October 11, 2024Cardio-Oncology5 citationsOpen Access
Comparison of heart failure risk assessment tools among cancer survivors
Resultado clave
The HFA-ICOS and ARIC-HF risk scores outperformed the PCP-HF score in predicting incident heart failure among cancer survivors, with HFA-ICOS demonstrating an AUC of 0.753 compared to 0.717 for PCP-HF.
Diseño del estudio
Tipo
Cohort (n=132,128)
Multicéntrico
Sí
PICO estructurado
Do HFA-ICOS and ARIC-HF scores provide better discrimination for incident heart failure compared to PCP-HF in cancer survivors?
P
Población
33,032 cancer survivors from the UK Biobank, including 9,232 survivors of breast cancer or lymphoma (mean age 59.9 years, 87.8% female) and 23,800 survivors of other cancer types (mean age 59.1 years, 85.8% female).
I
Intervención
Heart failure risk assessment using HFA-ICOS and ARIC-HF scores
C
Comparador
Heart failure risk assessment using PCP-HF score
O
Resultado
Predictive performance for incident heart failure measured by area under the curve (AUC)
HFA-ICOS and ARIC-HF risk scores offer modest but superior discrimination for incident heart failure compared to PCP-HF in cancer survivors, highlighting the need for cancer-specific prediction tools.
Resultado numérico
Estimación del efecto: AUC (95% CI 0.739-0.766)
Tasa de eventos absoluta: 0.753% vs 0.717%
valor p: p=<0.001
Limitaciones
- Participants are mostly Caucasians, limiting generalizability to other ethnicities.
- Exclusion of participants with previous HF diagnosis eliminates a key determinant for HFA-ICOS, potentially underestimating its accuracy.
- Key clinical data including biomarkers and cancer treatments were not fully available.
- Utilization of ICD-10 codes may result in underdiagnosis of chronic diseases.
- Cancer patients who consented for the UK-Biobank might generally be healthier than frailer patients, limiting external validity.
Resumen
BACKGROUND: Cancer survivors have an increased risk of incident heart failure (HF) attributable to shared risk factors and cancer treatment-induced cardiac dysfunction. Selection for HF screening depends on risk assessment, but the optimal means of assessing risk is undefined. We undertook a comparison of HF risk calculators among survivors. METHODS: In this study from the UK Biobank, cancer and HF diagnoses were determined based on the International Classification of Diseases (ICD)-10 code and non-cancer participants were included as controls. Participants' risk of incident HF was determined using the Heart Failure Association-International Cardio-oncology Society (HFA-ICOS), the Atherosclerosis Risk in Communities (ARIC-HF) and the Pooled Cohort Equations to Prevent Heart Failure (PCP-HF). The predictive performances of each were compared using the area under the curve (AUC). RESULTS: After propensity matching with age and sex, 9,232 survivors from breast cancer or lymphoma (mean age 59.9 years, 87.8% female), and 23,800 survivors from other cancer types (mean age 59.1 years, 85.8% female) were included in the analysis. The discriminative value for HFA-ICOS (AUC 0.753 95%CI: 0.739-0.766) and ARIC-HF (0.757 95%CI: 0.744-0.770) were similar, and superior to PCP-HF (0.717 95%CI: 0.702-0.732). The overall performance for each risk score was better among participants in other cancer types than those with breast cancer and lymphoma. CONCLUSIONS: HFA-ICOS and ARIC-HF outperformed the PCP-HF among cancer- and non-cancer cohort, although all showed modest discrimination for incident HF to be applied to clinical practice. A cancer-specific HF prediction tool could facilitate HF prevention among survivors.