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Enregistrement W2560782884 · doi:10.1182/blood.v124.21.4551.4551

Comparative Efficacy Among 3rd Line Post-Imatinib Chronic Phase-Chronic Myeloid Leukemia (CP-CML) Patients after Failure of Dasatinib or Nilotinib Tyrosine Kinase Inhibitors

2014· article· en· W2560782884 sur OpenAlexaff
Jeffrey H. Lipton, Dhvani D. Shah, Vanita Tongbram, Manpreet Sidhu, Hui Huang, Lisa J. McGarry, Stephanie Lustgarten, Neil Hawkins

Notice bibliographique

RevueBlood · 2014
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Myeloid Leukemia Treatments
Établissements canadiensPrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésNilotinibDasatinibMedicineImatinibPonatinibInternal medicineBosutinibImatinib mesylateTyrosine-kinase inhibitorTyrosine kinaseOncologyMyeloid leukemiaCancer

Résumé

récupéré en direct d'OpenAlex

Abstract INTRODUCTION Patients with chronic myeloid leukemia (CP-CML) failing 1st line imatinib are most commonly treated with the second-generation (2G) tyrosine kinase inhibitors (TKIs) dasatinib and nilotinib. However, for patients who experience resistance or intolerance (R/I) to 2G-TKIs in 2nd line, there currently is no consensus on the optimal therapy sequence for 3rd line treatment. The comparative efficacy of using ponatinib in the 3rd line after 2G TKI failure was examined in a previous study (Lipton et al., ASH 2013). This study assesses the comparative efficacy of ponatinib versus sequential treatment of alternate 2G TKIs in 3rdline setting in two separate patient populations, post-imatinib and dasatinib patients and post-imatinib and nilotinib patients. METHODS A systematic review was conducted in MEDLINE, EMBASE and the Cochrane Libraries (2002-2014), as well as 3 conferences (ASH (2008-2014), ASCO (2008-2014), and EHA (2008-2013)). Studies evaluating any TKI were included if they enrolled 10 or more post-imatinib adult patients with CP-CML who were also R/I to dasatinib or nilotinib. All study designs were considered and no restriction was applied with respect to therapy dose, due to incomplete reporting of doses in the available studies. Analyses was run on two groups of patients, those failing imatinib and dasatinib (Group Ima/Das) and those failing imatinib and nilotinib (Group Ima/Nil). Bayesian methods were used to synthesize major cytogenetic response (MCyR) and complete cytogenetic response (CCyR) from individual studies and estimate the overall response probability with 95% credible interval (CrI) for each treatment. Bayesian analysis also was used to estimate the likelihood that each treatment offers the highest probability of CCyR/MCyR based on available evidence. RESULTS Six studies evaluating bosutinib, nilotinib and ponatinib for Group Ima/Das (n= 419) and five studies evaluating bosutinib, dasatinib and ponatinib for Group Ima/Nil (n=83) were included in the analysis. All studies reported CCyR in both groups. Five studies evaluating bosutinib, nilotinib and ponatinib reported MCyR in Group Ima/Das and three studies evaluating bosutinib and ponatinib reported MCyR in Group Ima/Nil. Synthesized treatment-specific probabilities and 95% CrI for CCyR are presented in Figure 1. Synthesized treatment-specific probabilities of CCyR for Group Ima/Das were 27% for nilotinib, 20% for bosutinib and 54% (95% CrI 43%% to 66%) for ponatinib. Treatment-specific probabilities of MCyR for Group Ima/Das were 41% for nilotinib, 28% for bosutinib and 66% (95% CrI 55%% to 77%) for ponatinib. The probability of ponatinib providing superior response to all other included treatments for group Ima/Das was estimated to be >99% for both CCyR and MCyR. Synthesized treatment-specific probabilities of CCyR for Group Ima/Nil were 25% for dasatinib, 26% for bosutinib and 67% (95% CrI 51%% to 81%) for ponatinib. Treatment-specific probabilities of MCyR for Group Ima/Nil were 33% for bosutinib and 75% (95% CrI 60%% to 87%) for ponatinib. The probability of ponatinib providing superior response to all other included treatments for group Ima/Nil was estimated to be >99% for both CCyR and MCyR. CONCLUSIONS The post imatinib and dasatinib group included more studies with larger sample sizes compared with the post imatinib and nilotinib group. Overall, response rates appear higher for TKIs in the post imatinib and nilotinib group compared with the post imatinib and dasatinib group. For both groups, patients on ponatinib had higher CCyR and MCyR rates compared with the sequential 2G TKIs included in this analysis. Based on available data, ponatinib appears to provide a higher probability of treatment response for patients failing imatinib and dasatinib/ nilotinib compared with sequential 2G TKI therapy commonly used in this indication. Figure 1 Figure 1. Disclosures Lipton: Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Bristol Myers: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Ariad: Equity Ownership, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Shah:Ariad Pharmaceuticals: Research Funding. Tongbram:Ariad Pharmaceuticals: Research Funding. Sidhu:Ariad Pharmaceuticals Inc.: Research Funding. Huang:ARIAD Pharmaceuticals, Inc.: Employment, Equity Ownership. McGarry:ARIAD Pharmaceutical, Inc.: Employment, Equity Ownership. Lustgarten:ARIAD Pharmaceuticals Inc: Employment, Equity Ownership. Hawkins:Ariad Pharmaceuticals Inc.: 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)0,011
score de la tête « metaresearch » (Gemma)0,025
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: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,011
Score d'incertitude au seuil0,058

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0110,025
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0080,012
Bibliométrie0,0060,005
Études des sciences et des technologies0,0000,001
Communication savante0,0020,002
Science ouverte0,0010,001
Intégrité de la recherche0,0020,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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 Opus0,015
Tête enseignante GPT0,278
Écart entre enseignants0,263 · 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

Citations7
Publié2014
Routes d'admission1
Résumé présentoui

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