The clinical and economic burden of metastatic renal cell carcinoma in Canada in real-world setting
Notice bibliographique
Résumé
Aim: The management of metastatic renal cell carcinoma (mRCC) has changed significantly in the past decade with the scientific advancement in the field of pharmacotherapy, the search for optimal timing of surgery and different ablation methods. In parallel, the economic burden of mRCC has grown with increased incidence and costly treatments. This research program aimed: 1) to evaluate effectiveness and costs of targeted therapy (sunitinib and pazopanib) in first-line setting in clear cell mRCC patients; 2) to develop a Markov model with Monte-Carlo simulations in order to assess the cost-utility of sunitinib vs. pazopanib in patients who have mRCC in first-line setting from the Canadian healthcare system perspective and 3) to evaluate the impact of metastasectomy on clinical outcomes in mRCC patients using real-world data from Canadian academic hospitals.For the first objective of this research program, the Canadian Kidney Cancer information system (CKCis), a pan-Canadian database, was used to identify prospectively collected mRCC patients’ data between January 2011 and December 2017. Survival curves (Kaplan-Meier, conditional survival and direct adjusted survival curves) were used to estimate the unadjusted and adjusted overall survival (OS) by treatment. Unit treatment cost was taken from the Régie d’assurance Maladie du Québec (RAMQ) list of medications to estimate the cost by line of treatment and the total cost of targeted therapy for the management of mRCC patients. We included 475 patients receiving sunitinib or pazopanib in the first-line setting. Patients were mostly treated with sunitinib (81%), and 19% of patients were treated with pazopanib. The adjusted OS with sunitinib was 32 months compared to 21 months with pazopanib (p=0.01). The total average first-line cost of treatment with sunitinib and pazopanib was $94,232 (95%CI: $74,059 - $114,169) and $70,000 (95%CI: $32,942 -$107,993), respectively.For the second objective, a Markov model with Monte-Carlo microsimulations was developed to estimate the clinical and economic outcomes of patients treated in first-line with sunitinib vs. pazopanib over a 5-year period. Transition probabilities were calculated using the effectiveness results from the first objective. The costs of therapies, disease progression, and management of adverse events were included in the model in Canadian dollars. The difference in quality-adjusted life year (QALY) was 0.54 in favour of sunitinib with an incremental cost-utility ratio (ICUR) of $67,227/QALY for sunitinib vs. pazopanib. The difference in life years gained (LYG) was 1.21 (33.51 vs. 19.03 months), and the incremental cost-effectiveness ratio (ICER) was $30,002/LYG. For the third objective, patients were stratified depending if they were managed with a complete or incomplete metastasectomy or no metastasectomy. A total of 417 patients had a complete (273 patients) and incomplete (144 patients) metastasectomy, respectively. At 12 months, 98.7%, 87.1% and 77.7% of patients were alive in the complete metastasectomy, incomplete metastasectomy and no metastasectomy group, respectively (p<0.001). After matching, patients who underwent complete metastasectomy had a longer overall survival (HR: 0.41, 95%CI:0.30-0.56) compared to patients who did not undergo metastasectomy, but this benefit was not shown in patients undergoing incomplete metastasectomy (HR: 0.95, 95%CI: 0.71-1.28) vs. non-metastasectomy patients.In conclusion, using the CKCis database, we have assessed the real-life utilization of resources such as pharmacotherapy and surgical management as well as their respective outcome on mRCC patients in Canada. Also, our cost-utility analysis is the first economic analysis based on real-world evidence, and positions well the clinical values found in our results with regards to the economic value of targeted therapy
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 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 | 0,000 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,005 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 ».