Abstract P4-16-12: Does initial cardiac imaging impact clinical outcomes in patients with breast cancer?
Notice bibliographique
Résumé
Abstract Background: Echocardiography (echo) and multigated acquisition (MUGA) scans are the most commonly used modalities to assess cardiac function during breast cancer (BC) treatment. However, a case series of 176 patients with cancer suggests enhanced cardiac care with echo surveillance. We hypothesized that patients with early BC imaged by echo have improved cardiac outcomes compared to those imaged by MUGA. Methods: Consecutive patients with stage I to III breast cancer undergoing pre-treatment echo or MUGA were retrospectively screened from January 2010 to December 2014. Patients participating in clinical trials with mandated imaging and/or cardiac reviews were excluded. Demographics, medical history and clinical events were collected via chart review and electronic health records. All patients had a minimum 1 year of follow-up. The primary outcome was a composite of death, cardiac hospitalization or cardiac emergency room visit. Results: 598 patients were identified as having a baseline echo and 636 had had baseline MUGA. Mean follow-up was 4.5±1.4 years. Patients undergoing MUGA were younger, had more advanced stage of disease and received more anthracycline and trastuzumab (table1). Patients imaged by MUGA had lower cardiac function at baseline compared to echo, LVEF 64% vs. LVEF 65% respectively, P <0.001. Cancer therapy related cardiac dysfunction was similar between groups, 10% vs. 11%, p=0.81. Patients in the echo group were more likely to be seen by cardiology, 7% vs. 3%, p<0.0001, and to be initiated on beta blocker, 4% vs. 1%, p=0.006, or angiotensin converting enzyme inhibitor, 3% vs. 1%, p=0.002.However, there was no difference between groups for the primary outcome, 10% event rate in each group, even after adjustment for age, BC stage, chemotherapy and cardiac medications, hazard ratio 1.04 (CI 0.72-1.49), p=0.842. Conclusion: For patients with early stage BC, the choice of cardiac imaging modality at baseline does not impact adverse cardiac events. However, patients undergoing echo were more likely to be evaluated and managed by cardiology. Table 1.Baseline Characteristics Echo (N=598)MUGA (N=636)Age mean54±1053±10*BMI mean29±629±7Cardiovascular HistoryDiabetes66(11%)56(9%)Hypertension154(26%)155(24%)Dyslipidemia83(14%)75(12%)CAD9(2%)6(1%)CHF7(1%)4(1%)Beta Blocker22(4%)28(4%)ACE-Inhibitor51(9%)64(10%)Angiotensin Receptor Blocker69(12%)44(7%)*Cancer HistoryStage*Stage I65(11%)56(9%)Stage II377(63%)361(57%)Stage III155(26%)219(34%)Receptor StatusTriple negative64(11%)76(12%)HER2 negative, hormone positive342(58%)387(61%)HER2 positive192(32%)173(27%)Cancer TherapyChemotherapy (any)528(88%)594(93%)*Anthracycline310(52%)394(62%)*Trastuzumab170(28%)148(23%)*Anthracycline & trastuzumab6(1%)19(3%)*Hormone therapy459(77%)487(77%)Radiation (any)487(81%)527(83%)Radiation left side237(49%)259(49%)Surgery597(100%)633(100%)* p<0.05 for comparison between echo and MUGA groups Citation Format: Parent S, Xu L, Becher H, Mackey J, King K, Pituskin E, Paterson I. Does initial cardiac imaging impact clinical outcomes in patients with breast cancer? [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-16-12.
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 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».