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Record W2621834912 · doi:10.1002/hon.2439_120

PROLONGED MOLECULAR AND CLINICAL REMISSIONS IN FOLLICULAR LYMPHOMA PATIENTS TREATED WITH HDT/ASCT AND COMBINATION IMMUNOTHERAPY WITH RITUXIMAB AND INTERFERON α

2017· article· en· W2621834912 on OpenAlexaff
Neil L. Berinstein, Liam Smyth, Nancy Pennell, Rashmi Weerasinghe, Matthew C. Cheung, Kevin Imrie, David Spaner, Lisa Chodirker, Eugenia Piliotis, Violet Milliken, Angela Boudreau, Liying Zhang, Marciano D. Reis, Alden Chesney, David Good, Zeina Ghorab, Rena Buckstein

Bibliographic record

VenueHematological Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsKingston General HospitalHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineInternal medicineRituximabOncologyFollicular lymphomaMinimal residual diseaseAutologous stem-cell transplantationSurgeryBone marrowLymphoma

Abstract

fetched live from OpenAlex

Introduction: Follicular lymphoma is an indolent disease with a relapsing remitting course and shorter remission periods with each successive treatment. The median PFS and OS for patients who relapse within 12 m of prior therapy are 13 m and 60 m, respectively. Strategies to improve outcome including combining autologous stem cell transplant (ASCT) with effective immunotherapies such as rituximab (R) and/or interferon α (IFN α) could be considered. Detailed long-term data, including impact of minimal residual disease (MRD) status on PFS, are lacking for combination approaches such as this. We present long-term follow-up of a median 10 y of PFS and MRD on a cohort of 30 patients who received ASCT followed by maintenance R-IFN α. Methods: Patients in 1st or 2nd relapse were enrolled in this prospective study. Salvage included CHOP or DHAP with 3 weekly infusions of R prior to stem cell harvest as an “in vivo purge”. Patients then received high-dose therapy with cyclophosphamide, BCNU and etoposide followed by ASCT. IFN α began at 3-m post ASCT for 2 y with 6 weekly infusions of R from week 14. Response assessment included clinical, radiographic, and MRD assessments of bone marrow (BM) and peripheral blood (PB). Real-time quantitative PCR was used to evaluate MRD on the apheresis product and on BM and PB Q3m post ASCT for 1 y and Q6m from then on. An extended follow-up study included MRD assessment on patients who remained in CR. Results: From July 2000 to September 2009, 36 patients were enrolled with a mean age of 47 y (30–66 y). Sixty-seven percent of patients had stage IV disease, 50% had a FLIPI score of 3 or 4, and the median time from previous chemotherapy to enrolment was 12.8 m. Six patients were not transplanted. The median follow-up was 124 m (range 23–194 m), the 10-y OS and EFS was 69% and 40%, respectively, in the ITT population, and 50% and 56% in the SCT group. There was evidence of plateau at 100-m post ASCT. Seven transplanted patients died: 4 from progressive disease and 3 from secondary malignancies. Of the 30 transplanted, there were PCR markers for 22 (73%). Although 10/22 (45%) stem cell collections were MRD+, PFS was not significantly different from patients transplanted with MRD− grafts. Clinical and molecular remission in PB was achieved after R-IFN in 5 of 7 patients who were MRD positive in the BM at 3-m post ASCT. Both of these results suggest that R-IFN may be effective in eradicating MRD post ASCT. There appears to be good correlation between MRD assessment on PB and clinical response/relapse (Figure 1). Fifteen patients reached 100-m EFS, and of these, 9 PCR evaluable patients were also in molecular remission. Uni- and multi-variate analyses were performed. Keywords: autologous stem cell transplantation (ASCT); follicular lymphoma (FL); minimal residual disease (MRD).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.041
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

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

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 head0.021
GPT teacher head0.330
Teacher spread0.308 · 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 teacher head, 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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