Environmental Scan of Genetic and Genomic Biomarker Testing Assessment Frameworks, Processes, and Inventories in Cancer Care
Notice bibliographique
Résumé
What Is the Issue? Precision medicine is rapidly emerging and increasingly being adopted in cancer care. Precision medicine relies on testing for biomarkers, such as genes or proteins, to provide information about disease status and likely response to treatment. However, approaches to evaluating and implementing testing for various biomarkers are not standardized and vary between jurisdictions in Canada. What Did We Do? This Environmental Scan included a literature review and consultations to identify and summarize existing assessment frameworks, processes, and guiding principles that inform the implementation of or funding decisions for biomarker testing in cancer care. We summarized and compiled key concepts from the frameworks, literature from within and outside of Canada, and consultations for guiding principles, assessment criteria, and decision-making processes. We also identified and described existing inventories, databases, and lists of genetic and genomic biomarkers for which testing is currently available or is being funded in cancer care in jurisdictions across Canada. What Did We Find? Four guiding principles were identified through the literature and consultations: health rights of individuals and communities transparency and accountability collaboration, cooperation, and engagement social justice and equity. Three categories of assessment criteria were identified: evidentiary (i.e., clinical condition, test considerations, characterization of available evidence, and personal considerations) implementation (i.e., health system context, health care context, and social and ethical values) decision-making (i.e., deliberation and recommendations, and priorities for future research). Five categories or steps within a decision-making process were identified: test nomination evidence reviews and impact assessment deliberation and recommendations communication and engagement implementation. Biomarker assessment and decision-making processes vary substantially across jurisdictions in Canada, with some implementing structured systems that emphasize reviews of evidence and clinical guidelines through a centralized evaluation process, while other jurisdictions operate a more decentralized process that may be driven by clinical demand. In some jurisdictions, there are key distinctions between decision-making for companion diagnostic testing (in support of targeted drug therapies) and other biomarker testing (used for prognostic or predictive purposes or in support of nondrug therapies). Funding approaches vary, with some jurisdictions allocating specific budgets for biomarker tests, while others integrate requests into broader laboratory or health budgets. Many provinces in Canada maintain inventories or lists of available biomarker testing, with some more comprehensive and current than others, and some intended for internal use by health providers requesting tests and others also intended for access by members of the public. What Does This Mean? The guiding principles, assessment criteria, and decision-making processes we compiled through our literature review and consultations can support and inform the development of consistent and efficient approach to assessment and decision-making for biomarker testing in Canada. A consensus assessment framework could help to establish standardized assessment criteria and help to reduce inequities in availability and access to timely biomarker testing in cancer care.
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 | 0,111 | 0,228 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,020 | 0,042 |
| Études des sciences et des technologies | 0,015 | 0,017 |
| Communication savante | 0,020 | 0,009 |
| Science ouverte | 0,005 | 0,010 |
| Intégrité de la recherche | 0,003 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».