Association of body mass index and cardiotoxicity related to anthracyclines and trastuzumab in early breast cancer: French CANTO cohort study.

BACKGROUND: In patients treated with cardiotoxic chemotherapies, the presence of cardiovascular risk factors and previous cardiac disease have been strongly correlated to the onset of cardiotoxicity. The influence of overweight and obesity as risk factors in the development of treatment-related cardiotoxicity in breast cancer (BC) was recently suggested. However, due to meta-analysis design, it was not possible to take into account associated cardiac risk factors or other classic risk factors for anthracycline (antineoplastic antibiotic) and trastuzumab (monoclonal antibody) cardiotoxicity. METHODS AND FINDINGS: Using prospective data collected from 2012-2014 in the French national multicenter prospective CANTO (CANcer TOxicities) study of 26 French cancer centers, we aimed to examine the association of body mass index (BMI) and cardiotoxicity (defined as a reduction in left ventricular ejection fraction [LVEF] > 10 percentage points from baseline to LVEF < 50%). In total, 929 patients with stage I-III BC (mean age 52 ± 11 years, mean BMI 25.6 ± 5.1 kg/m2, 42% with 1 or more cardiovascular risk factors) treated with anthracycline (86% epirubicin, 7% doxorubicin) and/or trastuzumab (36%), with LVEF measurement at baseline and at least 1 assessment post-chemotherapy were eligible in this interim analysis. We analyzed associations between BMI and cardiotoxicity using multivariate logistic regression. At baseline, nearly 50% of the study population was overweight or obese. During a mean follow-up of 22 ± 2 months following treatment completion, cardiotoxicity occurred in 29 patients (3.2%). The obese group was more prone to cardiotoxicity than the normal-weight group (9/171 versus 8/466; p = 0.01). In multivariate analysis, obesity (odds ratio [OR] 3.02; 95% CI 1.10-8.25; p = 0.03) and administration of trastuzumab (OR 12.12; 95% CI 3.6-40.4; p < 0.001) were independently associated with cardiotoxicity. Selection bias and relatively short follow-up are potential limitations of this national multicenter observational cohort. CONCLUSIONS: In BC patients, obesity appears to be associated with an important increase in risk-related cardiotoxicity (CANTO, ClinicalTrials.gov registry ID: NCT01993498). TRIAL REGISTRATION: ClinicalTrials.gov NCT01993498.

Risk Prediction Models for Cardiotoxicity of Chemotherapy Among Patients With Breast Cancer: A Systematic Review.

Importance: Cardiotoxicity is a serious adverse effect that can occur in women undergoing treatment for breast cancer. Identifying patients who will develop cardiotoxicity remains challenging. Objective: To identify, describe, and evaluate all prognostic models developed to predict cardiotoxicity following treatment in women with breast cancer. Evidence Review: This systematic review searched the Medline, Embase, and Cochrane databases up to September 22, 2021, to include studies developing or validating a prediction model for cardiotoxicity in women with breast cancer. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was used to assess both the risk of bias and the applicability of the prediction modeling studies. Transparency reporting was assessed with the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) tool. Findings: After screening 590 publications, we identified 7 prognostic model studies for this review. Six were model development studies and 1 was an external validation study. Outcomes included occurrence of cardiac dysfunction (echocardiographic parameters), heart failure, and composite clinical outcomes. Model discrimination, measured by the area under receiver operating curves or C statistic, ranged from 0.70 (95% IC, 0.62-0.77) to 0.87 (95% IC, 0.77-0.96). The most common predictors identified in final prediction models included age, baseline left ventricular ejection fraction, hypertension, and diabetes. Four of the developed models were deemed to be at high risk of bias due to analysis concerns, particularly for sample size, handling of missing data, and not presenting appropriate performance statistics. None of the included studies examined the clinical utility of the developed model. All studies met more than 80% of the items in TRIPOD checklist. Conclusions and Relevance: In this systematic review of the 6 predictive models identified, only 1 had undergone external validation. Most of the studies were assessed as being at high overall risk of bias. Application of the reporting guidelines may help future research and improve the reproducibility and applicability of prediction models for cardiotoxicity following breast cancer treatment.