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Treatment-Free Remission (TFR) Eligibility in Patients (pts) with Chronic Myeloid Leukemia in Chronic Phase (CML-CP) and Residual Disease on Long-Term Imatinib (IM) Who Switched to Second-Line Nilotinib (NIL)

2015· article· en· W2545387711 on OpenAlexaffabout
Timothy P. Hughes, Francisco Cervantes, Nelson Spector, Brian Leber, Susan Branford, Tara Glynos, Sandip Acharya, Darshan Dalal, Jeffrey H. Lipton

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoMcMaster University
Fundersnot available
KeywordsNilotinibMedicineImatinibInternal medicineImatinib mesylateMyeloid leukemiaDasatinibTyrosine-kinase inhibitorGastroenterologySurgeryCancer

Abstract

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Abstract Background: The randomized, phase 3 ENESTcmr study evaluated whether pts with CML-CP with detectable residual disease on long-term IM could achieve deeper molecular responses (MRs) by switching to NIL vs remaining on IM. Achievement of a sustained deep MR is a key prerequisite for successful TFR following frontline tyrosine kinase inhibitor (TKI) therapy; however, limited data are available on TFR following second-line TKI therapy. To estimate the proportion of pts who may be eligible to attempt TFR following second-line NIL, we analyzed 4-y data from ENESTcmr to evaluate the proportion of pts who maintained MR4.5 (BCR-ABL1 ≤ 0.0032% on the International Scale) for 1 y after achieving it after ≥ 2 y on second-line NIL. Methods: In ENESTcmr (NCT00760877), pts with CML-CP with complete cytogenetic response but detectable BCR-ABL1 after ≥ 2 y on IM were randomized to NIL 400 mg twice daily (BID; n = 104) or IM (400 or 600 mg once daily; n = 103). Pts in the IM arm could cross over due to detectable BCR-ABL1 after 2 y on study or treatment failure/confirmed loss of response at any time. In this exploratory analysis of data from ENESTcmr, key criteria for attempting TFR in ENESTop (NCT01698905) were applied a posteriori to estimate the rate of eligibility to attempt TFR with second-line NIL. These criteria included ≥ 3 y of total TKI therapy (≥ 4 weeks of frontline IM and ≥ 2 y of second-line NIL), with MR4.5 achieved on NIL and sustained MR4.5 on NIL for an additional ≥ 1 y. A time-to-event analysis was used to estimate the rate of eligibility for TFR, using these criteria, among pts randomized to the ENESTcmr NIL arm; pts who discontinued early were censored at the data cutoff date, and pts who did not meet the eligibility criteria but were still on treatment at the data cutoff were censored at the date of last dose. Results: Most pts in ENESTcmr had received > 3 y of prior IM (NIL 400 mg BID arm, 83%; IM arm, 80%). At the data cutoff (minimum follow-up of 4 y), 59/104 pts in the NIL arm, 36/46 pts who crossed over from IM to NIL, and 41/57 pts in the IM arm who did not cross over remained on study treatment. Median time receiving NIL was 3.9 y among pts in the NIL arm and 1.8 y among pts who crossed over from IM to NIL. By 4 y, rates of MR4.5 in pts without MR4.5 at study entry (NIL, n = 98; IM, n = 96) were 52% and 42% in the NIL and IM arms, respectively; when responses achieved after crossover from IM to NIL were excluded, rates were 52% and 28%, respectively. Among pts who crossed over, 13/46 (28%) achieved a first MR4.5 on NIL after crossover. By 4 y, 44/104 pts in the NIL arm (42.3%) had received ≥ 2 y of NIL and achieved MR4.5 on NIL (Figure). Five of these 44 pts achieved MR4.5 between 3 and 4 y and were therefore not evaluable for sustained MR4.5 for ≥ 1 y by the data cutoff; of the pts who achieved MR4.5 by 3 y, 17/39 (43.6%) had sustained MR4.5 for ≥ 1 y on NIL by 4 y. Overall among pts randomized to NIL (n = 104), an estimated 17.4% (95% CI, 11.1%-26.7%) had both a ≥ 3-y duration of NIL treatment and a ≥ 1-y duration of sustained MR4.5. A similar analysis to estimate the proportion of pts who achieved a sustained deep MR with continued IM therapy was not possible due to the confounding effect of a large proportion of pts crossing over to NIL (46/103) during the study. Similarly, because most of the 46 pts who crossed over to NIL received < 2 y of NIL by the 4-y data cutoff, the rate of sustained deep MR on NIL could not be evaluated in these pts. Conclusion: For pts in whom TFR is a treatment goal, achievement of a sustained deep MR is a critical milestone. By 4 y in ENESTcmr, 43.6% of pts (17/39) with ≥ 2 y of second-line NIL who achieved MR4.5 by 3 y also sustained this response for an additional ≥ 1 y on NIL (the key ENESTop criteria for attempting TFR). The optimal depth and duration of MR for successful TFR following second-line TKI therapy have not been determined, and the proportion of pts eligible to attempt TFR would be expected to vary between studies, depending on the specific criteria required for attempting TFR. Overall, these results suggest that for pts lacking deep MR on frontline IM, switching to second-line NIL may provide a route to TFR eligibility. Figure 1. Figure 1. Disclosures Hughes: ARIAD: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Off Label Use: Nilotinib is currently approved for the treatment of patients with newly diagnosed CML in chronic phase and in patients with CML in chronic phase or accelerated phase who are resistant or intolerant to previous therapy including imatinib. The ENESTcmr study (results of which are presented in this abstract) evaluated the safety and efficacy of second-line nilotinib in patients with complete cytogenetic response but with detectable levels of BCR-ABL1 transcripts after 2 y frontline imatinib.. Cervantes:Novartis: Consultancy, Speakers Bureau; Sanofi-Aventis: Consultancy; CTI-Baxter: Consultancy, Speakers Bureau. Spector:Novartis Pharmaceuticals: Research Funding. Leber:Celgene Canada: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis Canada: Honoraria, Membership on an entity's Board of Directors or advisory committees. Branford:Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Ariad: Research Funding; Qiagen: Membership on an entity's Board of Directors or advisory committees. Glynos:Novartis Pharmaceuticals: Employment. Acharya:Novartis Healthcare Pvt. Ltd.: Employment. Dalal:Novartis: Employment, Equity Ownership. Lipton:Ariad: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Teva: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Novartis Pharmaceuticals: Consultancy, Research Funding.

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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)0.002
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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.311
Teacher spread0.286 · 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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Citations3
Published2015
Admission routes2
Has abstractyes

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