Abstract P4-04-14: Economic analysis of germline genetic testing to assess for hereditary breast cancer: a systematic review
Notice bibliographique
Résumé
Abstract Introduction: Germline genetic testing (GGT) is included in clinical guidelines and has steadily increased in use to inform treatment decisions for breast cancer patients and those with genetic predisposition. The expanding implementation has magnified the influence of GGT on the economics of breast cancer care worldwide. The objective of this systematic review was to evaluate the economic impact of GGT among adults diagnosed with breast cancer, those at increased risk of breast cancer, and in the general population. Methods: This analysis was part of a broader study following PRISMA methodology. PubMed-Medline and Embase were searched for manuscripts published after January 2013 that reported the clinical, economic, and humanistic outcomes of GGT in patients with breast cancer and those at risk of breast cancer. The present analysis summarizes a subset of articles specifically addressing the economic value of GGT. Results: The initial search, inclusive of all outcomes, identified 10,198 studies. Of the 231 articles extracted for data analysis, 30 studies evaluated economic outcomes. Twenty-four of these were cost-effectiveness analyses related to testing for hereditary breast cancer; the remaining six studies were cost comparison analyses or budget impact models. Of the 24 cost-effectiveness studies, five were multinational and evaluated the cost-effectiveness of GGT in 12 countries (US, UK, Germany, Canada, Norway, Netherlands, Spain, Israel, India, Brazil, China, and Malaysia). The US (n=10) and the UK (n=7) were studied most frequently; however, there was notable heterogeneity derived from different international healthcare systems and varying patient populations. The studies modeled the effect of testing patients diagnosed with breast cancer (n=7) or breast/ovarian cancer (n=1), testing individuals with an increased risk of breast cancer (n=6), and population-specific genetic screening (n=10). Both single-syndrome (BRCA1/2; n=17) and multigene testing strategies (n=7) were investigated. Thirteen studies employed a Markov model. Close to half of the studies (n=11/24) considered cascade testing, and almost all (n=22/24) considered risk-reducing surgery (breast and/or ovarian). All studies were analyzed from a payer perspective; six used both payer and societal perspectives. Studies evaluated cost-effectiveness against various willingness-to-pay (WTP) thresholds. Each study found at least one cost-effective strategy for all countries and perspectives. Four studies presented GGT strategies that were cost-saving. Conclusions: This analysis presents the economic impact of GGT for hereditary breast cancer syndromes with global representation and a range of testing strategies. In all settings, the analyses found GGT to be cost-effective, supporting the positive economic impact of GGT for hereditary breast cancer. Opportunities for further exploration include the added value of cascade testing and use of multigene panels, as well as the evaluation of economic impact from the patient perspective. Citation Format: Heather Johnson, Deborah Hartzfeld, Mary Linton Peters, Jade Xiao, Bhakti Mody, Carol Kirshner, Feyza Sancar, Brandie Heald, Joyce Kong, Jecinta Scott, Gebra Cuyún Carter. Economic analysis of germline genetic testing to assess for hereditary breast cancer: a systematic review [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2024; 2024 Dec 10-13; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(12 Suppl):Abstract nr P4-04-14.
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 | 0,012 | 0,074 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,009 | 0,010 |
| Bibliométrie | 0,008 | 0,009 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 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 ».