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Enregistrement W3094840453 · doi:10.1182/blood-2020-136162

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

2020· article· en· W3094840453 sur OpenAlexaffabout
Dennis Dong Hwan Kim, Igor Novitzky‐Basso, Tae-Hyung Kim, Eshetu G. Atenafu, Donna L. Forrest, Lynn Savoie, Isabelle Bence‐Bruckler, Mary‐Margaret Keating, Lambert Busque, Robert Delage, Anargyros Xenocostas, Elena Liew, Kristjan Paulson, Tracy Stockley, Pierre Laneuville, Jeffrey H. Lipton, Suzanne Kamel‐Reid, Brian Leber

Notice bibliographique

RevueBlood · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Myeloid Leukemia Treatments
Établissements canadiensMcMaster UniversityMcGill University Health CentreLondon Health Sciences CentreJuravinski Cancer CentreHôpital de l'Enfant-JésusUniversité de MontréalHôpital Maisonneuve-RosemontQueen Elizabeth II Health Sciences CentrePrincess Margaret Cancer CentreVancouver General HospitalUniversity of CalgaryBC Cancer AgencyAlberta Health ServicesCancerCare ManitobaUniversity of Alberta HospitalOttawa HospitalUniversity Health NetworkUniversity of TorontoAlberta Hospital EdmontonUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésDiscontinuationMedicineImatinibMyeloid leukemiaInternal medicineImatinib mesylateImmunologyOncology

Résumé

récupéré en direct d'OpenAlex

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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,005

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,024
Tête enseignante GPT0,288
Écart entre enseignants0,264 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2020
Routes d'admission2
Résumé présentoui

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