What Is Important When Making Treatment Decisions in Metastatic Breast Cancer? A Qualitative Analysis of Decision-Making in Patients and Oncologists
Notice bibliographique
Résumé
BACKGROUND: Metastatic breast cancer (MBC) is an ideal environment for shared decision-making because of the large number of guideline-based treatment options with similar efficacy but different toxicity profiles. This qualitative analysis describes patient and provider factors that influence decision-making in treatment of MBC. MATERIALS AND METHODS: Patients and community oncologists completed in-person interviews. Academic medical oncologists participated in focus groups. Interviews and focus groups were audio-recorded, transcribed, and analyzed using NVivo. Using an a priori model based on the Ottawa Framework, two independent coders analyzed transcripts using a constant comparative method. Major themes and exemplary quotes were extracted. RESULTS: Participants included 20 patients with MBC, 6 community oncologists, and 5 academic oncologists. Analysis of patient interviews revealed a decision-making process characterized by the following themes: decision-making style, contextual factors, and preferences. Patient preference subthemes include treatment efficacy, physical side effects of treatment, emotional side effects of treatment, cognitive side effects of treatment, cost and financial toxicity, salience of cutting-edge treatment options (clinical trial or newly approved medication), treatment logistics and convenience, personal and family responsibilities, treatment impact on daily activities, participation in self-defining endeavors, attending important events, and pursuing important goals. Physician decisions emphasized drug-specific characteristics (treatment efficacy, side effects, cost) rather than patient preferences, which might impact treatment choice. CONCLUSION: Although both patients with MBC and oncologists considered treatment characteristics when making decisions, patients' considerations were broader than oncologists', incorporating contextual factors such as the innovative value of the treatment and life responsibilities. Differences in perspectives between patients and oncologists suggests the value of tools to facilitate systematic communication of preferences in the setting of MBC. IMPLICATIONS FOR PRACTICE: Both patients with metastatic breast cancer (MBC) and oncologists emphasized importance of efficacy and physical side effects when making treatment decisions. However, other patient considerations for making treatment decisions were broader, incorporating contextual factors such as the logistics of treatments, personal and family responsibilities, and ability to attend important events. Furthermore, individual patients varied substantially in priorities that they want considered in treatment decisions. Differences in perspectives between patients and oncologists suggest the value of tools to facilitate systematic elicitation of preferences and communication of those preferences to oncologists for integration into decision-making in MBC.
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 | 0,023 | 0,037 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,011 | 0,012 |
| Communication savante | 0,006 | 0,005 |
| Science ouverte | 0,002 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,004 |
| 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 ».