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Enregistrement W3211783573 · doi:10.1182/blood-2021-148636

Association between Bariatric Surgery and Outcomes in Patients with Chronic Myeloid Leukemia Treated with Oral Tyrosine Kinase Inhibitors

2021· article· en· W3211783573 sur OpenAlexaboutno aff
Fadi Haddad, Hagop M. Kantarjian, Elias Jabbour, Nicholas J. Short, Naveen Pemmaraju, Kayleigh Marx, Farhad Ravandi, Koji Sasaki, Ghayas C. Issa

Notice bibliographique

RevueBlood · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Myeloid Leukemia Treatments
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineMyeloid leukemiaTyrosine kinaseInternal medicineSurgeryTyrosine-kinase inhibitorGastroenterologyCancer

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Patients with a history of bariatric surgery are often excluded from clinical trials evaluating oral therapies. This is due to concerns that these surgeries alter bioavailability and drug metabolism. Oral tyrosine kinase inhibitors (TKIs) are the mainstay treatment for chronic myeloid leukemia (CML). However, the impact of bariatric surgeries on CML treatment outcomes is largely unknown. Methods: In a retrospective analysis, we screened patients with CML treated at our institution and identified those who had any type of bariatric surgery including gastric bypass, gastric sleeve surgery or gastric banding. Subsequently, we compared their responses and outcomes to a control cohort of patients without history of bariatric surgery, using propensity score matching for Sokal Risk and body mass index (BMI) at a 2:1 ratio. In addition to cytogenetic and molecular responses, we assessed times to achieving responses and BCR-ABL1 halving times to investigate differences in response dynamics (Branford, Blood 2014). Event-free survival (EFS) was measured from treatment start to loss of response, progression or death, whereas failure-free survival (FFS) additionally accounted for therapy discontinuation for any other reason such as intolerance. Overall survival (OS) was measured from treatment start date to death, or censored at last follow-up. Univariate and multivariate analyses (MVA) were used to assess the association between characteristics and overall survival. Results: We identified 28 patients with CML and bariatric surgery, of whom 22 (79%) had their surgery before CML. Their baseline characteristics are summarized below (Figure 1). Despite propensity score matching, patients with bariatric surgery compared to control had a higher BMI at time of CML diagnosis (median: 38 vs 26 Kg/m 2, P<0.0001) and lower Sokal Risk (76% vs 50%, P=0.03). More patients in the bariatric surgery group were treated with imatinib (39% vs 14 %, P=0.02). Patients with history of bariatric surgery received a higher number of TKIs throughout their CML treatment because of resistance or intolerance compared to control (median of 2, range 1-6 vs median of 1, range 1-3, P<0.0001). They tended to have slower response dynamics evidenced by a lower proportion of patients with BCR-ABL1 <10% at 3 months (71% vs 89%, P=0.09), and a longer halving time (26 vs 19 days, P=0.06). Despite having a similar complete cytogenetic response rate (CCyR) (93% vs 96%, P=0.2), their median time to achieve CCyR was significantly longer (6 months vs 3 months; P<0.0001). In addition, they had longer median time to achieve a major molecular remission (MMR) (12 months vs 6 months, P=0.013) and a lower rate of MR4.5 (61% vs 86%, P=0.02) (Figure 1). Patients with bariatric surgery and CML had inferior EFS compared to control (5-year EFS rate: 61% vs 87% respectively, P=0.0003) and inferior FFS (5-year FFS rate: 15% vs 77% respectively, P<0.0001). Bariatric surgery was associated with worse OS with a 5-year rate of 81% compared to 95% in the control group (P=0.01) (Figure 1). There was no difference in OS comparing patients who had bariatric surgery and received imatinib as first-line treatment vs those that received other TKIs (P=0.5). To account for the impact of co-variates such as BMI, type of TKI and Sokal Risk on survival, we conducted univariate and multivariate analyses. We found that bariatric surgery was an independent predictor of the risk of death with a hazard ratio (HR) of 13 (95% confidence interval [CI], 2.3-71.4, P=0.004). The only other independent predictor of OS in the MVA was age where older patients had an increased risk of death with a HR of 1.1 (95% CI, 1.0-1.2, P<0.0001). However, BMI, Sokal Risk and type of TKI used as frontline therapy were not independent predictors of OS in the MVA. Conclusion: Bariatric surgery is associated with slower responses to TKIs in patients with CML, and a lower chance of deep remission. It is also associated with higher rates of treatment failure and worse overall survival. There is an unmet need to design treatment strategies for these patients. Although not readily available in the clinical setting, studies measuring drug level in these patients are needed to assess which TKI has a better bioavailability, which in turn could translate to improved outcomes. Figure 1 Figure 1. Disclosures Kantarjian: Aptitude Health: Honoraria; BMS: Research Funding; Astellas Health: Honoraria; Jazz: Research Funding; Pfizer: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Immunogen: Research Funding; KAHR Medical Ltd: Honoraria; Ascentage: Research Funding; AbbVie: Honoraria, Research Funding; NOVA Research: Honoraria; Daiichi-Sankyo: Research Funding; Amgen: Honoraria, Research Funding; Astra Zeneca: Honoraria; Ipsen Pharmaceuticals: Honoraria; Precision Biosciences: Honoraria; Taiho Pharmaceutical Canada: Honoraria. Jabbour: Amgen, AbbVie, Spectrum, BMS, Takeda, Pfizer, Adaptive, Genentech: Research Funding. Short: Takeda Oncology: Consultancy, Research Funding; NGMBio: Consultancy; AstraZeneca: Consultancy; Astellas: Research Funding; Novartis: Honoraria; Jazz Pharmaceuticals: Consultancy; Amgen: Consultancy, Honoraria. Pemmaraju: Roche Diagnostics: Consultancy; Dan's House of Hope: Membership on an entity's Board of Directors or advisory committees; Sager Strong Foundation: Other; ASCO Leukemia Advisory Panel: Membership on an entity's Board of Directors or advisory committees; Novartis Pharmaceuticals: Consultancy, Other: Research Support, Research Funding; Plexxicon: Other, Research Funding; HemOnc Times/Oncology Times: Membership on an entity's Board of Directors or advisory committees; Samus: Other, Research Funding; Celgene Corporation: Consultancy; Stemline Therapeutics, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding; Clearview Healthcare Partners: Consultancy; Protagonist Therapeutics, Inc.: Consultancy; Incyte: Consultancy; Abbvie Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding; ASH Communications Committee: Membership on an entity's Board of Directors or advisory committees; Affymetrix: Consultancy, Research Funding; Cellectis S.A. ADR: Other, Research Funding; CareDx, Inc.: Consultancy; Daiichi Sankyo, Inc.: Other, Research Funding; Blueprint Medicines: Consultancy; LFB Biotechnologies: Consultancy; Aptitude Health: Consultancy; Springer Science + Business Media: Other; DAVA Oncology: Consultancy; MustangBio: Consultancy, Other; Bristol-Myers Squibb Co.: Consultancy; ImmunoGen, Inc: Consultancy; Pacylex Pharmaceuticals: Consultancy. Ravandi: Amgen: Honoraria, Research Funding; Xencor: Honoraria, Research Funding; AstraZeneca: Honoraria; Novartis: Honoraria; AbbVie: Honoraria, Research Funding; Astex: Honoraria, Research Funding; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Taiho: Honoraria, Research Funding; Syros Pharmaceuticals: Consultancy, Honoraria, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Prelude: Research Funding; Agios: Honoraria, Research Funding; Jazz: Honoraria, Research Funding. Sasaki: Pfizer: Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Research Funding. Issa: Novartis: Consultancy, Research Funding; Syndax Pharmaceuticals: Research Funding; Kura Oncology: Consultancy, Research Funding.

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 enseignants0,002
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
Bibliométrie0,0000,001
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)0,0020,000

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 Opus0,008
Tête enseignante GPT0,216
Écart entre enseignants0,208 · 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
Publié2021
Routes d'admission1
Résumé présentoui

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