Mitral annular plane systolic excursion and global longitudinal strain for the prediction of cardiotoxicity or heart failure in lymphoma patients treated with anthracycline-based chemotherapy. (3rd October 2022)

• Record Type: Journal Article
• Authors: Vallejo, B; Quintero-Martinez, J A; Mogollon, R J; Cordova-Madera, S N; Garcia-Arango, M; Nhola, L F; Alam, M M; Herrmann, J; Boddicker, N J; Cerhan, J R; Thompson, C A; Villarraga, H R
• Is Part Of: European heart journal. Volume 43(2022)Supplement 2
• Publication Date: 2022-10-03
• Subjects: Cardiology -- Periodicals; Heart -- Diseases -- Periodicals; 616.12005
• DOI: 10.1093/eurheartj/ehac544.058
• Languages: English
• ISSNs: 0195-668X

Abstract

Abstract: Background: Assessing cardiac performance of patients receiving chemotherapy is a cornerstone for adequate cardiovascular care. Mitral annular plane systolic excursion (MAPSE) has been considered as a surrogate for Ejection Fraction (EF). However, little is known about its role in predicting Cardiotoxicity or Heart Failure in Lymphoma patients, as its relationship with Global Longitudinal Strain (GLS) and EF. Purpose: Our aims were: i) to evaluate if MAPSE and GLS can predict the development of CT and/or HF in lymphoma patients treated with anthracyclines and ii) to evaluate its correlation with GLS and EF. Methods: For this prospective observational study, 325 Hodgkin (HL) & non-Hodgkin (NHL) lymphoma patients (n=325) treated with anthracyclines were recruited from 2013 to 2021 and followed for 1 year. MAPSE by M-mode and GLS by Speckle-Tracking (ST) were measured at baseline (T0), during treatment (T1), and up to 1 year after chemotherapy completion (T2). CT was defined as a decrease in EF by >10% to a value <50% and HF by a cardiologist as the first occurrence after the initiation of anthracyclines. Logistic regression analyses with Receiving operator characteristics (ROC) and Area under the curve (AUC) were performed. Pearson's correlation coefficient was also calculated. A p-value <0.05 was considered statistically significant. Results: Two hundred sixty-four patients (81.2%) had NHL and 61 (18.8%) HL. Of these, fifteen (4.6%) and 21 individuals (6.4%) developed CT at T1 and T2, respectively. Nine subjects (2.8%) developed HF at T1 and 14 (4.3%) at T2. MAPSE at T0 had the highest AUC to predict both HF at T1 (AUC=0.865, cut-off 14.9, sensitivity 100%, specificity 63%, p=0.008) and at T2 (AUC=0.757, cut-off 10.9, sensitivity 67%, specificity 93%, p=0.045). This same variable at T1 predicted HF at T2 with an AUC of 0.752 (cut-off 11.4, sensitivity 67%, specificity 94%, p=0.004). For CT prediction at T2, MAPSE at T1 had an AUC of 0.738 (cut-off 12.5, sensitivity 56%, specificity 85%, p<0.0001). GLS at T0 predicted CT at T1 (AUC=0.657, cut-off −19, sensitivity 67%, specificity 63%, p=0.012) and when obtained at T1, it predicted CT at T2 (AUC=0.776, cut-off −17, sensitivity 74%, specificity 75%, p-value <0.0001) (Table 1). Pearson's correlation between MAPSE and GLS at T0 (coefficient −0.25, p=0.023) at T1 (coefficient −0.38, p<0.0001) at T2 (coefficient −0.037, p<0.0001) and MAPSE with EF at T0 (coefficient 0.33, p=0.0002) at T1 (coefficient 0.28, p<0.0001) and T2 (coefficient 0.29, p<0.001). Conclusions: To our best knowledge, this is the first time that MAPSE and GLS were compared to predict CT and HF in lymphoma patients receiving anthracycline-based chemotherapy; we have demonstrated that MAPSE measured at T0 was a very good predictor of HF at T1. Either MAPSE or GLS assessment at T0 and T1 were able to predict CT or HF. Future studies could explore the combination of these two variables to predict either CT or HF. Funding Acknowledgement: Type of funding sources: Private hospital(s). Main funding source(s): Department of Cardiovascular Medicine. Mayo Clinic, Rochester-MN