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Enregistrement W2547879229 · doi:10.1182/blood.v126.23.2090.2090

Nilotinib Vs Dasatinib As Second-Line Therapy in Patients with Philadelphia-Positive Chronic Myeloid Leukemia in Chronic Phase (Ph+ CML-CP) Who Are Resistant or Intolerant to Imatinib: A Cost-Effectiveness Analysis (CEA) Based on Real-World Data

2015· article· en· W2547879229 sur OpenAlexaboutno aff
Nanxin Li, Chelsey Yang, Liangyi Fan, Todor Totev, Annie Guérin, Lei Chen

Notice bibliographique

RevueBlood · 2015
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Myeloid Leukemia Treatments
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésNilotinibDasatinibMedicineDiscontinuationInternal medicineImatinibImatinib mesylateOncologyMyeloid leukemia

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Nilotinib and dasatinib are common second-line therapy for patients with Ph+ CML-CP who are resistant or intolerant to imatinib. Since their approval, several CEAs comparing second-line nilotinib vs dasatinib have been published (Rogers et al., Health Technol Assess 2012; 16(22); Loveman et al., Health Technol Assess 2012; 16(23)). However, these models were developed in the absence of any comparative effectiveness evidence between the two drugs. Another major limitation of these models as recognized by a leading health technology assessment (HTA) agency was the use of surrogate markers to impute survival endpoints (e.g., progression-free survival [PFS] and overall survival [OS]). As direct comparative evidence of the two drugs based on real-world data become available, this study was conducted to address these limitations and re-evaluate the cost-effectiveness of second-line nilotinib vs dasatinib for Ph+ CML-CP using real-world comparative PFS and OS data from a third-party payer perspective in the U.S. Methods: A lifetime partitioned survival model was developed to compare healthcare costs, life years (LYs) and quality-adjusted life years (QALYs) associated with second-line therapy with nilotinib vs dasatinib in patients with Ph+ CML-CP who were resistant or intolerant to first-line imatinib. The model included four health states: CP on second-line treatment (CP on treatment), CP post-discontinuation of second-line treatment (CP post-discontinuation), accelerated phase or blast crisis (progressive disease), and death. Patients can only transition into a subsequent health state but not in the other direction; patients in the first three health states can all transition to death. Time on treatment (TOT), PFS, and OS for second-line nilotinib and dasatinib were estimated using data from a real-world comparative effectiveness study (Griffin et al., Curr Med Res Opin 2013; 29(6):623-31). Parametric survival models were used to extrapolate outcomes beyond the study period. Drug treatment costs, medical costs, and adverse event (AE) costs were obtained from literature and publicly available databases. Utilities for health states were derived from literature. Costs, LYs, and QALYs were discounted at 3% per annum. Incremental cost-effectiveness ratios (ICERs), including incremental cost per LY gained and incremental cost per QALY gained, were estimated comparing nilotinib vs dasatinib. Deterministic sensitivity analyses (DSAs) were performed by varying starting age, sex-ratio, adherence level of second-line therapies, drug treatment costs for post-second-line states, medical costs for all health states, AE costs, and utility for CP post-discontinuation. Results: Over life time, initiating second-line treatment with nilotinib was associated with 11.69 LYs, 9.13 QALYs, and total costs of $1,406,265; initiating second-line with dasatinib was associated with 9.51 LYs, 7.30 QALYs, and total costs of $1,418,235. Second-line nilotinib was associated with better health outcomes (difference in LY = 2.18 years, difference in QALY = 1.84 years) and lower costs (difference in total cost = $11,970) relative to dasatinib. DSA results similarly showed better outcomes and lower costs for nilotinib vs dasatinib based on variations of sex-ratio, progressive disease treatment costs, medical costs for all health states, AE costs, and utility for CP post-discontinuation; DSA results also showed better outcomes but higher costs for nilotinib vs dasatinib based on variations of starting age, adherence to second-line therapies, and CP post-discontinuation treatment cost with ICERs of $10,738/QALY, $2,648/QALY, and $2,318/QALY, respectively.Table 1.Base Case ResultsNilotinibDasatinibNilotinib vs DasatinibCosts (2015 USD)Treatment costs$1,235,535$1,253,081-$17,546Medical costs$162,326$156,762$5,564AE costs$8,404$8,392$11Total costs$1,406,265$1,418,235-$11,970EffectivenessTotal LYs11.699.512.18Total QALYs9.137.301.84ICERIncremental cost per LY gainedBetter LY with lower costsIncremental cost per QALY gainedBetter QALY with lower costs Conclusions: The CEA based on real-world comparative evidence suggests that second-line nilotinib is associated with better life expectancy, quality of life, and lower cost when compared with dasatinib, among patients with Ph+ CML-CP who are resistant or intolerant to imatinib. Disclosures Li: Novartis Pharmaceuticals Corporation: Consultancy, Other: Nanxin Li is an employee of Analysis Group Inc, which has received consultancy fees from Novartis Pharmaceuticals Corporation; AbbVie Inc., Astellas Pharma US Inc., Bayer Healthcare Pharmaceuticals LLC, Bristol-Myers Squibb Company, Celgene Corporation, Forest Laboratories Inc., Sanofi: Consultancy, Other: Nanxin Li is an employee of Analysis Group Inc, which has received consultancy fees from the listed organizations. Yang:Astellas Pharma US, Inc.: Consultancy, Other: Chelsey Yang is an employee of Analysis Group Inc, which has received consultancy fees from Astellas Pharma US, Inc.; Bristol-Myers Squibb Company: Consultancy, Other: Chelsey Yang is an employee of Analysis Group Inc, which has received consultancy fees from Bristol-Myers Squibb Company; Forest Laboratories, Inc.: Consultancy, Other: Chelsey Yang is an employee of Analysis Group Inc, which has received consultancy fees from Forest Laboratories, Inc.; Sanofi: Consultancy, Other: Chelsey Yang is an employee of Analysis Group Inc, which has received consultancy fees from Sanofi; AbbVie Inc.: Consultancy, Other: Chelsey Yang is an employee of Analysis Group Inc, which has received consultancy fees from Abbvie Inc.; Shire Pharmaceuticals Inc.: Consultancy, Other: Chelsey Yang is an employee of Analysis Group Inc, which has received consultancy fees from Shire Pharmaceuticals Inc.; GE Healthcare: Consultancy, Other: Chelsey Yang is an employee of Analysis Group Inc, which has received consultancy fees from GE Healthcare; Millennium Pharmaceuticals, Inc.: Other: Chelsey Yang is an employee of Analysis Group Inc, which has received consultancy fees from Millennium Pharmaceuticals, Inc.; Novartis Pharmaceuticals Corporation: Consultancy, Other: Chelsey Yang is an employee of Analysis Group Inc, which has received consultancy fees from Novartis Pharmaceuticals Corporation. Fan:Novartis Pharmaceuticals Corporation: Consultancy, Other: Liangyi Fan is an employee of Analysis Group Inc, which has received consultancy fees from Novartis Pharmaceuticals Corporation; AbbVie Inc, Astellas Pharma US Inc, Bristol-Myers Squibb Co, Ethicon Inc, Forest Labs Inc, GE Healthcare, Genentech Inc, MedImmune LLC, Millennium Pharmaceuticals Inc, Sanofi, Shire Pharmaceuticals Inc, Takeda Pharmaceuticals Inc, Teva Specialty Brands: Consultancy, Other: Liangyi Fan is an employee of Analysis Group Inc, which has received consultancy fees from the listed organizations. Totev:Novartis Pharmaceuticals Corporation: Consultancy, Other: Todor Totev is an employee of Analysis Group Inc, which has received consultancy fees from Novartis Pharmaceuticals Corporation; AbbVie Inc., Astellas Pharma US Inc., Bayer Healthcare Pharmaceuticals LLC, Biogen Idec Inc., Boehringer Ingelheim, Bristol-Myers Squibb Company, Cleveland HeartLab Inc., Eli Lilly & Company, Forest Laboratories Inc., Gilead Sciences Inc., GlaxoSmithKline: Consultancy, Other: Todor Totev is an employee of Analysis Group Inc, which has received consultancy fees from the listed organizations; Janssen Scientific Affairs LLC, Sanofi, Shire Pharmaceuticals Inc, UCB Inc, Vertex Pharmaceuticals Inc: Consultancy, Other: Todor Totev is an employee of Analysis Group Inc, which has received consultancy fees from the listed organizations. Guerin:Pfizer Canada, Inc.,RX&D, Sanofi, Savient Pharmaceuticals, Inc., Shire Pharmaceuticals Inc., Sunovion Pharmaceuticals Inc.,Takeda Global Research & Development Center, Inc., Takeda Pharmaceuticals U.S.A., Inc.: Consultancy, Other: Annie Guerin is an employee of Analysis Group Inc, which has received consultancy fees from the listed organizations; GlaxoSmithKline, Janssen Scientific Affairs, Janssen-Ortho, Inc., Merck & Co., Inc., Merck Frosst Canada, Novartis Pharmaceuticals Corporation, Novo Nordisk Inc., Ogilvy Renault, Ortho-Clinical Diagnostics, Inc., Otsuka America Pharmaceutical, Inc.,: Consultancy, Other: Annie Guerin is an employee of Analysis Group Inc, which has received consultancy fees from the listed organizations; AbbVie Inc., Alcon Laboratories, Bayer Healthcare Pharmaceuticals, LLC, Celgene Corporation, Cempra Inc., Centocor Ortho Biotech, Cooley LLP, Cyberonics, Inc., DLA Piper, Eli Lilly & Company, Forest Laboratories, Inc., Genentech, Inc.,: Consultancy, Other: Annie Guerin is an employee of Analysis Group Inc, which has received consultancy fees from the listed organizations. Chen:Novartis Pharmaceuticals Corporation: Employment, Equity Ownership, Other: Lei Chen is an employee of and owns stocks/options of Novartis Pharmaceuticals Corporation, the sponsor of this study.

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)0,007
score de la tête « metaresearch » (Gemma)0,009
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: Empirique
Score de désaccord entre enseignants0,008
Score d'incertitude au seuil0,038

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0070,009
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,006
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0020,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,002
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 Opus0,056
Tête enseignante GPT0,348
Écart entre enseignants0,292 · 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

Citations2
Publié2015
Routes d'admission1
Résumé présentoui

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