Celgene: Honoraria; Janssen: Honoraria. Reece:Janssen: Consultancy, Honoraria, Research Funding; Merck: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Bristol Myers Squibb: Honoraria, Research Funding; Otsuka: Honoraria, Research Funding; Millennium Pharmaceuticals: Research Funding.

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)0,000
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: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,004

Scores du classifieur distillé par catégorie (deux têtes)

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

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.

Tête enseignante Opus0,017
Tête enseignante GPT0,255
Écart entre enseignants0,238 · 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
GenreEmpirique

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

En bref

Citations1
Publié2012
Routes d'admission1
Résumé présentoui

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