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Predictors of Response Duration and Survival with Second-Line Bosutinib Therapy in Patients (pts) with Chronic Phase Chronic Myeloid Leukemia (CML) Resistant or Intolerant to Prior Imatinib

2015· article· en· W2587441942 on OpenAlexaff
Jörge E. Cortes, Tim H. Brümmendorf, Hagop M. Kantarjian, Dong‐Wook Kim, Philippe Schafhausen, Sashi Nadanaciva, Nathalie Bardy‐Bouxin, Mark Shapiro, Eric Leip, Jeffrey H. Lipton, Carlo Gambacorti‐Passerini

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineBosutinibInternal medicineImatinibCumulative incidenceProportional hazards modelGastroenterologyDiscontinuationTyrosine-kinase inhibitorRetrospective cohort studyMyeloid leukemiaOncologyNilotinibCohortCancer

Abstract

fetched live from OpenAlex

Abstract Bosutinib (BOS), a Src/Abl tyrosine kinase inhibitor (TKI), is approved for adults with Philadelphia chromosome-positive (Ph+) CML that is resistant/intolerant to prior therapy. In this retrospective analysis, baseline and on-treatment characteristics of chronic phase (CP) CML pts receiving second-line BOS following imatinib resistance (IM-R) or intolerance (IM-I) in an ongoing open-label, phase 1/2 study and a long-term extension study were examined to identify potential predictors of duration of major cytogenetic response (MCyR), overall survival (OS), and progression-free survival (PFS), using a backward-elimination multivariate Cox regression model. A total of 284 (IM-R, n=195; IM-I, n=89) pts who received BOS starting at 500 mg/d were included in this analysis. Median (range) age was 53 (18‒91) y; time from CML diagnosis was 3.7 (0.1‒15.1) y; treatment duration was 25.6 (0.2‒106.7) mo; follow-up duration was 53.7 (0.5‒106.8) mo. For the last enrolled patient, time from first BOS dose was ≥6 y. After ≥6 y of follow-up, median MCyR duration and OS were not yet reached. Kaplan-Meier estimated probability of maintaining MCyR at 6 y was 71%, OS rate was 83%, and cumulative incidence of on-treatment disease progression or death was 21%. Several factors were identified as predictive of MCyR duration, OS or PFS, including baseline Ph+ ratio ≥95% vs ≤35% and MCyR by week 12, which were significant predictors of all 3. Other significant predictors of decreased OS included: age ≥65, BOS-sensitive mutations vs no mutations and higher peripheral blood (PB) blasts at baseline (all P ≤0.031; Table). Other significant predictors of decreased PFS included: higher PB blasts and no dose reduction to 400 mg/d due to AEs (all P ≤0.025; Table). Prior IM response or resistance did not predict long-term outcomes, nor did any treatment-emergent adverse events examined except for abnormal liver function test (LFT), which was predictive of increased OS. In conclusion, pts with CP CML resistant/intolerant to IM treated with BOS were identified as having an increased risk of poorer outcomes if they had the following characteristics: baseline Ph+ ratio ≥95% vs ≤35%, higher PB blasts at baseline or no MCyR by week 12. Having a better understanding of factors that may be predictive of long-term patient outcomes with TKI therapies may aid healthcare providers in the future selection of optimal treatment regimens for pts with Ph+ CML. Disclosures Cortes: ARIAD Pharmaceuticals Inc.: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Teva: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding. Brümmendorf:Ariad: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Patent: Patents & Royalties: Patent on the use of imatinib and hypusination inhibitors. Kim:BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; ILYANG: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Schafhausen:ARIAD: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Novartis: Consultancy, Honoraria. Nadanaciva:Pfizer Inc: Employment. Bardy-Bouxin:Pfizer Inc: Employment. Shapiro:Pfizer Inc: Employment, Other: Stock Ownership. Leip:Pfizer Inc: Employment. Lipton:Ariad: Equity Ownership, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Gambacorti-Passerini:Pfizer: Consultancy, Research Funding; BMS: Consultancy.

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)0.000
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
Metaresearch0.0000.001
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 integrity0.0000.000
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 head0.019
GPT teacher head0.274
Teacher spread0.255 · 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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Citations0
Published2015
Admission routes1
Has abstractyes

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