Influence of BI-RADS Breast Density Scores on the Implementation of Supplemental Imaging Modalities in Those With Average Risk and Negative Mammogram by Primary Care Providers in British Columbia
Notice bibliographique
Résumé
Introduction: Breast Imaging-Reporting and Data System (BI-RADS) density scores have been included in screening mammography reports in BC since 2018. Despite these density scores being present in screening mammography reports for numerous years, there remains insufficient evidence to guide supplemental testing for patients with dense breasts. Objective: The primary objective of this study was to evaluate how primary care providers in Canada utilize BI-RADS density scores reported on normal screening mammograms of average risk, asymptomatic patients in their clinical practice. The secondary objective of this study was to determine if there are any patterns related to primary care provider demographics and practice settings in BC that could be linked to differences in screening practices for patients based on BI-RADS density scores. Methods: A cross-sectional survey was conducted with family physicians (FPs) and nurse practitioners (NPs) practicing in BC. Descriptive statistics were calculated using percentages and further stratified by participant demographics. P values were derived from Fisher’s exact test and results were regarded as statistically significant at P < .05. Results: Ninety-eight participants (85 FPs, 13 NPs) responded to the survey. The percentage of participants who ordered supplemental testing based on BI-RADS density scores alone was 8% for BI-RADS score D, 37% for BI-RADS scores C or D, and 2% for BI-RADS scores B, C, or D. Forty-eight percent of female participants and 45% of male participants would order supplemental testing based on BI-RADS density scores alone ( P = 1). Forty-nine percent of FPs and 39% of NPs would order supplemental testing based on BI-RADS density scores ( P = .56). Fifty-three percent of participants who had been in practice for more than 10 years, 50% of those who had been in practice for 6 to 10 years, and 36% of those in practice for 5 years or less would order supplemental testing ( P = .34). Fifty-seven percent of those practicing in large urban centres, 43% of those practicing in medium-sized communities, and 32% of those in rural or remote communities would order testing ( P = .17). Fifty-seven percent of participants were aware of the increased risk of breast cancer with higher breast density. Conclusion: Variations exist in how primary care providers in BC utilize the BI-RADS density scores reported on normal screening mammography of average risk, asymptomatic patients in their clinical practice. Further research in this area is needed to establish clearer clinical guidelines to educate and inform primary care providers on the need for supplemental testing for patients with dense breasts and to improve resources for breast cancer screening in BC.
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 | 0,001 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».