Risk of Progression in Chronic Phase - Chronic Myeloid Leukemia (CML) Patients Eligible for Tyrosine Kinase Inhibitor Discontinuation (TFR-PRO study): Preliminary Results
Notice bibliographique
Résumé
Abstract Background. Over 50% of CP-CML patients will achieve a deep molecular response (DMR) at some point during treatment with Tyrosine Kinase Inhibitors (TKI), where DMR is defined as BCR-ABL1 transcript levels lower than 1/10000 (or MR4). Treatment discontinuation (TD) in CP-CML patients with stable DMR is successful in approximately half of cases, with a relapse free survival (RFS) of 48-61% at 3 years. TD is considered safe, since MMR is achieved in almost all cases when TKI re-initiation is required. As such, treatment-free remission (TFR) is now usually attempted outside of clinical trials and is part of many CML guidelines. The progression to accelerated phase/blast crisis (AP/BC) after TD was considered virtually impossible for a long time. However, recent reports document at least six cases of disease progression after TD, some of which were fatal. These observations raise concerns about the safety of TD, since now the practice can no longer be considered completely immune from the risk of disease progression, an occurrence that drastically changes the patient situation and perspective when it develops. To best counsel patients and more safely apply TD, a precise quantification of the risk of progression in this setting is needed. Study Design and Methods The TFR-PRO project monitor CML patients in long term treatment and with stable DMR, followed at 28 centers in 4 different countries (Canada, Italy, Germany, Spain). Each center is expected to enroll approximately 100 patients. The following variables were measured: time adjusted rates (TAR) of molecular relapse (loss of MR3) and of progression to AP/BC; progression free and overall survival. Primary Objective To quantify the risk of progression to AP/BP, expressed as TAR, after TKI discontinuation in CML patients who undergo a first or subsequent TKI discontinuation attempt. This value will be compared to that obtained in a similar population of patients with the same characteristics who do not discontinue TKI treatment. A flexible statistical approach will allow to attribute patients to the two groups according to their decision about TKI discontinuation and to the loss of MR3. Patients eligibility includes a history of at least 3 years of TKI treatment and at least 18 months of continuous DMR. Results The study opened on July 24 th,2020. Twelve centers are presently active with 303 eligible patients registered, for a total of 1614 person years available for analysis. Median follow up is 4.99 years (range 0.39-15.00 years), median age at diagnosis is 50.4 years and 47.9% patients are female. Sokal score (available in 147 patients) is low in 44.90%, intermediate in 32.65% and high in 22.45%. A total of 116 patients (38.28%) attempted TD at some point; 10 patients (3.30%) attempted TD twice. Loss of MR3 occurreded in 44/116 (37.93%) patients after TD for a TAR of 15.69/100 person years, (95% confidence interval (CI) [11.68-21.09]), but also in patients who did not attempt TD (21/187, or 11.23%), TAR: 1.83/100 person years, 95%CI [1.19-2.81], p<0.0001. No patient progressed to AP/BC and therefore the TAR of progression is 0% with an upper value of 95%CI of 1.07/100 person years for patients who attempted TD, and with an upper value of 95%CI of 0.26/100 person years for patients who did not attempt TD. Conclusions These preliminary results obtained in a real world scenario indicate that approximately 40% of eligible patients attempt TD. The loss of MR3 after TD seem to happen less frequently (38%) than previously reported. Patients who discontinue treatment have a significantly higher risk of losingMR3 than those who continue treatment, and the risk of progression to AP/BC is lower than 1.07/100 person years. More patients need to be enrolled in this study in order to better estimate this latter number. Disclosures Assouline: Gilead: Speakers Bureau; Jewish General Hospital, Montreal, Quebec: Current Employment; Johnson&Johnson: Current equity holder in publicly-traded company; Novartis: Honoraria, Research Funding; Eli Lilly: Research Funding; Roche/Genentech: Research Funding; Takeda: Research Funding; BeiGene: Consultancy, Honoraria, Research Funding; Amgen: Current equity holder in publicly-traded company, Research Funding; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria. Abruzzese: Pfizer: Consultancy, Honoraria; Bristol Myers Squibb: Consultancy, Honoraria; Incyte: Consultancy, Honoraria; Novartis: Consultancy, Honoraria. Elena: CELGENE: Other: funding for meeting participation; PFIZER: Membership on an entity's Board of Directors or advisory committees; NOVARTIS: Membership on an entity's Board of Directors or advisory committees; GILEAD: Membership on an entity's Board of Directors or advisory committees. Saussele: Roche: Honoraria; Pfizer: Honoraria; Incyte: Honoraria, Research Funding; BMS: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Gambacorti-Passerini: Pfizer: Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».