Strategies for improving biomarker testing rates in non-small cell lung cancer in north America: a scoping review
Notice bibliographique
Résumé
Background: Biomarker testing plays a pivotal role in the management of non-small cell lung cancer (NSCLC). However, despite advancements in diagnostic technologies and clinical guidelines recommending widespread use, the adoption of biomarker testing in routine practice remains inconsistent. To address these gaps, this study summarizes the common barriers to biomarker testing in NSCLC and highlights practical solutions to increase utilization. Methods: We conducted a scoping review, guided by the JBI Manual of Evidence Synthesis and PRISMA-ScR checklist, with a comprehensive search of six databases (Medline, Embase, Cochrane CENTRAL, CINAHL, Scopus, and Web of Science) focused on NSCLC biomarker testing in U.S. and Canadian adult populations. Eligible studies addressed barriers or proposed solutions to improve testing implementation and utilization. Titles and abstracts were independently screened by two reviewers using Covidence, and data were extracted and thematically synthesized to identify common challenges and actionable strategies. Results: A total of 7,192 records were identified through database searches, of which 27 studies underwent full-text screening, and 14 studies met the inclusion criteria. Three overarching themes were identified: operational barriers, communication and knowledge gaps, and access and financial challenges. Operational barriers were the most frequently reported, with time-related constraints in 85.7% of studies and insufficient tissue samples in 74%. Proposed solutions included streamlining reflex testing and standardizing policy protocols and workflows (both reported in 50% of studies), leveraging advanced testing technologies (43%), and adopting comprehensive next-generation sequencing (NGS) panels (14%). Communication and knowledge gaps were also prominent, with knowledge deficiencies reported in 57% of studies and challenges in care coordination in 64%. Solutions to these issues included supporting education and continuous learning (71%), promoting multidisciplinary collaboration and tumor boards (57%), and leveraging data and technology (43%). Access and financial barriers were primarily driven by inadequate funding, which was reported in 71% of studies, and limited access to NGS, reported in 29%. Proposed solutions included securing funding for biomarker testing infrastructure (29%) and improving reimbursement and coverage policies (14%). Conclusions: This study highlights critical gaps in biomarker testing for NSCLC, with operational challenges and inadequate funding emerging as the most significant barriers, while being accompanied by the fewest proposed solutions. In contrast, communication and knowledge deficits were well-addressed, presenting opportunities for immediate interventions, such as enhancing education and multidisciplinary collaboration.
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 | 0,096 | 0,259 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,006 | 0,009 |
| Bibliométrie | 0,039 | 0,034 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,010 | 0,013 |
| Science ouverte | 0,005 | 0,006 |
| Intégrité de la recherche | 0,005 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».