Clinical prediction tools to identify patients at highest risk of myeloma in primary care: a retrospective open cohort study

Patients with myeloma experience substantial delays in their diagnosis, which can lead to poorer outcomes. To improve time to diagnosis, researchers aimed to generate a clinical prediction rule to identify primary care patients who are at highest risk of myeloma. They conducted a retrospective open cohort study using electronic health records data from the UK’s Clinical Practice Research Datalink between 1 January 2000 and 1 January 2014. Of 1,281,926 eligible patients, 737 (0.06%) were diagnosed with myeloma within 2 years. 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%). 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. Read Full Text