BCR-ABL1 Transcript Doubling Time after Imatinib Discontinuation for Treatment-Free Remission in Chronic Myeloid Leukemia in Chronic Phase: Predictor for Treatment-Free Remission Failure
Bibliographic record
Abstract
Background: The Canadian tyrosine kinase inhibitor (TKI) discontinuation trial, named "Treatment Free Remission Accomplished By Dasatinib " (NCT#02268370), has reported 56.8% molecular relapse-free survival (mRFS) rate at 12 months after imatinib (IM) discontinuation. MMR loss occurred quickly after IM discontinuation, typically within 2-4 months, while those who lost MR4 on two consecutive measurements tended to lose their molecular response more gradually. BCR-ABL transcript doubling time (DT) after TKI discontinuation is a reciprocal concept to transcript halving time following TKI therapy. Due to inter-individual differences in DT after TKI discontinuation, DT can be used as a potential biomarker to identify those patients at high-risk for TFR failure when measured before they experience a clinically significant event of molecular relapse. The present study has not only evaluated the kinetics of BCR-ABL transcript rise after IM discontinuation, but also explored the predictive/prognostic role of DT of BCR-ABL transcript level as an early predictor of TFR failure. Patients and methods: Changes of BCR-ABL1 transcript level in each patient were assessed monthly by estimating the number of days required for BCR-ABL1 to double from the previous expression level/measurement, termed the DT. Based on the BCR-ABL1 qPCR value taken monthly in the first 6 months after IM discontinuation, DT was calculated monthly, as x = ln(2)/K, where x is the DT and K is the fold BCR-ABL1 change from the previous value divided by the number of days between each measurement. K was determined as follows: K = [ln(b) - ln(a)]/t, where a is the BCR-ABL1 value of the previous measurement, b is the BCR-ABL1 at the relevant time point, and t is the number of days between measurements. The baseline qPCR level from the prior month to TKI discontinuation was referenced. The distribution of DT was assessed at each time point of DT measurement within the first 6 months. In order to define cut-off levels for BCR-ABL1 qPCR and DT for the first 6 months, multiple statistical parameters were taken into account including positive (PPV) and negative predictive value (NPV), accuracy and F1 score of DT value, resulting in the DT value of 12.75 days at 2 months as the optimal cut-off value of DT value. Patients were stratified into the 3 groups based on the DT value of 12.75 days at 2 months after IM discontinuation. The high-risk group was defined as the patients showing DT < 12.75 days but above 0, i.e. rapidly proliferating CML cells, implying a high risk for TFR failure with a shorter DT. The intermediate-risk group was defined as those patients with DT ≥ 12.75 days, i.e. more slowly proliferating CML cells implying intermediate risk for TFR failure. The low-risk group was defined as patients showing DT of zero or below, i.e. no increase in the size of the pool of cells expressing BCR-ABL, implying a low risk for TFR failure. The mRFS was analyzed for each of these risk groups at 6 monthly intervals after TKI discontinuation. Results: We compared the DT values of the patients that failed TFR with those from the patients who maintained their molecular response at last follow-up. The DT values at 2 months were much shorter in patients who failed TFR after IM cessation (median 8.32 days) compared to those who maintained molecular response (median 20.7 days; p<0.001 by Mann-Whitney U-test). The DT value of 12.75 days was defined as the optimal value for DT at 2 months with the NPV, PPV, accuracy and F1 score of 80.90%, 96.43%, 84.62% and 0.75, respectively, as the -log10(p-value), accuracy and F1 score reached a plateau at a DT of 12.75 days as presented in the Figure A. At a DT value of 12.75 days at 2 months after IM discontinuation, patients were stratified into 3 groups: high- (n=26), intermediate- (n=16) and low-risk groups (n=71; Figure B). With respect to mRFS rate, the high-risk group showed 7.7% mRFS rate at 12 months compared to 53.6% in the intermediate-risk group or 90.0% in the low-risk group (p<0.001; Figure C). Thus, this risk stratification system based on DT value at 2 months can stratify patients according to their risk of TFR failure after IM cessation. Conclusion: Monthly assessment of DT based on the monthly BCR-ABL qPCR is useful to identify the patients with an imminent risk of molecular recurrence after IM cessation for TFR. Figure Disclosures Bence-Bruckler: Merck: Membership on an entity's Board of Directors or advisory committees. Keating:Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Hoffman La Roche: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Consultancy; Merck: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Servier: Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Shire: Membership on an entity's Board of Directors or advisory committees; Taiho: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Busque:Novartis: Honoraria; BMS: Honoraria; Pfizer: Honoraria. Delage:Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Lipton:BMS: Consultancy, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria; Ariad: Consultancy, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Research Funding. Leber:Pfizer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS/Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Treadwell: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda/Palladin: Honoraria, Membership on an entity's Board of Directors or advisory committees; Alexion: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Lundbeck: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Otsuka Pharmaceutical: Honoraria, Membership on an entity's Board of Directors or advisory committees.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".