Value of baseline clinical and CMR characteristics for the prediction of cancer therapeutics-related cardiac dysfunction: results from the Cardiotoxicity Prevention Research Initiative (CAPRI)
Bibliographic record
Abstract
Abstract Background Whether baseline cardiovascular health status significantly influences the risk of Cancer Therapeutics-Related Cardiac Dysfunction (CTRCD) in patients receiving de-novo chemotherapy exposure is an important clinical question for both surveillance and management decisions. The reference standard technique for the serial monitoring of left ventricular (LV) volumes and ejection fraction (EF) is cardiovascular magnetic resonance (CMR). Using this technique, we sought to prospectively evaluate baseline clinical risk factors and CMR-based pre-exposure characteristics for their influence on the incident occurrence of CTRCD. Methods We prospectively enrolled 371 cancer patients referred for baseline (pre-chemotherapy) followed by surveillance CMR imaging as part of the Cardiotoxicity Prevention Research Initiative (CAPRI). We also recruited 62 healthy volunteers to evaluate for referral population differences in CMR-based markers. Study subjects and healthy volunteers underwent identical CMR imaging protocols inclusive of cine imaging, T1 and T2 mapping. CTRCD was defined according to surveillance CMR imaging with criteria established as a drop in LVEF by >5% (meaningful detectable difference for CMR technique) to a value ≤56% (lower limit of normal) at any time point during chemotherapy surveillance. A total of 1474 CMR studies were performed over a median surveillance period of 12.5 months (range 2.3 to 68.9 months). Results The majority of patients were female (77%), being referred for breast cancer (64%) or lymphoma (36%), with a mean age of 54.0±14 years. The baseline prevalence of hypertension, diabetes, hyperlipidemia, and current smoking were 32%, 11%, 46%, and 13%, respectively. Compared to healthy volunteers, cancer patients at baseline showed smaller indexed LV and RV volumes, higher indexed LV mass, and higher native T1 values (mean difference +33 msec; p<0.001). LV and right ventricular (RV) EF and T2 mapping values were not significantly different. CTRCD criteria were met in 22% of patients. Figure 1 shows a forest plot of univariable and multivariable predictors of CTRCD occurrence. Following multivariable adjustment, only combined anthracycline/trastuzumab regimen (OR 4.4, 95% CI 2.0–9.5) and baseline indexed LVEDV (OR 2.3, 95% CI 1.2–4.5) were found to be significant predictors of this outcome. Conclusion Using the reference standard of serial CMR imaging we identified that of all baseline (pre-chemotherapy) clinical and CMR-based markers of cardiovascular health, only indexed LV end-doastolic volume (EDV) was independently associated with future occurrence of CTRCD following adjustment for chemotherapy regimen. We did not observe significant associations with conventional cardiac risk factors in our study population. The observed risk for indexed LVEDV was clinically meaningful (2.3-fold risk per 10 ml/m2) and warrants further investigation as a relevant baseline marker of risk in this referral population. Figure 1. Forest plot of predictors of CTRCD Funding Acknowledgement Type of funding source: Public Institution(s). Main funding source(s): Alberta Innovates/Genome Alberta: CAPRI
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".