Adjusting For Drug Wastage In Economic Evaluations Of New Therapies For Hematologic Malignancies: A Systematic Review Of The Literature and Implications
Notice bibliographique
Résumé
Abstract The cost of cancer care is rising to levels that appear unsustainable, in large part driven by a rapid increase in expenditures for novel therapies. In 2005, the direct costs of cancer care in the United States were $74 billion, with a prediction that these figures will double this decade as the population ages and we enter an age of biologically-tailored drug development. Historically, the evaluation of the cost-effectiveness of new drug therapies presumes that every milligram of drug is effectively utilized. With manufacturers dictating the availability of vial sizes for parenteral drugs, however, this may not be the case. A recent single-institution study in Canada estimated that an annual loss of $150 000 ($CDN) could be attributed to drug wastage of a parenteral therapy for myelodysplasia (Walker et al., Can J Hosp Pharm 2012). Whether current economic evaluations routinely model the potential for drug wastage, or the strategies to mitigate wastage, has not previously been determined. We sought to identify the frequency of drug wastage modeling in economic evaluations of modern parenteral therapies for hematologic malignancies. All US Food and Drug Administration (FDA) approved parenteral therapies from 2006-2013 (n=14) were identified for review. A systematic review of published English-language economic evaluations for these therapies was conducted and data on the conduct of the cost-analyses were extracted in duplicate. The primary outcome was the proportion of studies that explicitly modeled drug wastage in the base-case analysis, with results presented descriptively. Where possible, we calculated the impact of wastage on incremental cost-effectiveness ratios (ICERs) and drug acquisition costs. Thirty-three publications were retrieved; five of these studies were excluded (3 were non-English language and 2 were review articles). Of the remaining 27 reports, 3 were publicly-funded health technology assessments (HTAs) to inform funding decisions by the UK National Institute for Health and Care Excellence (NICE) and the remainder (n=24) were peer-reviewed publications. Sixteen economic evaluations were of rituximab-based regimens and 6 were bortezomib-based. Drug wastage was considered in the primary or base-case analysis in one third of the publications (9 of 27; 33%); wastage was considered in 2 of the 3 HTAs (67%) and 7 of the 24 peer-reviewed reports (29%). Of the 9 models that considered wastage in the base-case analysis, 2 completed sensitivity analyses in which no drug wastage occurred (i.e. vial sharing between patients). In both studies, consideration of wastage changed the calculated ICER. In one study, the ICER increased by 32% when wastage was incorporated into drug acquisition costs. In the second study, azacitidine (AZA) was compared to decitabine (DEC) for myelodysplasia, with both drugs provided as single-use vials and subject to substantial wastage. When no drug wastage was modeled, AZA was associated with higher costs than DEC (+$2 655 USD) and yielded an ICER of $15 528/QALY. When wastage for both drugs was considered, AZA was associated with lower costs (-$15 890) and AZA dominated DEC. Of the 18 publications that did not model wastage in the primary analysis, no study went on to model wastage in sensitivity analyses. In 4 of these 18 studies, the potential effect of wastage on drug acquisition costs could be calculated from data provided in the publication. The calculated drug acquisition costs if wastage occurred would potentially be +5-16% higher (mean +9%) than the costs modeled in the base-case analyses of these 4 studies. The potential costs associated with drug wastage are considered in only one third of modern cost-effectiveness models. The impact of wastage on calculated ICERs and drug acquisition costs is potentially substantial. The modeling of wastage in base-case and sensitivity analyses is recommended for future economic evaluations of new intravenous therapies for hematologic malignancies. Disclosures: No relevant conflicts of interest to declare.
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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 | 0,067 | 0,252 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,010 | 0,022 |
| Bibliométrie | 0,015 | 0,016 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,005 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,003 |
| 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 ».