Risk prediction models for cancer therapy related cardiac dysfunction in patients with cancer and cancer survivors: systematic review and meta-analysis.
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OBJECTIVES: To systematically review all prediction models developed or validated for cancer therapy related cardiac dysfunction (CTRCD) and to quantitatively analyse their performance. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Embase, Medline, and the Cochrane Central Register of Controlled Trials, from inception to 23 August 2024. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Studies that developed or externally validated multivariable models to predict CTRCD risk in young people (children, adolescents, and young adults (≤39 years)) or older adults (≥40 years) with cancer or cancer survivors treated with systemic antineoplastic agents. Studies on radiation induced cardiotoxicity were excluded. METHODS: Two reviewers independently screened studies, extracted data, and assessed risk of bias using the Prediction model Risk Of Bias ASsessment Tool. Performance measures were pooled using random effects meta-analyses. RESULTS: 56 studies were included, reporting 51 developed models and 12 externally validated models. Most models were developed in adults (n=34/51, 67%), primarily for breast cancer (n=20/34, 59%) or haematological malignancies (n=6/34, 18%) to determine pretreatment risk (n=33/34, 97%). In young people, most developed models (n=16/17, 94%) focused on long term risk assessment, mostly in survivors of haematological malignancies. Discrimination and calibration metrics were reported for 13/51 (25%) developed models and 6/44 (14%) external validations. Nearly all models were at high risk of bias. 12/51 (24%) developed models underwent external validation, four of 17 (24%) in young people and eight of 34 (24%) in adult populations. The Heart Failure Association-International Cardio-Oncology Society (HFA-ICOS) tool was the most frequently validated (11 times), mainly in patients with breast cancer receiving HER2 (human epidermal growth factor receptor 2) targeted therapies (5/11, 45%). Across all external validations, this tool consistently underestimated risk, with observed event rates exceeding predicted risks, especially in studies where mild CTRCD was the most frequently reported outcome. Among patients with breast cancer treated with anti-HER2 agents, the pooled C statistic was 0.60 (95% confidence interval 0.52 to 0.68). In this population, observed pooled event rates were 12% in the low risk group (<2% predicted), 15% in the medium risk group (2-9%), 25% in the high risk group (10-19%), and 41% in the very high risk group (≥20%). CONCLUSIONS: Existing prediction models for CTRCD need additional evidence before widespread clinical adoption. Poor reporting of key performance metrics and limited external validation studies currently restrict their thorough evaluation. The HFA-ICOS tool shows suboptimal performance, especially when mild forms of CTRCD are included as events. Future research should prioritise validating and updating existing models using large, clustered datasets across various malignancies to enhance the assessment of their performance, generalisability, and clinical utility in routine practice. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42023475469.