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Enregistrement W4405047930 · doi:10.1182/blood-2024-204999

Prognostic Implication of Framingham Risk Score As a Comorbidity Measure on Treatment Outcomes Following First-Line Tyrosine Kinase Inhibitor in Newly Diagnosed CML Patients

2024· article· en· W4405047930 sur OpenAlexaffabout
May Chiu, María Agustina Perusini, Jaeyoon Kim, Danielle Pyne, Muzaffar Bhatti, Anthea Travas, Oyeronke Ayansola, Amirtha Ambalavanan, Jenny Ho, Dennis Dong Hwan Kim

Notice bibliographique

RevueBlood · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Myeloid Leukemia Treatments
Établissements canadiensLondon Health Sciences CentrePrincess Margaret Cancer CentreUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésMedicineComorbidityInternal medicineFramingham Risk ScoreTyrosine-kinase inhibitorOncologySecond line treatmentTyrosine kinaseDiseaseCancerOverall survival

Résumé

récupéré en direct d'OpenAlex

Introduction Comorbidities, including cardiovascular (CV) disease and risk factors, are crucial in selecting tyrosine kinase inhibitors (TKIs) for chronic myeloid leukemia (CML) patients (pts). About 40-60% of CML pts have at least 1 comorbid condition, and 30% present with CV risk factors at diagnosis. While the Framingham Risk Score (FRS) assesses the 10-year CV risk events in general population and is suggested to be accounted in the TKI selection in CML pts, prospective data on its impact on TKI choice and outcomes is limited. Patients and method The TCGA-GTA project, started in November 2020, is an ongoing, prospective, non-interventional registry study of newly diagnosed CML patients in the Greater Toronto Area, Canada. At initial evaluation, comorbidities and FRS were assessed. Pts with low FRS have ≤10% CV risk at 10 years, intermediate risk is 10-20%, and high risk is >20%. Event-free survival (EFS), failure-free survival (FFS), and TKI-switch-free survival were compared between pts with low FRS (FRSlow) and those with intermediate to high FRS (FRSint/hi). Events included TKI switch, treatment failure (TF), or death, with TF defined by European LeukemiaNet (ELN) 2013 guidelines. Results From Nov 2020 to Jun 30, 2024, the study enrolled 101 newly diagnosed CML pts. Of these, 74.3% were in the FRSlow group and 25.7% in the FRSint/hi group. The median age was 49 years, with the FRSint/hi cohort being older (67.5 vs. 41 years, p<0.001). Males constituted 59% of the the FRSlow group vs. 81% of the FRSint/high group (p=0.057). Chronic phase presentation was seen in 96% of the FRSlow group and 92.3% of the FRSint/hi group. High-risk cytogenetic abnormalities were present in 9.5% of the FRSlow group and 7.7% of the FRSint/hi group. The median SOKAL score was 0.8 in the FRSlow and 0.9 in the FRSint/hi group (p=0.198). The median EUTOS score was 1.25 in the FRSlow and 1.80 in FRSint/hi group (p=0.001). Comorbidities were present in 44% of patients, with hypertension (27.7%) and hyperlipidemia (25.7%) being most common, followed by diabetes mellitus (12.9%), chronic lung disease (11.9%), and vascular disease (9.9%), including coronary artery disease, stroke and peripheral vascular disease. Comorbidities were more prevalent in the FRSint/hi cohort (80.8% vs. 30.7%, p<0.001), with a median of 3 vs. 0 comorbidities per patient. Imatinib was more frequently prescribed in the FRSint/hi group (69.2% vs. 14.9%), while 2nd generation (2G) TKI were more common in the FRSlow group including nilotinib (40.5%) and dasatinib (36.5%). With a median follow-up of 21.3 months, the FRSint/hi group had more adverse events (AEs) (56% vs. 38.6%, p=0.161), including gastrointestinal AEs (19.2% vs. 5.4%, p=0.049) and fatigue (15.4% vs. 1.4%, p=0.016). Overall, 66% of pts achieved BCR::ABL1 <10% at 3 months, 60.5% achieved BCR::ABL1 <1% at 6 months, and 71.9% achieved BCR::ABL1 <0.1% at 12 months. These molecular response rates were higher in the FRSlow group but the differences were not statistically significant. Twenty-seven percent experienced TF, and 31% required a TKI switch, with higher rates in the FRSint/hi cohort. Resistance was the main reason for switching therapy (17.6% in the FRSlow vs. 23.1% in FRSint/hi), followed by intolerance (12.2% in FRSlow vs. 15.4% in the FRSint/hi). At 12 months, EFS and FFS were 69.6% and 75.4% in the FRSlow group vs. 57.2% and 66% in the FRSint/hi group. The probability of remaining on the 1L TKI was also higher in the FRSlow group (67% vs. 49.8%, p=0.142). Progression to advanced phase was similar between the groups (4-5% at 12 months). Multivariable analysis showed that the type of TKI was the only independent factor associated with EFS, FFS, and TKI-switch/discontinuation-free survival, with 2G-TKIs demonstrating superior outcomes compared to imatinib. Conclusion FRS is a key tool for evaluating CV comorbidities and guiding the choice of 1L TKI in CML practice, with FRSint/hi group more likely to receive imatinib. However, intolerance and resistance to imatinib remain significant issues in the FRSint/hi group, and FRS itself does not independently predict treatment outcomes. The type of 1L TKI drug is the most important independent factor influencing treatment outcomes, with 2G-TKIs showing superior results compared to imatinib. Therefore, there is an unmet need for alternative treatments with better efficacy and tolerability, such as asciminib, in the FRSint/hi group.

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)0,003
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 enseignants0,016
Score d'incertitude au seuil0,033

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,020
Tête enseignante GPT0,281
Écart entre enseignants0,261 · 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

Citations0
Publié2024
Routes d'admission2
Résumé présentoui

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