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Phase II multicenter study of oblimersen sodium, a Bcl‐2 antisense oligonucleotide, in combination with rituximab in patients with recurrent B‐cell non‐Hodgkin lymphoma

2008· article· en· W1963879883 on OpenAlexaff
Barbara Pro, Brian Leber, Mitchell R. Smith, Luis Fayad, Jorge Romaguera, Fredrick B. Hagemeister, Maria Alma Rodriguez, Peter McLaughlin, Felipe Samaniego, James A. Zwiebel, Adriana López, Larry W. Kwak, Anas Younes

Bibliographic record

VenueBritish Journal of Haematology · 2008
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsMcMaster University
FundersNational Cancer Institute
KeywordsRituximabLymphomaMedicineCancer researchOligonucleotideHodgkin lymphomaMonoclonalInternal medicineOncologyMonoclonal antibodyImmunologyChemistryAntibodyBiochemistryGene

Abstract

fetched live from OpenAlex

Oblimersen sodium plus rituximab was evaluated in relapsed/refractory B-cell non-Hodgkin lymphoma (NHL) patients. Oblimersen was administered as a continuous intravenous infusion at a daily dose of 3 mg/kg/d for 7 d on alternate weeks for 3 weeks. Rituximab was given at a weekly dose of 375 mg/m(2) for six doses. Patients with stable disease or objective response were allowed to receive a second course of treatment. The overall response rate (ORR) was 42% with 10 complete responses (CR) and eight partial responses (PR). Twelve (28%) patients achieved a minimal response or stable disease. Among the 20 patients with follicular lymphoma the ORR was 60% (eight CR, four PR). Three of the responders were refractory to prior treatment with rituximab, and two of the responses occurred in patients who had failed an autologous stem cell transplant. Median duration of response was 12 months. Most toxicities were low grade and reversible. In conclusion, oblimersen sodium can be safely combined with rituximab. The combination appears to be most beneficial in patients with indolent NHL and warrants further investigation in a large randomized trial.

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 score0.241
Threshold uncertainty score0.696

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 head0.010
GPT teacher head0.249
Teacher spread0.239 · 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".

Quick stats

Citations105
Published2008
Admission routes1
Has abstractyes

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