Evidence map›Paper›PMID 40939222›Full record

ArticleJACC. Advances2025

Development of an Electronic Medical Record-Based Score for Heart Failure Prediction in Cancer Survivors.

Cheng Hwee Soh, Lena Nguyen, Anna Chu, Agus Salim, Husam Abdel-Qadir, Thomas H Marwick

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Article in JACC. Advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Cheng Hwee SohImaging Research Laboratory, Baker Heart and Diabetes Institute, Melbourne, Australia; Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia; Baker Department of Cardiovascular Research, Translation and Implementation, La Trobe University, Melbourne, Australia.
Lena NguyenInstitute for Clinical Evaluative Sciences (ICES), Toronto, Ontario, Canada.
Anna ChuInstitute for Clinical Evaluative Sciences (ICES), Toronto, Ontario, Canada.
Agus SalimBaker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia.
Husam Abdel-QadirInstitute for Clinical Evaluative Sciences (ICES), Toronto, Ontario, Canada.
Thomas H MarwickImaging Research Laboratory, Baker Heart and Diabetes Institute, Melbourne, Australia; Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia; Menzies Institute for Medical Research, Hobart, Australia. Electronic address: tom.marwick@baker.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAwareness of heart failure (HF) as a long-term complication of cancer has led to an interest in HF surveillance among survivors. However, existing HF risk scores are not tailored for survivors and not designed for the use in electronic medical records (EMRs) or administrative data sets where clinical data such as blood pressure and pathology results are often unavailable.

objectivesThe objective of the study is to develop a cancer-specific incident HF risk score suitable for screening in EMR or administrative data sets.

methodsThe cancer-specific HF prediction from EMRs in survivor health care (CHERISH) risk score was developed from risk variables identified in 16,191 cancer survivors (mean 61 years; 59.5% female) derived from the UK Biobank. External validation was conducted in a population-based Ontario cohort (n = 446,096; mean 67 years; 53.9% female). HF risk classification with CHERISH was compared against the ARIC (Atherosclerotic Risk In Community)-HF score using area under the curve (AUC).

resultsThe CHERISH score incorporates 11 clinical variables-age, years since cancer diagnosis, coronary heart disease, arrhythmia, myocardial infarct, diabetes, hypertension, leukemia, non-Hodgkin lymphoma, lung cancer, and breast cancer. CHERISH demonstrated strong prediction of 10-year HF incidence during internal validation (AUC: 0.829), exceeding ARIC-HF (AUC: 0.697; P < 0.001). In external validation, CHERISH showed an AUC of 0.721 in predicting 10-year HF incidence, compared to an AUC of 0.751 (P < 0.001) with ARIC-HF.

conclusionsThe integration of the CHERISH score into EMR systems may provide large-scale, automated HF risk assessment in cancer survivors, using routinely collected clinical data.

Indexed as

cardio-oncologycardiovascular preventioncardiovascular toxicity

Identifiers

PMID40939222
PMCPMC12791888

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