Abstract PS16-09: A decision support intervention to promote the use of preventive therapy among women at high risk for invasive breast cancer
Notice bibliographique
Résumé
Abstract Background: Clinical trials have reported significant breast cancer risk reduction with preventive therapy among women at high risk for invasive disease, but these medications remain underutilized. We developed risk communication and decision support tool comprised of an educational video and graphic display of benefits of preventive therapy for providers to use during patient consultations. The primary aim was to increase the uptake of preventive therapy among high-risk women. Methods: Women aged 35–69 years with a history of lobular carcinoma in situ (LCIS) or atypical hyperplasia (AH) receiving care at MD Anderson Cancer Center, Houston, Texas, were eligible to participate. After cognitive testing, a field test was performed on two patient populations before (pre-implementation) and after incorporating the tool into clinical practice (implementation). Study participants completed self-administered questionnaires including knowledge about preventive therapy, treatment preferences, decisional conflict, shared decision-making process and Ottawa acceptability scales; physicians completed surveys on their experiences with the decision support tool. Descriptive analyses and standard tests of association were performed. Results: Of the 48 female participants who completed surveys, 21 were in the implementation group. Majority of the participants were non-Hispanic (80.8%), White (75%), with a college degree or more (63.8%) and mean age of 53 years. Most participants had good knowledge about the role of preventive therapy but only 10% pre-implementation and 15% in the implementation group correctly identified that taking preventive therapy can reduce the risk of breast cancer by up to 50%. Overall, 65.2% of participants were leaning towards taking preventive therapy. Compared to those in the implementation group, women in the pre-implementation group were more likely to be unsure about their decision (34.6% vs 20.0%, p=0.088). Participants in the implementation group were less likely to take preventive therapy (57.1% vs 70.4%, p=0.428). Decision making process scores were high (3.26 vs 3.65, p=0.122) and decisional conflict was low in both groups (12.9 vs 16.1, p=0.498). While participants in the implementation group agreed that the amount of information provided by the tool was just right (80%), they found the materials slanted towards taking preventive therapy (75%). Using a psychometric assessment, physicians gave high ratings for acceptability (mean 4.1, SD 0.6), feasibility (mean 4.4; SD 0.60) and appropriateness (mean 4.2, SD 0.6) of the tool and were satisfied/very satisfied (83.3%) with the tool. Conclusion: Although study participants had good health literacy, the majority were unaware of the significant benefit of preventive therapy in reducing breast cancer risk. A greater percentage of women in the pre-implementation group were unsure about their decision compared to women who received the tool but after receiving the tool, women in the implementation group were less likely to agree to preventive therapy. These findings suggest that the decision support tool might reduce the proportion of patients uncertain about preventive therapy but increase preference for not starting treatment. The next steps are to enhance provider discussions on the benefits of preventive therapy, test the decision support tool in less educated and underrepresented minority populations, and track adherence to preventive therapy in patients who receive the tool. Citation Format: Inimfon Jackson, Lisa Lowenstein, Parijatham S. Thomas, Therese Bevers, Viola Leal, Jurnie Hinde, Robert J. Volk, Abenaa M. Brewster. A decision support intervention to promote the use of preventive therapy among women at high risk for invasive breast cancer [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 PS16-09.
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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 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,016 | 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 ».