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Enregistrement W2908013812 · doi:10.1182/blood-2018-99-111533

Characteristics of Patients (pts) Who Relapse and Die of Multiple Myeloma (MM) within One Year Post Frontline Autologous Stem Cell Transplant (ASCT) in the Novel Agent Era: An Ultra-High Risk Population

2018· article· en· W2908013812 sur OpenAlexaff
Hatem Alahwal, Heather J. Sutherland, Shruthi Ganeshappa Kodad, Stephen H. Nantel, Yasser Abou Mourad, Michael J. Barnett, Donna L. Forrest, Alina S. Gerrie, Donna E. Hogge, Sujaatha Narayanan, Thomas J. Nevill, Maryse Power, David Sanford, Cynthia L. Toze, Jennifer White, Raewyn Broady, Kevin Song

Notice bibliographique

RevueBlood · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensUniversity of British ColumbiaBC Cancer AgencyVancouver General HospitalLeukemia & Lymphoma Society of Canada
Organismes subventionnairesnon disponible
Mots-clésMedicineLenalidomideAutologous stem-cell transplantationInternal medicineOncologyMultiple myelomaPopulationBortezomibSurgery

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: MM remains incurable but therapeutic advances has resulted in improved overall survival (OS) particularly for younger pts who are eligible for ASCT. Regardless OS improvements have been heterogeneous and it is well known that relapse within one year of ASCT is an independent negative prognostic factor. A particularly worse subgroup is pts who relapse and die of MM within a year of ASCT. There is limited data describing this subgroup of pts, the risk factors associated with their early relapse post ASCT and characteristics at relapse. Objective: Describe patient and disease related characteristics among MM pts who underwent ASCT and died of relapsed MM within the first year post ASCT in the era of novel agents. Methods: Pts were identified from the Leukemia/BMT Program of B.C. database, underwent ASCT between January 1st 2007 and July 31st 2016 and died of MM related causes within 365 days post ASCT. During this time period bortezomib (BORT) and lenalidomide (LEN) were available as second line therapy and BORT was available as induction pre-transplant for defined circumstances including high risk cytogenetics. Out of 752 ASCTs, 702 were performed as a part of initial therapy. The remaining ASCTs were performed as salvage or were the second of planned tandem ASCTs. Among the remaining 702 pts 37(5.3%) died within the first 365 days post ASCT. Of the 37 pts, 32 died from MM and related causes, 2 died of TRM from ASCT and 3 died from other causes not related to MM or ASCT. The 32 pts (4.6% of the total) who died of MM and related causes were matched with 64 controls (2:1 ratio) who were selected randomly from the remaining patient cohort and matched for age, gender, and year of transplantation. Results: There was no difference in Age at diagnosis (Median: case 61 VS control 60, P= .97) or gender (Male case 40.6% VS control 35.9%, P= .66). There was no significant difference in the prevalence of anemia, renal dysfunction, or hypercalcemia between both groups at diagnosis (table). Pts who died within the first year of ASCT had a more advanced stage at diagnosis compared to the control group (ISS Stage III: 53.1% vs 18.8%, P= .003). BORT based induction therapy was used in 84.4% of the cases compared to 53.1% in the control group, P= .001. The majority of pts in both groups had partial response or better to frontline therapy (Cases: 81.2% VS Controls 79.7%, P= .5). Only 9.4% of cases and 4.7% of controls had evidence of disease progression at the time of ASCT. High risk cytogenetics (t(4;14), t(14;16), or del 17p) were significantly more prevalent among pts who died within the first year post ASCT compared to the control (58.82% vs 31.67%, P= .009). There was no difference in the monoclonal protein subtype between the cases and controls, P= .55. The median time from ACST to disease relapse was 118 days (40-319) for the case group compared to 511 (107-1958) in the control group. Within the case group, 19 (59.3%) received LEN based therapy as second line therapy and 9 (28.1%) received BORT based therapy. Three patients (9.37%) were not candidates for any further therapy due to acute illness (2 sepsis, 1 subdural hemorrhage) related to fulminant MM relapse and one patient (3.1%) decided not to proceed with therapy due to functional decline. Overall, 17 pts (53.1%) received both BORT and LEN during the disease course, 12 (37.5%) received BORT only, 2 (6.25%) received LEN only and one received neither (3.1%). At the time of disease relapse, 9 (28.1%) had Hb level <85 g/l, 1 (3.1%) ANC<1000/mm3, 9 (28.1%) Plt <50/mm3, 9 (28.1%) GFR <20 ml/min, and 20 (62.5%) had at least one abnormal value (Hb, ANC, Plt, or Cr) and were not candidates for inclusion to clinical trials. Median OS (months) was Case 7.3 vs Control 63.8, P<.001. Conclusion: Approximately 5% of pts with MM who are ASCT eligible will die of MM within the first year post transplant. High risk cytogenetics (t(4;14), t(14;16), or del 17p) and advanced stage disease (ISS III) are risk factors for early mortality post ASCT for MM pts. These patient who relapse early typically have fulminant relapse with hematological and biochemical parameters outside of the range which would allow them to be enrolled on clinical trials and/or results in challenging standard of care management. Even in the era of novel agents, such pts do particularly poorly and represent a true unmet need in the treatment of MM. Further studies to understand the biology of their MM is required for identifying more potent therapeutic targets and protocols. 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)0,000
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 seuil0,008

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 savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 GPT0,241
Écart entre enseignants0,224 · 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
Publié2018
Routes d'admission1
Résumé présentoui

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