Abstract P1-04-09: Evaluating the Necessity and Impact of Cardiac Imaging on Breast Cancer Care in Northwestern Ontario
Notice bibliographique
Résumé
Abstract Background: Over 25,000 women are annually diagnosed with breast cancer in Canada. Their survival rates have improved significantly due to advances in screening and treatment. However, many treatments are cardiotoxic, and cardiovascular disease is currently the leading competing cause of death in older breast cancer survivors. Baseline left ventricular ejection fraction (LVEF) is a reliable predictor of heart failure (HF) in patients receiving anthracyclines (AC) and/or trastuzumab. Identification of reduced LVEF can promote interventions to prevent HF and improve patient outcomes. Accordingly, pre-treatment cardiac imaging is supported by the National Comprehensive Cancer Network (NCCN) Clinical Practice Guidelines. Research Question:Despite the perceived necessity of cardiac imaging before and during breast cancer treatment, the recommendations underlying its use is mostly based on expert opinion rather than specific data. This research aims to analyze local data to determine the impact of cardiac imaging on treatment outcomes for breast cancer patients receiving AC and/or trastuzumab and offer evidence-based guidance for ordering physicians at the Thunder Bay Regional Health Sciences Centre (TBRHSC). Methods: This is a retrospective cohort study including all female patients seen at the TBRHSC who were treated with AC and/or trastuzumab for newly diagnosed breast cancer between January 1, 2012, and December 31, 2017. Data, including baseline characteristics, treatment regimen, imaging tests ordered from diagnosis until one-year post-treatment, and clinical outcomes were collected from the patient’s medical records and recorded in a secure REDCap database. Patients were grouped into three cohorts based on treatment regimen: trastuzumab only (A), AC only (B), and both trastuzumab and AC (C). Initially, 125 patients were identified, but those who did not receive either treatment or had no imaging tests recorded were excluded from this study. Results: A total of 93 patients met the exclusion criteria for this analysis, with an average age at diagnosis of 59.5 years (SD = 10.4). Invasive ductal carcinoma was the most common cancer (97.8%, n=91). Most cancers were diagnosed at stage 2 (51.6%, n=48), followed by stage 1 (24.7%, n=23), and stage 3 (14.0%, n=13); 9.7% (n=9) had unknown stages. Regarding receptor status, 69.9% (n=65) were ER-positive, 62.4% (n=58) were PR-positive, and 34.4% (n=32) were HER2-positive. BRCA1/2 status was unknown for 79.6% (n=74) of the patients included in this study. In cohort A (n=3), 14 scans (4.67 per patient) led to 1 change in care (7.1%). Cohort B (n=60) had 75 scans (1.25 per patient) resulting in 10 changes in care (13.3%), including changes in chemotherapy (4.0%, n=3), care provider (5.3%, n=4), and medication (4.0%, n=3). Cohort C (n=30) had 144 scans (4.80 per patient) leading to 6 changes in care (4.2%). Conclusion: This study found that the most significant changes in patient care based on cardiac imaging occurred in patients receiving only AC treatment, with changes happening in 13.3% of cases and each patient receiving an average of 1.25 scans. However, patients receiving only trastuzumab or a combination of trastuzumab and AC had fewer changes in care (7.1% and 4.2%, respectively) despite having more scans per patient (4.67 and 4.80, respectively). This indicates that more frequent scans do not always lead to more useful information. The study highlights the importance of focusing cardiac imaging on those most likely to benefit, especially in areas with limited resources like Northwestern Ontario. Future research will aim to identify predictive factors for the optimal use of cardiac imaging to enhance resource allocation and patient outcomes. Citation Format: Hannah Shortreed, Rabail Siddiqui, Olexiy Aseyev. Evaluating the Necessity and Impact of Cardiac Imaging on Breast Cancer Care in Northwestern Ontario [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 P1-04-09.
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 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».