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Enregistrement W2915579267 · doi:10.1093/annonc/mdz057

Value assessment frameworks in oncology: championing concordance through shared standards

2019· editorial· en· W2915579267 sur OpenAlexaboutno aff
Monica M. Bertagnolli, Josep Tabernero

Notice bibliographique

RevueAnnals of Oncology · 2019
Typeeditorial
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueEconomic and Financial Impacts of Cancer
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineConcordanceCancerScopusFamily medicineMEDLINEInternal medicine

Résumé

récupéré en direct d'OpenAlex

As rapidly evolving tools under the constant rigorous review and development by both ASCO and ESMO’s expert task forces, the ASCO Value Framework Net Health Benefit Score (ASCO-NHB) and the ESMO Magnitude of Clinical Benefit Scale (ESMO-MCBS) were both launched in 2015 to assess the relative benefit of cancer therapies and were recently compared [1.Cherny N.I. de Vries E.G.E. Dafni U. et al.Comparative assessment of clinical benefit using the ESMO-Magnitude of Clinical Benefit Scale Version 1.1 (ESMO-MCBS v1.1) and the ASCO Value Framework Net Health Benefit Score (ASCO-NHB v2).J Clin Oncol. 2019; 37: 336-349Crossref PubMed Scopus (72) Google Scholar]. Both societies are working to better understand and measure the value of new cancer therapies and are facilitating a broader discussion with stakeholders that, hopefully, will lead to a coherent approach to confronting the global burden of cancer. The time to do so is now. According to a recent report [2.Fitzmaurice C. Akinyemiju T.F. et al.Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life-years for 29 cancer groups, 1990 to 2016. A systematic analysis for the global burden of disease study.JAMA Oncol. 2018; 4: 1553-1568Crossref PubMed Scopus (1040) Google Scholar], there were 17.2 million cancer cases worldwide and 8.9 million deaths in 2016, with cancer cases up 28% from 2006 to 2016. With global oncology costs continuing to soar—the price tag is predicted to reach $150 billion by 2020 [3.IMS Health. MIDAS, December 2015; Market Prognosis, March 2016; IMS Institute for Healthcare Informatics, May 2016.Google Scholar]—access to optimal cancer care is beyond the reach of too many patients. A recent study [4.Saluja R. Arciero V.S. Cheng S. et al.Examining trends in cost and clinical benefit of novel anticancer drugs over time.J Oncol Pract. 2018; 14: e280-e294Crossref PubMed Scopus (49) Google Scholar] used both the ESMO-MCBS and ASCO-NHB to establish whether clinical benefits of novel drugs have risen over time in parallel with increasing costs. Assessing 42 novel anticancer therapies from phase III randomized controlled trials over a decade from 2006 to 2015, researchers at the Sunnybrook Health Sciences Centre in Toronto scored each drug using both value frameworks. They concluded that while drug costs have risen over the past decade, the clinical benefit provided by their use has not improved proportionally. A further concern is the lack of access to treatments across borders. Of the 49 cancer medicines analyzed that were initially launched between 2010 and 2014 in 22 different countries, fewer than half were accessible by the end of 2015 to patients in all but six countries—the United States, Germany, the United Kingdom, Italy, France and Canada. Further, there is often a glaring lack of reimbursement under public insurance programmes. Out of the drugs approved from 2014 to 2015, only a handful of countries had more than half on their reimbursement lists (end 2015) [5.IMS Institute for Healthcare Informatics.Global Oncology Trend Report. 2015; Google Scholar]. While designed for different purposes, the ESMO-MCBS and ASCO-NHB ultimately aspire to provide an assessment of clinical benefit using a valid, clear, unbiased and reliable approach to data analysis. The resulting scores generated by these tools can be used to help the larger oncology community achieve a transparent and standardized approach to assessing value, which can then be used by physicians with their patients, policymakers, payers, manufacturers, and others to guide high-value cancer care delivery and research. The latest versions—ESMO-MCBS v1.1 (2017) [6.Cherny N.I. Dafni U. Bogaerts J. et al.ESMO-Magnitude of Clinical Benefit Scale version 1.1.Ann Oncol. 2017; 28: 2340-2366Abstract Full Text Full Text PDF PubMed Scopus (331) Google Scholar] and ASCO-NHB v2 (2016) [7.Schnipper L.E. Davidson N.E. Wollins D.S. et al.Updating the American Society of Clinical Oncology Value Framework: revisions and reflections in response to comments received.J Clin Oncol. 2016; 34: 2925-2934Crossref PubMed Scopus (437) Google Scholar]—employ varying approaches and scoring systems to define, measure and weigh new drug benefits. By evaluating the scoring using both scales across 97 studies in the non-curative setting, totaling 102 pairs of comparisons graded by the two scales, the new study in this issue [1.Cherny N.I. de Vries E.G.E. Dafni U. et al.Comparative assessment of clinical benefit using the ESMO-Magnitude of Clinical Benefit Scale Version 1.1 (ESMO-MCBS v1.1) and the ASCO Value Framework Net Health Benefit Score (ASCO-NHB v2).J Clin Oncol. 2019; 37: 336-349Crossref PubMed Scopus (72) Google Scholar] not only demonstrates that ASCO and ESMO are largely in agreement regarding assessment outcomes but also addresses the incorrect perception that the scales have low concordance on what constitutes high- or low-benefit studies. By applying the described thresholds, the authors identified 37 discordant scores: in 19 cases, ASCO’s score was higher than ESMO’s, while in 18 ASCO’s score was lower than the ESMO-MCBS. The unmasking of these disparities brings with it a great opportunity to understand these differences as both societies seek to make the scoring systems as informative as possible. While there are naturally different criteria and approaches adopted to develop a clinical benefit or net health benefit score, the article discusses potential factors behind non-convergence, including different approaches to the evaluation of relative and absolute gain for overall survival and progression-free survival, crediting tail of the curve gains, and application of toxicity penalties. In addition, the authors offer a four-point plan to overcome them and further improve their respective platforms. The comparative assessment of clinical benefit using ESMO-MCBS and ASCO-NHB is an important step in evaluating value in cancer care. Both societies are strongly committed to improving the utility of their analyses as well as explaining discordant data. The future development of both tools, considering the latest findings, will be key to providing robust tools for evaluating clinical benefit of anti-cancer therapies based on comparable parameters while upholding accountability for reasonableness. Both platforms represent very important tools to ensure the appropriate use of limited resources in delivering cost-effective and more affordable cancer care globally. Inarguably, data weighted and reported in these evolving scoring systems will help to identify those therapies with proven clinical benefit and guide clinical decision-making and provide physicians, patients and their families with independent, balanced information. Guided by evidence-based data reported through the ASCO and ESMO frameworks, decision makers will need to balance efficacy and reimbursement of anti-cancer treatments with regional socio-economic realities. In parallel, professional societies and organizations, including ASCO and ESMO, have a shared responsibility to help map these necessary directions. In our dedicated efforts to improve oncology practice and promote quality and high-value cancer care for all our patients, we can and will do better. None declared.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche
Catégories consensuellesIntégrité de la recherche
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,280
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,003
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0030,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0050,003
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,063
Tête enseignante GPT0,399
Écart entre enseignants0,336 · 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2019
Routes d'admission1
Résumé présentoui

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