Investigating prescribing patterns for as-yet-undiagnosed cancer symptoms and their utility in managing diagnostic uncertainty in primary care

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Early cancer detection can vastly improve the prognosis of cancer patients [1]. General practitioners (GPs) serve as gatekeeper for further investigation in symptomatic patients. In primary care, many early symptoms of cancer are non-specific and hard to differentiate from symptoms of other conditions, most of which do not require specialist diagnostic assessment. When patients present with low risk (but not no risk) symptoms, GPs need to triage these patients to identify those needing further investigation. Best practice safety-netting guidelines aim to ensure patients are followed up until symptoms are explained or resolved [2]. However GP interviews show that clearer guidance on the aspects of clinical practice that contribute towards effective safety-netting is needed [3]. This would reduce inadequate safety-netting implementation which is linked to diagnostic error in primary care [4]. Understanding how other clinical pre-diagnostic events influence how GPs safety-net, patient help-seeking behaviours, and the interplay between these factors could help clarify effective safety-netting practice. Research defines the GP-patient conversation as a key determinant of patients' self-management behaviour and health outcomes [5]. Identifying practices that actively promote appropriate patient help-seeking behaviours is warranted as much of the qualitative evidence base on GP-patient interactions doesn't include potential patient behaviours that could lead to diagnostic error in primary care [6]. Patient healthcare utilisation patterns prior to diagnosis show higher diagnostic activity and increasing numbers of GP consultations for up to a year before diagnosis. These patterns indicate a window of opportunity for earlier diagnosis exists in some patients, ranging between 6 to 4 months. Patients often receive prescriptions after consulting in primary care where a decision was taken not to refer. Understanding how prescriptions are used to manage low-risk symptoms may be a useful way to identify windows of opportunity for earlier diagnosis. Emerging research from Denmark has observed increased prescribing patterns of COPD drugs, antibiotics and opioids prior to lung cancer diagnosis, and haemorrhoid drugs, laxatives, oral iron and opioids prior to colorectal or colon cancer diagnosis. Research has also begun discriminate cancer risk associated with prescription drugs, and drugs prescribed to treat symptoms of not-yet-diagnosed cancer. In the UK, recent linkage of national cancer registration data with national prescriptions data opened the possibility of conducting similar studies. Additionally, since 2015 CPRD, a very well-established research resource including anonymised information from patient electronic health records from UK practices (including information on prescription) is also linked to cancer registration data. Machine learning approaches have identified statistical evidence of differential prescribing patterns in lung and colorectal cancers pre-diagnosis. Analysis of prescribing patterns for additional tumour groups is required to help identify windows of opportunity for earlier diagnosis across the disease group. The tenet of the proposed studies is that by understanding the interplay between GP prescribing decisions and GP safety-netting practices we can improve the speed of cancer diagnosis.