A cost-utility analysis of combined durvalumab and tremelimumab in patients with refractory metastatic colorectal cancer (mCRC) and high plasma tumour mutation burden (pTMB): A Canadian Cancer Trials Group (CCTG) study.
Notice bibliographique
Résumé
e15581 Background: The randomized phase II CCTG CO.26 clinical trial investigated the use of combined durvalumab and tremelimumab vs. best supportive care (BSC) for patients with mCRC and suggested an increase in overall survival (OS). The largest benefit was seen in patients who were microsatellite stable (MSS) with a pTMB ≥ 28 variants per megabase. Considering significantly higher adverse event rates and costs associated with durvalumab and tremelimumab, it is important to evaluate its cost-effectiveness. Accordingly, we performed a cost-utility analysis of durvalumab and tremelimumab compared to BSC in the intention-to-treat (ITT) and biomarker-enriched populations using CO.26 trial data. Methods: We developed a 4-state microsimulation model to evaluate the expected health outcomes in life-years (LYs), quality-adjusted life-years (QALYs) and costs of the treatment group compared to BSC over a lifetime horizon (5 years). The incremental cost-utility ratio (ICUR) was used to compare treatment strategies. Direct trial data from CO.26 were used to inform model inputs, including OS curves, progression-free survival (PFS) curves, and adverse event rates. As health state utilities were not collected in CO.26, values from the CORRECT trial, a multi-centre randomized placebo-controlled phase III study for regorafenib in mCRC, were used. Costs of therapy, hospitalization due to adverse events, end-of-life care, and physician costs were derived from the literature and publicly available sources (in 2020 Canadian dollars). Since the monthly price of tremelimumab was unavailable, it was approximated with the price of another CTLA-4 inhibitor, ipilimumab. The base-case analysis evaluated these treatment strategies in the ITT population. Scenario analyses evaluated the cost-effectiveness in biomarker-enriched populations. Costs and effects were discounted at 1.5% as per Canadian guidelines. Results: In the base-case, expected LYs for combined durvalumab and tremelimumab and BSC were 0.75 and 0.51 (incremental (Δ) 0.24) respectively. Expected QALYs were 0.47 and 0.33 (Δ 0.14). Expected lifetime costs were $60 500 and $15 500 (Δ $45 000) for an ICUR of $320 000/QALY. In the biomarker-enriched subgroup, the expected LYs were 0.67 and 0.33 (Δ 0.34), expected QALYs were 0.43 and 0.22 (Δ 0.21), and expected lifetime costs were $62 000 and $15 200 (Δ $47 000). This represents an increase in the incremental QALYs by 50% and costs by 5% for an ICUR 30% lower than the base case at $220 000/QALY. Conclusions: Combined durvalumab and tremelimumab is not considered cost-effective in refractory mCRC under conventional willingness-to-pay thresholds. Cost-effectiveness is improved with biomarker enrichment for high pTMB, driven by the greater derived health outcomes in this subgroup.
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 | 0,007 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,004 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».