Shifting perspectives on the value of non-OS endpoints and PROs: Considerations across stakeholder groups to support oncology HTA decision-making.
Notice bibliographique
Résumé
e13646 Background: The ability of novel cancer drugs to extend patients’ overall survival (OS) has been key to determining their approval and access conditions. However, in some disease settings, OS can have limitations: delayed access due to the time required to collect mature OS data; confounding from subsequent treatment lines; and poor ability to reflect value beyond survival. Stakeholders such as regulators and physicians increasingly recognise the value of non-OS endpoints as surrogates for OS. In addition, non-OS endpoints and patient reported outcomes (PROs) may have stand-alone value, e.g., in capturing disease burden. However, stakeholders are misaligned on the benefits of non-OS endpoints and PROs due to differences in underlying value drivers. Methods: This study investigates stakeholder perceptions of non-OS endpoints and PROs, based on 76 semi-structured interviews with physicians, patients, patient advocacy groups (PAGs), regulators and health economists in 7 key markets (U.S., Canada, Japan, UK, France, Germany and Italy), 3 roundtable discussions and a literature review. Results: Non-OS endpoints address some concerns with OS as they can be captured earlier in trials and may act as surrogates of OS; show reduced susceptibility to confounding; and better reflect the value to patients beyond survival. However, the value perception of non-OS endpoints and PROs varies across stakeholders: 1) Patients / PAGs value non-OS endpoints as they capture outcomes beyond mortality, e.g., the avoidance of surgery and PROs such as pain. 2) Physicians acknowledge the scientific and clinical trial limitations of relying primarily on OS, but note that OS limitations vary by cancer type / stage. 3) Regulators are accepting of non-OS endpoints, providing accelerated / conditional approvals when they are used as surrogates for OS or when they have standalone value, and increasingly expect PROs in submission dossiers. 4) Payers are uncertain, as without appropriate validation, drugs approved based on non-OS endpoints risk additional treatment burden and cost to healthcare systems without patient benefit. The limited alignment in value perception among stakeholders is further complicated as this may shift during the course of the disease – e.g., patients at early stages may value treatments which prolong survival but may place more emphasis on quality of life and freedom from progression as the disease advances. Conclusions: The value of non-OS endpoints and PROs is increasingly recognised, particularly by physicians and regulators; payers, however, can be less accepting, driven largely by uncertainties around their value, as surrogates or as stand-alone measures of benefit. Stakeholders must align on the value of non-OS endpoints and PROs, ensuring they are fit for purpose for each cancer type / stage, to improve their acceptance and advance patient access to novel therapies.
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 | 0,158 | 0,203 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,010 | 0,009 |
| Communication savante | 0,016 | 0,013 |
| Science ouverte | 0,002 | 0,015 |
| Intégrité de la recherche | 0,010 | 0,014 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
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 ».