Author

M. Petrie

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Review Open access Aug 2026

Heart Failure and Cancer: Incidence and Mortality Patterns, A Systematic Review and Meta-analysis.

BACKGROUND Cancer and heart failure (HF) frequently coexist due to population ageing and improved survival for both conditions. HF is a well-recognised complication of oncologic therapies and a potential association between HF and subsequent cancer incidence has been recently noticed. We therefore conducted a meta-analysis to quantify cancer incidence and mortality in patients with and without HF. METHODS Databases were searched from inception to 15 February 2026. Data from observational studies and randomised trials on individuals with and without HF and reporting cancer incidence and/or mortality during follow-up were included. The main outcome of interest was the incidence of any cancer; secondary outcomes included site-specific cancer incidence (lung, colorectal, breast, and prostate) and all-cause, cardiovascular, and cancer-related mortality. RESULTS Twelve studies comprising 8,979,195 individuals were included. HF was associated with a higher incidence of cancer (hazard ratio [HR] 1.33, 95% confidence interval [CI] 1.14-1.54), with substantial heterogeneity (I2 = 99.7%). Cancer site-specific analyses showed increased incidences of lung (HR 1.70, 95% CI 1.26-2.29), colorectal (HR 1.28, 95% CI 1.11-1.48), and breast (HR 1.19, 95% CI 1.04-1.37), but not prostate, cancer. Effect estimates varied according to analytical strategy: matched HF and non-HF cohorts reported higher risk estimates than those using covariate adjustment without matching. Mortality data were sparse and heterogeneous. CONCLUSIONS HF is associated with a higher incidence of cancer, although with marked heterogeneity among studies and cancer types. Mortality and cause of death were rarely reported. The observed HF-cancer association is influenced by statistical methodology, shared risk factors, differences in surveillance intensity and cancer type, that confound analyses investigating possible causal biological links. More granular and harmonised studies are required.

L. Sanasi, A. Iaconelli, Danila Azzolina et al. · European Journal of Heart Fa... · 0 citations

Open access Jul 2026

Scalable risk stratification of undiagnosed heart failure using routine health data and its association with imaging phenotypes and outcomes.

Late diagnosis of Heart failure (HF) is associated with worse outcomes. We aimed to develop a scalable tool to identify those at high risk of undiagnosed HF using routine electronic health records (EHR). We developed and internally validated a logistic regression (FIND-HF) model for incident HF diagnosis within one year in United Kingdom primary care EHRs (CPRD-Aurum, n=3 520 186), with good prediction performance (area under the receiver operating characteristic curve (AUC) 0.79), equal to more complex modelling techniques. We externally validated FIND-HF in United Kingdom (CPRD-GOLD, n=570 850, AUC 0.72), Japan (JMDC, n=6 820 694, AUC 0.73), United States of America (Epic Cosmos, n=7 710 398, AUC 0.78), and Taiwan (NTUH, n=170 518, AUC 0.85). In a cohort who had undergone HF diagnostics an optimised FIND-HF threshold had a positive predictive value of 21.4% and a negative predictive value of 96.9%. Amongst patients with HF who had undergone cardiac magnetic resonance imaging, high FIND-HF risk compared with low FIND-HF risk as reference, was associated with increased risk of a primary composite outcome of heart failure hospitalisation or cardiovascular death and more advanced adverse remodelling including lower left ventricular ejection fraction. FIND-HF is a scalable EHR-based model which has the potential to help rule out undiagnosed HF in low risk cases, whilst high risk cases are associated with more advanced cardiac dysfunction and worse prognosis.

Y. Nakao, R. Nadarajah, F. Shuweihdi et al. · Scientific Reports · 0 citations