MétaCan
Menu
← Back to cohort
Record 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 on 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

Bibliographic record

VenueBlood · 2016
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsHealth Sciences CentreDalhousie UniversityJuravinski HospitalQueen's UniversityMcMaster UniversitySunnybrook Health Science CentreJuravinski Cancer CentrePrincess Margaret Cancer CentreCanadian Partnership Against Cancer
Fundersnot available
KeywordsMedicineAutologous stem-cell transplantationInternal medicineGemcitabineOncologyTransplantationSalvage therapySurgeryChemotherapyMitoxantrone

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.929
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.333
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueBlood→Same topicLymphoma Diagnosis and Treatment→French-language works237,207→