Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

BACKGROUND: Patients with myeloma experience substantial delays in their diagnosis, which can adversely affect their prognosis. AIM: To generate a clinical prediction rule to identify primary care patients who are at highest risk of myeloma. DESIGN AND SETTING: Retrospective open cohort study using electronic health records data from the UK's Clinical Practice Research Datalink (CPRD) between 1 January 2000 and 1 January 2014. METHOD: Patients from the CPRD were included in the study if they were aged ≥40 years, had two full blood counts within a year, and had no previous diagnosis of myeloma. Cases of myeloma were identified in the following 2 years. Derivation and external validation datasets were created based on geographical region. Prediction equations were estimated using Cox proportional hazards models including patient characteristics, symptoms, and blood test results. Calibration, discrimination, and clinical utility were evaluated in the validation set. RESULTS: Of 1 281 926 eligible patients, 737 (0.06%) were diagnosed with myeloma within 2 years. Independent predictors of myeloma included: older age; male sex; back, chest and rib pain; nosebleeds; low haemoglobin, platelets, and white cell count; and raised mean corpuscular volume, calcium, and erythrocyte sedimentation rate. A model including symptoms and full blood count had an area under the curve of 0.84 (95% CI = 0.81 to 0.87) and sensitivity of 62% (95% CI = 55% to 68%) at the highest risk decile. The corresponding statistics for a second model, which also included calcium and inflammatory markers, were an area under the curve of 0.87 (95% CI = 0.84 to 0.90) and sensitivity of 72% (95% CI = 66% to 78%). CONCLUSION: The implementation of these prediction rules would highlight the possibility of myeloma in patients where GPs do not suspect myeloma. Future research should focus on the prospective evaluation of further external validity and the impact on clinical practice.

Original publication

DOI

10.3399/BJGP.2020.0697

Type

Journal article

Journal

Br J Gen Pract

Publication Date

05/2021

Volume

71

Pages

e347 - e355

Keywords

cancer, diagnosis, epidemiology, myeloma, primary care, Aged, Cohort Studies, Humans, Male, Multiple Myeloma, Primary Health Care, Prospective Studies, Retrospective Studies, Risk Assessment