ASSIGN score and cancer risk in the Scottish Heart Health Extended Cohort (SHHEC) study

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Abstract

Background

The aim of this work was to determine whether the ASSIGN cardiovascular disease (CVD) score, a 10-year CVD risk score used in primary care in Scotland, could additionally detect cancer risk.

Methods

18,107 participants were recruited to the Scottish Heart Health Extended Cohort (SHHEC) study between 1982 and 1995. Information on health and lifestyle were collected, along with blood and urine, and participants were followed up via record linkage to 2017. Cox proportional hazards were used to estimate HRs (95% CIs) for time to cancer diagnosis.

Results

A total of 5046 cases of cancer were reported during the follow up period. ASSIGN was significantly associated with a diagnosis of cancer, with a 2.3–3.4% increase in risk of cancer per 1-point increase of ASSIGN. The components of ASSIGN predominantly associated with the risk of cancer were age (HR 1.52; 95% CI 1.48–1.56, cholesterol level (HR 1.11; 95% CI 1.08–1.13), diabetes status (HR 1.24; 95% CI 1.01–1.53), and systolic blood pressure (HR 1.16; 95% CI 1.13–1.19).

Conclusion

ASSIGN could be used not only to predict CVD, but also to predict cancer risk in patients. This needs to be validated in further cohorts.

Related collections

Most cited references 16

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Molecular Biomarkers in Cancer

Virinder Kaur Sarhadi, Gemma Armengol (2022)

Molecular cancer biomarkers are any measurable molecular indicator of risk of cancer, occurrence of cancer, or patient outcome. They may include germline or somatic genetic variants, epigenetic signatures, transcriptional changes, and proteomic signatures. These indicators are based on biomolecules, such as nucleic acids and proteins, that can be detected in samples obtained from tissues through tumor biopsy or, more easily and non-invasively, from blood (or serum or plasma), saliva, buccal swabs, stool, urine, etc. Detection technologies have advanced tremendously over the last decades, including techniques such as next-generation sequencing, nanotechnology, or methods to study circulating tumor DNA/RNA or exosomes. Clinical applications of biomarkers are extensive. They can be used as tools for cancer risk assessment, screening and early detection of cancer, accurate diagnosis, patient prognosis, prediction of response to therapy, and cancer surveillance and monitoring response. Therefore, they can help to optimize making decisions in clinical practice. Moreover, precision oncology is needed for newly developed targeted therapies, as they are functional only in patients with specific cancer genetic mutations, and biomarkers are the tools used for the identification of these subsets of patients. Improvement in the field of cancer biomarkers is, however, needed to overcome the scientific challenge of developing new biomarkers with greater sensitivity, specificity, and positive predictive value.

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Biomarkers in Colorectal Cancer: Current Research and Future Prospects

Olorunseun O. Ogunwobi, Fahad Mahmood, Akinfemi Akingboye (2020)

Colorectal cancer (CRC) is a leading cause of death worldwide, despite progress made in detection and management through surgery, chemotherapy, radiotherapy, and immunotherapy. Novel therapeutic agents have improved survival in both the adjuvant and advanced disease settings, albeit with an increased risk of toxicity and cost. However, metastatic disease continues to have a poor long-term prognosis and significant challenges remain due to late stage diagnosis and treatment failure. Biomarkers are a key tool in early detection, prognostication, survival, and predicting treatment response. The past three decades have seen advances in genomics and molecular pathology of cancer biomarkers, allowing for greater individualization of therapy with a positive impact on survival outcomes. Clinically useful predictive biomarkers aid clinical decision making, such as the presence of KRAS gene mutations predicting benefit from epidermal growth factor receptor (EGFR) inhibiting antibodies. However, few biomarkers have been translated into clinical practice highlighting the need for further investigation. We review a range of protein, DNA and RNA-based biomarkers under investigation for diagnostic, predictive, and prognostic properties for CRC. In particular, long non-coding RNAs (lncRNA), have been investigated as biomarkers in a range of cancers including colorectal cancer. Specifically, we evaluate the potential role of lncRNA plasmacytoma variant translocation 1 (PVT1), an oncogene, as a diagnostic, prognostic, and therapeutic biomarker in colorectal cancer.

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CanRisk Tool—A Web Interface for the Prediction of Breast and Ovarian Cancer Risk and the Likelihood of Carrying Genetic Pathogenic Variants

Tim Carver, Simon Hartley, Andrew Lee … (2021)

The CanRisk Tool (https://canrisk.org) is the next-generation web interface for the latest version of the BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) state-of-the-art risk model and a forthcoming ovarian cancer risk model.

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Author and article information

Contributors

Jill JF. Belch: j.j.f.belch@dundee.ac.uk

Journal

Journal ID (nlm-ta): BJC Rep

Journal ID (iso-abbrev): BJC Rep

Title: BJC Reports

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2731-9377

Publication date (Electronic): 1 October 2024

Publication date PMC-release: 1 October 2024

Publication date Collection: 2024

Volume: 2

Electronic Location Identifier: 75

Affiliations

[1 ]GRID grid.416266.1, ISNI 0000 0000 9009 9462, The Institute of Cardiovascular Research, Division of Molecular and Clinical Medicine, University of Dundee, , Ninewells Hospital, ; Dundee, UK

[2 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, The George Institute for Global Health, School of Public Health, , Imperial College London, ; London, UK

[3 ]GRID grid.1005.4, ISNI 0000 0004 4902 0432, The George Institute for Global Health, , University of New South Wales, ; Sydney, NSW Australia

Article

Publisher ID: 102

DOI: 10.1038/s44276-024-00102-5

PMC ID: 11523964

SO-VID: 567cf044-da38-4846-8917-7cc3a00d8588

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 13 February 2024

Date revision received : 2 September 2024

Date accepted : 12 September 2024

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100011314, Sir John Fisher Foundation;

Funded by: The Northwood Trust

Funded by: The Miller Bequest

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