Echocardiographic indicators of anthracycline cardiotoxicity in breast cancer patients with normal left ventricular ejection fraction: Experience of the first cardio-oncology unit in Morocco

Abstract

Anthracycline is a mainstay in the treatment of many cancers, especially breast cancer. Anthracyclines are known for their significant cardiotoxic potential. Although the cardiotoxicity induced by anthracyclines is dose-dependent and often irreversible, it can occur very early at the start of treatment and sometimes even very late after several years from the end of treatment. The aim of this study was to assess whether echocardiographic measurements of LV function, in the case of normal LVEF, predict the development of anthracycline cardiotoxicity in patients followed for breast cancer. We conducted a longitudinal study of 2329 cancer patients including 2284 female breast cancer survivors, recruited from the cardio-oncology unit in Casablanca, who were diagnosed with primary invasive breast cancer between January 2017 and April 2022. All patients underwent pre-, per- and post-chemotherapy echocardiography. LV volumes, LVEF, MAPSE, S’LV, maximum longitudinal strain were measured. Of 2284 patients, 64% had normal resting LVEF. Mean LVEF was 56 ± 5%, global longitudinal strain (GLS) was −17.4 ± 2.2%, and LV end diastolic volume (LVEDV) was 108 ± 17 mL, MAPSE was 17 ± 5 mm and S’VG was 9+/4 cm/s. 12% percent presented with cardiotoxicity: heart failure with alteration of LVEF by more than 15% (CI) in 163 patients, 67% of whom had an altered S’LV < 8 cm/s) and an altered SGL (>−18%), arterial hypertension in 58 patients, 17 cases of pericardial effusions, 15 cases of arrhythmias, 6 cases of 3rd degree atrioventricular block and 3 cases of right ventricular dysfunction. Age, diabetes, obesity, GLS and LVEDV were all predictive of MACE (P = 0.028, 0.017, 0.041, 0.038 and 0.014 respectively). In patients treated with anthracyclines with normal pre-chemotherapy LVEF, longitudinal function (MAPSE AND S’LV) and baseline GLS predict the development of cardiotoxicity. This helps us to develop algorithms for close monitoring in this type of patient.