NIHR Oxford Biomedical Research Centre

Enabling translational research through partnership

MENUMENU
  • About
    • About the NIHR Oxford Biomedical Research Centre
    • A Guide to What We Do
    • Activities during COVID-19
    • Strategic Partnership Board
    • Steering Committee
    • Promoting Equality, Diversity and Inclusion in Research
    • Current Vacancies
    • Contact Us
    • Stay in Touch
  • Research
        • OUR 20 RESEARCH THEMES

        • Antimicrobial Resistance and Modernising Microbiology
        • Cardiovascular
        • Clinical Informatics and Big Data
        • Diabetes and Metabolism
        • Gastroenterology and Mucosal Immunity
        • Genomic Medicine
        • Haematology and Stem Cells
        • Imaging
        • Molecular Diagnostics
        • Multi-Modal Cancer Therapies
        • Multi-Morbidity and Long-Term Conditions
        • Musculoskeletal
        • Neurological Conditions
        • Obesity, Diet and Lifestyle
        • Partnerships for Health, Wealth and Innovation
        • Respiratory
        • Stroke and Vascular Dementia
        • Surgical Innovation and Evaluation
        • Technology and Digital Health
        • Vaccines for Emerging and Endemic Diseases
        • Oxford Biomedical Research Centre activities during COVID-19
  • Patient & Public Involvement
    • Getting involved with research
    • Researcher Guidance
    • Post an opportunity for patient and public involvement
  • Training Hub
    • Training Hub Overview
    • Clinical Academic Pathway
    • Internships
    • Preparatory Research Fellowships
    • Senior Research Fellowships
    • Research Training Bursaries
    • Doctoral Awards
    • Post-Doctoral Awards
    • Other funding
    • Leadership Training
    • Useful Links
    • Training and Education Resources
    • Upcoming Training Events & Courses
  • Industry
    • Collaborate with Oxford BRC
    • What Can We Do For Your Organisation?
    • Who Do We Work With?
    • IP and Licensing
    • Contacts for Industry
  • Videos
  • News
  • Events

News

You are here: Home > Clinical Informatics and Big Data > New clinical prediction tools for myeloma developed

New clinical prediction tools for myeloma developed

9 April 2021 · Listed under Clinical Informatics and Big Data, Multi-Modal Cancer Therapies

University of Oxford researchers have developed new clinical prediction models for use in primary care with the aim of accelerating the diagnosis of myeloma, a cancer of the bone marrow.

Histopathological image of multiple myoloma
(Photo: wikimedia commons)

Myeloma caused 117,077 deaths worldwide in 2020. Earlier diagnosis improves the rate of survival but unfortunately, delays in myeloma diagnosis are common and result in poorer patient outcomes.

One reason for these delays is that myeloma symptoms are non-specific and relatively common in people without cancer. For example, back pain is associated with myeloma, yet there are many other non-myeloma causes of this symptom.

Additional measures are therefore needed to highlight the possibility of myeloma in patients where GPs do not initially suspect this disease. GPs frequently order simple laboratory tests, such as the full blood count, to investigate patients presenting with non-specific symptoms.

Previous research by Dr Constantinos Koshiaris, Dr Jason Oke, Dr Brian Nicholson and colleagues from the University of Oxford’s Nuffield Department of Primary Care Health Sciences and the University of Exeter identified certain abnormalities in blood test results that indicate a higher risk of myeloma, such as low haemoglobin which can be observed up to two years before a myeloma diagnosis.

In their latest paper, published in the British Journal of General Practice, this research team, a number of whose members are supported by the NIHR Oxford Biomedical Research Centre, have developed new clinical prediction models for myeloma that incorporate both symptoms and blood test results.

Using the Clinical Practice Research Datalink (GOLD version), a primary care database containing electronic health records for more than 11 million patients in the UK, the team identified the most common symptoms and full blood count results recorded for patients with myeloma.

The most predictive of these were included in the models they developed and the new tools were validated against a set of test data. Decisions made using their prediction models resulted in fewer false positives and more true positives when compared to single tests or symptoms alone.

By identifying patients at highest risk of myeloma in primary care, these new prediction rules have the potential to reduce diagnostic delays by a substantial amount.

Further research is now needed to understand more about the feasibility and implementation of this tool in the primary care setting and the impact it will have on the diagnostic pathway and patient outcomes.

← Risk of severe COVID-19 from asthma and other respiratory diseases may be only modestly increased, new analysis suggests
National survey reveals big reductions in COVID-19 infections with single dose of Oxford-AZ and Pfizer vaccines →

News

  • Study highlights ongoing COVID-19 risk in some cancer patients despite vaccination 24 May 2022
  • BRC study outlines researchers training needs and barriers 20 May 2022
  • Three new Blood and Transplant Research Units created in Oxford 18 May 2022
See full news archive

News Categories

Month Archives

Subscribe to the Oxford BRC Newsletter

Keep informed about the work of the Oxford BRC by subscribing to our Mailchimp e-newsletter. It is produced several times a year and delivers news and information about upcoming events straight to your inbox.

Subscribe Now

Oxford BRC on Social Media

  • Facebook
  • LinkedIn
  • Twitter
  • YouTube

Feedback

We’d love to hear your feedback. Please contact us at obrcenquiries@ouh.nhs.uk

  • Sitemap
  • Data Control and Privacy
  • Accessibility
  • Our Partners
  • Disclaimer
  • Contact

Copyright © 2022 NIHR Oxford Biomedical Research Centre