医学
心脏毒性
乳腺癌
内科学
梅德林
接收机工作特性
荟萃分析
肿瘤科
癌症
化疗
政治学
法学
作者
Elisé G. Kaboré,Conor James MacDonald,Ahmed Kaboré,R. Didier,Patrick Arveux,Nicolas Méda,Marie‐Christine Boutron‐Ruault,Charles Guenancia
出处
期刊:JAMA network open
[American Medical Association]
日期:2023-02-23
卷期号:6 (2): e230569-e230569
被引量:4
标识
DOI:10.1001/jamanetworkopen.2023.0569
摘要
Cardiotoxicity is a serious adverse effect that can occur in women undergoing treatment for breast cancer. Identifying patients who will develop cardiotoxicity remains challenging.To identify, describe, and evaluate all prognostic models developed to predict cardiotoxicity following treatment in women with breast cancer.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.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.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.
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