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Prolonged Clinical and Molecular Remissions Following High-Dose Therapy/Autologous Stem Cell Transplantation (HDT/ASCT) and Rituximab and Interferon-alpha Maintenance for Relapsed High-Risk Follicular Lymphoma.

2007· article· en· W2553478512 on OpenAlexaff
Matthew C. Cheung, Neil L. Berinstein, Nancy Pennell, Lisa K. Hicks, Kevin Imrie, Eugenia Piliotis, Violet Milliken, Marciano D. Reis, Rena Buckstein

Bibliographic record

VenueBlood · 2007
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsSt. Michael's HospitalSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineRituximabInternal medicineFollicular lymphomaAutologous stem-cell transplantationTransplantationSalvage therapyMaintenance therapyGastroenterologyCyclophosphamideOncologySurgeryLymphomaChemotherapy

Abstract

fetched live from OpenAlex

Abstract High-dose therapy and autologous stem cell transplantation (HDT/ASCT) are associated with prolonged remissions in relapsed follicular lymphoma (FL). Maintenance rituximab (R) has an accepted role in extending remissions and preclinical evidence suggests that its effects may be enhanced by the immunomodulatory capacity of interferon alpha (IFN-α). We designed a phase II study to incorporate in-vivo purging (with R) and post-transplant maintenance immunotherapy (with combined R and IFN-α) to prolong the remissions attained by HDT/ASCT. We present a planned analysis of 30 patients age ≤65 with 1–2 relapses of FL. Individuals received salvage CHOP or DHAP and proceeded with stem cell mobilization and HDT/ASCT with cyclophosphamide/carmustine/etoposide if they achieved ≥75% reduction in bulk and <15% marrow involvement. R 375 mg/m2 was given as 3 weekly doses prior to collection and as 6 weekly maintenance doses starting 12 weeks post-ASCT. IFN-α was initiated at week 10 post-ASCT with titration to a dose of 3 million units/m2 tiw for 2 years. Samples for PCR (sensitivity 0.01%) of t(14;18) or VDJ rearrangements were taken from blood/marrow to assess for molecular remission (MR). Results: Twenty-nine patients are assessable with a median follow-up for survivors of 3.1 years. Median age was 46 years (30–65) and median number of prior regimens was 2. Median response duration to prior therapy was 0.6 years and patients were enrolled 2.3 years (median) following diagnosis. The overall response rate to salvage was 93% (95% CI 83.7% to 100%) and n=23 proceeded to HDT/ASCT. Six patients did not undergo ASCT due to inadequate response (n=2), failed mobilization (n=2), cardiomyopathy (n=1), and patient withdrawal (n=1). Significant non-hematologic ASCT toxicities (grade 3/4) included: 5 episodes of interstitial pneumonitis, retinal vein occlusion (n=1), and thrombotic thrombocytopenic purpura (n=1). One patient was diagnosed with ALL 30 months following ASCT. Twenty-one individuals initiated IFN-α with 14 able to complete 2-years of maintenance (median dose of 3 × 106 units/m2 tiw). The most common reason for discontinuation was depression. At baseline, 19 patients had detectable markers by PCR. Despite in-vivo purging with R, 8 of 17 stem cell grafts had molecular disease, although graft contamination did not affect subsequent MR (p=NS). Of 16 assessable patients post-transplantation, 11/16 achieved MR prior to immunotherapy and 16/16 achieved MR during maintenance. Three patients have had a molecular relapse at 12, 18, and 36 months post-ASCT, with molecular preceding clinical relapse in 2/3 patients. Median progression-free survival for all patients is 50 months and median overall survival has not been reached. Conclusions: HDT/ASCT was feasible and well-tolerated in this high-risk population of relapsed FL. Molecular detection of lymphoma in the auto-graft did not preclude extended MR and clinical remissions post-transplant. This may be due to the enhanced clearance of minimal residual disease achieved by combination maintenance immunotherapy (R and interferon-α) post-ASCT. This is our third study in a sequential program of HDT/ASCT trials incorporating immunotherapy pre- and post-transplantation; we will present comparative evidence across the series to determine the added benefit of IFN-α in this latest approach.

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)0.001
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.269
Teacher spread0.257 · 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

Citations3
Published2007
Admission routes1
Has abstractyes

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