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Autologous Transplantation As Consolidation for High Risk Aggressive T-Cell Non-Hodgkin's Lymphoma: A SWOG S9704 Intergroup Trial Subgroup Analysis

2016· article· en· W2713994360 on OpenAlexaff
Patrick J. Stiff, Hongli Li, James R. Cook, Louis S. Constine, Stephen Couban, Douglas A. Stewart, Thomas C. Shea, Pierluigi Porcu, Jane N. Winter, Brad S. Kahl, Sonali M. Smith, Deborah Marcellus, Kevin Barton, Glenn Mills, Michael LeBlanc, Lisa M. Rimsza, Stephen J. Forman, John P. Leonard, Richard I. Fisher, Jonathan W. Friedberg

Bibliographic record

VenueBlood · 2016
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsJuravinski HospitalDalhousie University
Fundersnot available
KeywordsMedicineAutologous stem-cell transplantationInternal medicineAggressive lymphomaOncologyLymphomaTransplantationCHOPRandomized controlled trialInternational Prognostic IndexDiffuse large B-cell lymphomaRegimenRituximab

Abstract

fetched live from OpenAlex

Abstract Background: We recently clarified the use of consolidative autologous stem cell transplantation (ASCT) as first remission consolidation therapy for high grade diffuse aggressive T and B non-Hodgkin's lymphoma (NHL)in patients with high-intermediate (HI) or High (H) age adjusted IPI disease (Stiff et al, NEJM 369:1681). After receiving CHOP or R-CHOP for 5 cycles responding patients were randomized to either 3 more induction cycles or 1 cycle followed by an ASCT using either a BCNU or TBI based preparative regimen. We found a PFS but not OS advantage for those randomized to transplant and no differential treatment effect for those with T-NHL patients as compared to B-NHL in the initial analysis of this study. In light of Phase II data suggesting a value of early ASCT for T-NHL, a lack of randomized ASCT trials for T-NHL and the inferior prognosis for T-NHL as compared to B cell disease, we further evaluated this sub group, since a post hoc analysis of the entire trial did find a survival advantage for those with H IPI disease. This then provided a unique opportunity to evaluate the role of ASCT consolidation for T-cell NHL in the setting of a prospective randomized trial. Method: Among the 370 eligible B-NHL and T-NHL patients with HI/H IPI disease treated on this trial, 40 had a T-NHL phenotype and were the subject of this analysis. Individual patient files were re-reviewed and those randomized after the first 5 cycles of CHOP were further analyzed for stage, IPI group, histology (centrally reviewed), and response to induction and consolidation and updated survival outcome. Results: Of the 40 T-NHL patients enrolled on study, 28 (70%) were randomized after induction therapy, a similar ratio to the entire trial (68%). Twelve were not randomized; 1 was ineligible for study, and of the eligible 11, 9 were HI IPI and 8 had peripheral T cell (PTCL-NOS). These 11 were not randomized due to patient choice in 2, and all of the remaining 9 pts progressed early: 2 after C1; 3 after C3, 1 after C4, and 3 after C5. For the 28 randomized, their median age was 50 and 19 were males. Of the group, 21/28 had B symptoms at diagnosis, 14 had stage IV disease, and 18 and 10 were in the HI and H IPI groups respectively. Histologies included 11 with PTCL-NOS, 7 angioimmunoblastic and 10 anaplastic large cell NHL. At randomization 13 were to continue CHOP and 15, ASCT. Of the 15 assigned to ASCT, 3 did not undergo transplant (2-refusals, 1- unable to mobilize); 7 received the BCNU-etoposide-cyclophosphamide and 5 the TBI-etoposide-cyclophosphamide preparative regimen. The 5 year estimates of PFS and OS for the randomized ASCT vs CHOP only groups (intent to treat) were 40% vs 38% (p=0.56) and 40% vs 45% (p=0.98) respectively. We found no difference in outcome based on IPI group, histology or stage of disease. Interestingly, only 1/7 patients who received BCV as the ASCT preparative regimen are long term survivors vs 4/5 receiving the TBI-based regimen. Conclusions: We did not observe a PFS/OS advantage for those with high-risk T-NHL in first remission randomized to ASCT following CHOP induction vs CHOP alone in this retrospective analysis. In addition, the 30% early drop out rate before randomization due primarily to early progression strongly suggests that more optimal induction regimens need to be developed for this disease. While the numbers are small the finding that TBI based preparative regimens might be associated with a higher PFS is of interest and deserves further study. Support: NIH/NCI grants CA180888 and CA180819; Bristol-Myers Squibb. Contributions of Dr. Raymond R Tubbs, deceased, are gratefully acknowledged. Figure 1 Figure 1. Disclosures Porcu: miRagen: Other: Investigator in a clinical trial; celgene: Other: Investigator in a clinical trial; Millenium: Other: investigator in a clinical trial; Innate Pharma: Other: Investigator in a clinical trial. Winter:Pharmacyclics: Research Funding; Medivation: Other: Provision of investigational agent for clinical trial; Seattle Genetics: Research Funding; GSK: Research Funding. Kahl:This study was coordinated by the ECOG-ACRIN Cancer Research Group (Robert L. Comis, MD and Mitchell D. Schnall, MD, PhD, Group Co-Chairs) and supported by the National Cancer Institute of the National Institutes of Health under the following award number: Research Funding. Smith:Juno: Consultancy; TGTX: Consultancy; AbbVie: Consultancy; Celgene: Consultancy; Genentech: Consultancy, Other: on a DSMB for two trials ; Gilead: Consultancy; Portola: Consultancy; Amgen: Other: Educational lecture to sales force; Pharmacyclics: Consultancy. Rimsza:NCI/NIH: Patents & Royalties: L.M. Rimsza is a co-inventor on a provisional patent, owned by the NCI of the NIH, using Nanostring technology for determining cell of origin in DLBCL.. Fisher:Gilead: Consultancy; Seattle Genetics: Consultancy; Johnson and Johnson: Consultancy. Friedberg:Bayer: Honoraria, Other: Data Safety Monitoring Board.

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)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0050.010
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.007
GPT teacher head0.253
Teacher spread0.246 · 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 designNon-randomized trial
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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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