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Effect of continued imatinib (IM) in pts with detectable BCR-ABL after ≥ 2 years on study on deep molecular responses (MR): 36-month update from ENESTcmr.

2014· article· en· W2591377132 on OpenAlexaff
Nelson Spector, Nelma Cristina D. Clementino, Pedro Enrique Dorlhiac‐Llacer, Brian Leber, Timothy P. Hughes, Francisco Cervantes, Anthony P. Schwarer, Donna L. Forrest, Suzanne Kamel‐Reid, Israel Bendit, Sandip Acharya, LaTonya Collins, Darshan Dalal, Jeffrey H. Lipton

Bibliographic record

VenueJournal of Clinical Oncology · 2014
Typearticle
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsPrincess Margaret Cancer CentreVancouver General HospitalOntario Institute for Cancer ResearchMcMaster University
Fundersnot available
KeywordsMedicineImatinibNilotinibImatinib mesylateInternal medicineGastroenterologyNuclear medicineMyeloid leukemia

Abstract

fetched live from OpenAlex

7025 Background: With 24 mo f/u, ENESTcmr demonstrated higher rates of stable, deep MRs with nilotinib (NIL) vs IM in pts on long-term (≥ 2 y) IM with residual disease. Here, we present 36-mo results, including crossover from IM to NIL after 2 y on study. Methods: Pts with Philadelphia chromosome–positive CML-CP (N = 207) with complete cytogenetic response but detectable BCR-ABL (by RQ-PCR with a sensitivity of ≥ 4.5 logs) after ≥ 2 y on IM were randomized to NIL 400 mg twice daily (BID; n = 104) or IM 400 or 600 mg once daily (QD; n = 103). Crossover from IM to NIL was allowed for pts with detectable BCR-ABL after 24 mo, treatment failure, or confirmed (≥ 2 consecutive assessments) loss of response at any time. Results: Significantly more pts achieved MR4.5 by 36 mo with NIL (Table). Median time to MR4.5 was 24 mo in the NIL arm and not reached in the IM arm with 36 mo f/u. 46 of 103 (45%) pts randomized to IM crossed over to NIL. When accounting only for responses up to crossover, 47% and 24% of pts on NIL and IM, respectively, achieved MR4.5 (P = .0003). At 24 mo, 52 pts on NIL and 78 pts on IM had detectable disease; 4/52 who continued NIL, 0/35 who continued IM, and 11/43 who crossed over from IM to NIL achieved undetectable BCR-ABL by 36 mo. The rate of MR4.5 appeared higher in pts randomized to NIL (33% by 1 y in pts without MR4.5 at baseline [BL]) than in pts who crossed over to NIL (21%) with similar follow-up. Adverse event profile was similar to the 12 mo report. Conclusions: By 36 mo, significantly more pts achieved MR4.5 by switching to NIL vs remaining on IM and median time to MR4.5 was accelerated by more than 1 y in the NIL arm. Pts with detectable disease who crossed over from IM to NIL after 24 mo were able to achieve deep MRs by 36 mo on study, whereas no pts who remained on IM achieved undetectable BCR-ABL. Delaying switching from IM to the more potent BCR-ABL inhibitor NIL does not increase the proportion of pts achieving deep MR. Clinical trial information: CAMN107A2405. NIL 400 mg BID (n = 98) IM 400 or 600 mg QD (n = 96) P Value MR4.5 in pts without MR4.5 at BL (intention to treat analysis) n (%) n (%) By 12 mo 32 (33) 13 (14) 0.0020 By 24 mo 42 (43) 20 (21) 0.0006 By 36 mo 46 (47) 32 (33) 0.0453 By 36 mo, excluding pts who crossed over to NIL 46 (47) 23 (24) 0.0003

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.025
GPT teacher head0.401
Teacher spread0.376 · 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".

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Citations1
Published2014
Admission routes1
Has abstractyes

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