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Impact of Transition to Generic Imatinib in the Molecular Response Among Patients with Chronic Myeloid Leukemia

2014· article· en· W379374868 on OpenAlexaffabout
Matthew Kang, Anargyros Xenocostas, Alejandro Lazo‐Langner, Ian Chin‐Yee, Kang Howson‐Jan, Maisam Abouzeenni, Michael J. Kovacs, Cyrus C. Hsia

Bibliographic record

VenueBlood · 2014
Typearticle
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsWestern UniversityLondon Health Sciences Centre
Fundersnot available
KeywordsImatinibImatinib mesylateMedicineMyeloid leukemiaInternal medicineTyrosine-kinase inhibitorOncologyPharmacologyCancer

Abstract

fetched live from OpenAlex

Abstract Background: The introduction of Imatinib Mesylate (Gleevec™), a tyrosine kinase inhibitor (TKI), has revolutionized the management of Chronic Myeloid Leukemia (CML). Recently, on April 2, 2013, Health Canada approved two generic versions of imatinib mesylate (Apotex and TEVA) for sale in Canada—both of which, have been shown to be bioequivalent to the brand name Gleevec™, with similar serum imatinib levels and area under the curve after oral ingestion. In one of the largest case series reported to date (N=126), it has been reported that complete hematologic response (CHR) was lost in 33% of CML patients who were switched from brand name to generic imatinib. In an effort to assess the generalizability of this claim, we conducted a retrospective review of all patients with CML treated with Gleevec™ at a single tertiary care centre to evaluate whether there was a change in CHR or major molecular responses (MMR) in all patients who were switched to generic imatinib. Method: We retrospectively evaluated adult CML patients who were treated from January 1, 2002 to December 2011 with brand name Imatinib (Gleevec™) and were switched to generic imatinib (Apotex or TEVA) during 2013. Patient-reported side effect profiles were also collected in a subset of patients before and after the change from Gleevec™ to generic. A follow-up period was defined as 12 months from the time of switch from brand name to generic. The primary outcome was a composite of rates of loss of CHR and/or MMR, based on the Canadian Consensus Group of the Management of Chronic Myelogneous Leukemia (CCGM-CML). Secondary outcome include side effect profiles, graded as per the National Cancer Institute (NCI) Common Terminology Criteria for Adverse Events (CTCAE), during the follow-up period. Results: During our study period, a total 71 adult CML patients were identified. Of these, only 30 patients were included in the analysis. Among the 41 patients who were excluded, data could not be retrieved in 23 (32.4%), 9 (12.7%) were on dasatinib, 3 (4.2%) were on nilotinib, 2 (2.8%) were transplanted and 4 (5.6%) had died at the time of the switch. Data was collected using electronic medical records from patient clinic visits. The median age of all included patients was 54 years and 16 (53.3%) were male. The primary endpoint was seen in 2 of 30 patients (6.7%; 95% CI 3.5-25.6). There was a loss of MMR in 1 (3.3%) where the BCR-ABL transcript declined from a 4.19 log reduction to a 2.78 log reduction after switching to TEVA-imatinib. There was a loss of CHR in 1 (3.3%) patient, where a 20 g/L drop in hemoglobin was seen after switching to APO-imatinib. In both patients in whom the primary endpoint was seen, their imatinib dose was 200 mg before and after switching. Further, in both patients, these losses of response were transient. The secondary outcomes will be presented at the meeting. Conclusion: The generic formulations of imatinib used in Canada do not seem to be associated with the same previously reported lack of clinical efficacy when compared to brand name Gleevec™ during a follow-up period of 12 months. Further, a loss of MMR and a loss of CHR were transient in the 2 of 30 patients identified. Despite these infrequent events, treating physicians should consider that a switch to a generic formulation may be a contributing factor for the patient’s loss of MMR or CHR. However, given the wide confidence intervals, larger studies and longer follow up are needed to address this issue. Disclosures No relevant conflicts of interest to declare.

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)0.004
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.006
GPT teacher head0.238
Teacher spread0.232 · 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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Citations6
Published2014
Admission routes2
Has abstractyes

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