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Enregistrement W2736866953 · doi:10.1182/blood.v128.22.690.690

Impact of Wait Times for Autologous Stem Cell Transplantation in Patients with Aggressive Non-Hodgkin Lymphoma, a Subset Analysis of the Canadian Cancer Trials Group (CCTG) LY.12 Clinical Trial

2016· article· en· W2736866953 sur OpenAlexaffabout
Tanya Skamene, Wenyu Jiang, Ralph M. Meyer, Michael Crump, John Kuruvilla, C. Tom Kouroukis, Stefano Luminari, Stephen Couban, Matthew C. Cheung, David A. Rizzieri, Peter Bardy, Joseph L. Pater, Marina Djurfeldt, Lois E. Shepherd, Bingshu E. Chen, Annette E. Hay

Notice bibliographique

RevueBlood · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphoma Diagnosis and Treatment
Établissements canadiensHealth Sciences CentreDalhousie UniversityJuravinski HospitalQueen's UniversityMcMaster UniversitySunnybrook Health Science CentreJuravinski Cancer CentrePrincess Margaret Cancer CentreCanadian Partnership Against Cancer
Organismes subventionnairesnon disponible
Mots-clésMedicineAutologous stem-cell transplantationInternal medicineGemcitabineOncologyTransplantationSalvage therapySurgeryChemotherapyMitoxantrone

Résumé

récupéré en direct d'OpenAlex

Abstract Background: High dose chemotherapy followed by autologous stem cell transplant (ASCT) is the standard curative option for patients with relapsed or refractory, chemosensitive, aggressive non-Hodgkin lymphoma (NHL). The optimal timing for ASCT following salvage chemotherapy is not known. Cancer Care Ontario (CCO)-the cancer agency for Ontario, Canada's largest province-treatment guidelines recommend that no more than 91 days should elapse from the first day of salvage chemotherapy to stem cell transplant. We evaluated the impact of time to stem cell transplant in the context of the international CCTG LY.12 phase 3 clinical trial. Methods: Patients with relapsed or refractory (R/R) aggressive NHL were randomly assigned to gemcitabine, cisplatin and dexamethasone (GDP) or dexamethasone, cytarabine, cisplatin (DHAP), with or without rituximab, followed by ASCT [Crump JCO 2014]. Time interval definitions were based on CCO guidelines: Total Wait Time (TWT) as the number of days from the first day of salvage chemotherapy to day of ASCT; Apheresis Wait Time (AWT) as the number of days from the first day of salvage to the first day of stem cell collection; Stem cell transplant Wait Time (SWT) as the number of days from the last day of stem cell collection to the day of ASCT. Patients were considered to have experienced a delay in TWT, AWT or SWT if the time intervals exceeded 91, 70 and 21 days respectively. Overall survival (OS) and event-free survival (EFS) from transplant date were compared between patients who met and exceeded TWT targets using a Cox proportional hazards model. A linear regression model was applied to analyze TWT as a continuous variable. Univariate and multivariate analyses were performed to estimate the adjusted hazard ratio (HR) for TWT for the following co-variables: age ≤60, performance status 0/1, disease stage (I/II), presence of ≤1 extranodal sites, and response after cycle 2 (complete response, CR; complete response, unconfirmed, CRu; partial response, PR). Results: Of 619 patients enrolled on LY.12, 307 (47%) had sufficient response to salvage chemotherapy and adequate stem cell collection to complete ASCT on protocol. Among these, median age was 54.6 years, 64% were male and 94% had a performance status of 0 or 1. International Prognostic Index (IPI) score at relapse was 0-1 in 45%, 2 in 31% and ≥3 in 24%. The majority of patients had poor risk disease at study entry; 58% had a best response of stable disease (SD) or progressive disease (PD) to primary therapy, or initial duration of response < 1 year. Following up to 2 cycles of salvage chemotherapy, 75/307 (24%) achieved CR/CRu, 142/307 (46%) achieved PR, 89/307 (29%) had SD. One patient had missing data. The median TWT for the total transplanted population was 91 days (range 50-217). Median AWT and SWT were 63 (range 0-151) and 26 (range 6-146) days, respectively. Fifty percent of patients exceeded TWT target of 91 days; 32% and 57% of patients exceeded AWT and SWT targets. There was no difference in median OS (HR 0.96, 95% CI 0.66-1.39, p=0.81) or EFS (HR 1.13, 95% CI 0.82-1.55, p=0.46) between patients who exceeded and met TWT targets. The 4-year OS for patients who met and exceeded TWT was 62% and 64%, respectively. The 4-year EFS for patients who met and exceeded TWT was 43% and 50%, respectively. When analyzed as a continuous variable, TWT did not affect OS (HR 0.99) or EFS (HR 0.99). Comparison of the quartiles with shortest and longest TWT demonstrated HR 0.72 (95% CI 0.42-1.26, p=0.25) for overall survival and 0.69 (95% CI 0.44-1.09, p=0.11) for EFS. Comparison of the 10th and 90th percentiles for TWT demonstrated HR 0.67 (95% CI 0.28-1.59, p=0.36) for overall survival and 0.71 (95% CI 0.35-1.44, p=0.34) for EFS. Only the presence of ≤1 extranodal sites of disease was found to be predictive of OS in the transplanted population on univariate and multivariate analysis (adjusted HR 0.51, p=0.005). The median TWT was longer for the 31 patients transplanted at Italian centers, compared to 266 transplanted at Canadian centers (median TWT 90 vs. 118 days, t < 0.0001). Conclusion: In this exploratory analysis, limited to patients who completed transplant on the LY.12 clinical trial, we did not find evidence that those meeting current CCO ASCT wait time targets had superior outcomes compared with those who did not. Table. Table. Figure 1. Figure 1. Figure 2. Figure 2. Disclosures Kuruvilla: BMS: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Amgen: Honoraria; Abbvie: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Merck: Honoraria; Roche Canada: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Lundbeck: Honoraria. Luminari:Roche: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accomodations, Expenses; Takeda: Other: Travel, Accomodations, Expenses; Teva Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria. Hay:Amgen: Research Funding; Novartis: Research Funding; Janssen: Research Funding; Kite 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)0,006
score de la tête « metaresearch » (Gemma)0,008
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: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,929
Score d'incertitude au seuil0,141

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0060,008
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,004
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0010,000
Intégrité de la recherche0,0010,002
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 Opus0,033
Tête enseignante GPT0,333
Écart entre enseignants0,300 · 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
Publié2016
Routes d'admission2
Résumé présentoui

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