This research will study blood tests (known as 'inflammatory markers') that detect inflammation in the body. The inflammation is probably due to illness of some sort, but the tests do not identify the exact cause. It may be as simple as a viral infection or as serious as cancer. Sometimes abnormal results sound a false alarm, increasing uncertainty and anxiety for everyone. Sometimes they may help GPs detect illness earlier.
This research aims to help GPs make better informed decisions when dealing with inflammatory marker test results.
We will study 80,000 people who have had an inflammatory marker blood test in 2014, and 20,000 with no inflammatory markers. We will measure how many of these people have a diagnosis of cancer, infections or autoimmune diseases in the year after testing. We use this to calculate the chance of serious disease in people with normal or raised inflammatory markers.
We will calculate how this risk of disease varies depending on the 'cut off' or maximum safe level of inflammatory marker test result chosen. This will help doctors dealing with test results to know when to reassure people, and when to do further tests to look for cancer, infection and autoimmune disease.
Millions of inflammatory marker tests (C reactive protein, plasma viscosity and eosinophil sedimentation rate) are performed in the UK annually and testing rates are rising. Most studies of inflammatory markers describe laboratory findings for one single disease, usually in secondary care. The spectrum of diseases seen with abnormal results in primary care is not known, making interpretation of results challenging for GPs.
This study aims to identify the conditions diagnosed subsequent to an inflammatory marker blood test in primary care. We will study 80,000 patients with inflammatory marker tests in 2014; and 20,000 matched patients with no inflammatory markers. We will measure the subsequent incidence of cancer, infection and autoimmune diseases in the test normal and test positive groups in order to calculate positive and negative predictive values for infections, autoimmune conditions and cancers. We will plot diagnostic accuracy at different levels of raised inflammatory marker using receiver operator curve analysis of sensitivity against 1-specificity, to explore optimum thresholds. We compare incidence of disease in the tested versus untested groups to calculate the diagnostic accuracy of the clinician's decision to request inflammatory markers. The findings will help clinicians receiving test results make informed decisions about appropriate further investigations or reassurance.
Incidence of cancer - Number of consultations - Number of antibiotic prescriptions - Incidence of infections - Number of blood tests - Incidence of autoimmune conditions - Number of referrals
Jessica Watson - Chief Investigator - University of Bristol
Jessica Watson - Corresponding Applicant - University of Bristol
Chris Salisbury - Collaborator - University of Bristol
Hayley Jones - Collaborator - University of Bristol
Penny Whiting - Collaborator - University of Bristol
Theresa Redaniel - Collaborator - University of Bristol
William Hamilton - Collaborator - University of Exeter
Yvette Pyne - Collaborator - University of Bristol