Abstract P1-04-09: Evaluating the Necessity and Impact of Cardiac Imaging on Breast Cancer Care in Northwestern Ontario
Bibliographic record
Abstract
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.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".