Abstract P4-16-12: Does initial cardiac imaging impact clinical outcomes in patients with breast cancer?
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".