Biomarker Determinants of Early Anthracycline-Induced Left Ventricular Dysfunction in Breast Cancer: A Systematic Review and Meta-Analysis.

BACKGROUND AND

OBJECTIVE

Breast cancer is the leading cause of cancer-related mortality amongst women. One of the most common chemotherapeutic agents used to treat breast cancer, anthracyclines, are associated with anthracycline-induced cardiotoxicity (ACIC). The aim of this meta-analysis was to quantify the predictive performance of biomarkers for early ACIC presentation in the breast cancer population.

METHODS

Five databases were searched from inception to 1 January, 2022. Studies reporting the association between worsening left ventricular ejection fraction and biomarker level change were included. Overall, study heterogeneity varied between I2 0 and 78%. The primary outcome was incident left ventricular dysfunction, defined as left ventricular ejection fraction < 50-55% or a 10%-point decrease, in patients with breast cancer with congruent ≥ doubling of biomarker serology levels (growth differentiation factor 15, Galectin-3, pro B-type natriuretic peptide, high-sensitivity cardiac troponin T, placental growth factor, myeloperoxidase, high-sensitivity C-reactive protein, Fms-Related Tyrosine Kinase 1), 3 months after anthracycline exposure, relative to pre-anthracycline exposure levels, expressed as random effects, hazard ratios. The STRING protein interaction database was explored for experimentally validated biomarker interactions.

RESULTS

Of 1458 records screened, four observational studies involving 1167 patients, with a low risk of bias, were included in this systematic review and meta-analysis. Doubling of growth differentiation factor 15 and Galectin-3 levels was associated with an increased risk of early ACIC, hazard ratio 3.74 (95% confidence interval 2.68-5.24) and hazard ratio 4.25 (95% confidence interval 3.1-5.18), respectively. Biomarker interactome analysis identified two putative ACIC biomarkers, neuropilin-1 and complement factor H.

CONCLUSIONS

This is the first meta-analysis quantifying the association of biomarkers and early ACIC presentation in the breast cancer population. This may be of clinical relevance in the timely identification of patients at high risk of ACIC, allowing for closer monitoring and chemotherapy adjustments.