Abstract PS9-47: A scoping review characterizing “choosing wisely” recommendations for breast cancer management
Notice bibliographique
Résumé
Abstract Background: Choosing Wisely (CW)® was created by the American Board of Internal Medicine (ABIM) to promote patient-physician conversations about unnecessary medical tests and treatment. It is estimated that 20% of healthcare cost is wasted on ineffective interventions. National societies such as American Society of Clinical Oncology, Americal Society of Breast Surgeons, and American Society for Radiation Oncology have developed lists of recommendations within the Choosing Wisely initiative to to eliminate non-evidence based practices and improve patient outcomes. Similarly, other countries outside of the US have created their own national panels of experts called “CW® campaigns” which typically review recommendations submitted by that country’s oncology societies. We performed a scoping review to consolidate CW® recommendations from different groups with respect to breast cancer care. Methods: A systematic search of Medline and Embase for English language publications presenting CW® recommendations for breast cancer care practices was conducted from Jan 1, 2011 - May 11, 2020. The search was designed and peer reviewed by information specialists. We also reviewed the CW® websites of ABIM and associated international CW® campaigns. Two reviewers independently screened studies for inclusion and performed data extraction, and findings were summarized narratively. Results: Review of ABIM CW® recommendations showed 26 breast cancer-related recommendations. These pertained to: screening (n=5), radiological staging (n=2), treatment (n=15), surveillance (n=2), and miscellaneous (genetic testing and pathology; n=2). Treatment recommendations were sub-classified into surgery (n= 9), chemotherapy (n= 2), radiation therapy (n= 2), and supportive therapy (n= 2). Of 20 countries which have a CW® campaign and endorse recommendations for a range of diseases, 13 have published recommendations for breast cancer. While most international campaigns published recommendations on the same topics as the ABIM campaign, 6 campaigns developed recommendations on new topics. These included: follow-up visits (Canada), involvement of multi-disciplinary teams and imaging in palliative care setting (India) and comparison of screening imaging modalities (Portugal). There was concordance in screening, treatment, and surveillance recommendations between the CW® campaigns. Conclusion: CW® recommendations focus on reducing overutilization of investigations and treatments. Breast cancer screening and treatment were most frequently addressed by CW® recommendations. There was a high rate of consensus between international CW® recommendations with respect to breast cancer care. As health care systems globally move attention to reduce low value care, further studies are required to address adherence to these current recommendations and develop new recommendations addressing topics not currently included in the US CW campaigns. Citation Format: Hely Shah, Julian Surujballi, Arif A Awan, Brian Hutton, Angel Arnaout, Risa Shorr, Lisa Vandermeer, Meshari J Alzahrani, Mark Clemons. A scoping review characterizing “choosing wisely” recommendations for breast cancer management [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS9-47.
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 | 0,053 | 0,249 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,006 | 0,007 |
| Bibliométrie | 0,031 | 0,030 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,006 | 0,006 |
| Science ouverte | 0,004 | 0,004 |
| Intégrité de la recherche | 0,004 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 ».