A web-based prediction score for head and neck cancer referrals.

OBJECTIVE: Following the announcement of the NHS Cancer Plan in 2000, anyone suspected of having cancer has to be seen by a specialist within 2 weeks of referral. Since this introduction, studies have shown that only 6.3%-14.6% of 2-week referrals were diagnosed with a head and neck cancer and that majority of the cancer diagnoses were via other referral routes. These studies suggest that the referral scheme is not currently cost-effective. Our aim is to develop a scoring system that determines the risk of head and neck cancer in a patient, which can then be used to aid GP referrals.

DESIGN: Retrospective data were collected from 1075 patients with 2-week head and neck cancer referrals from general practitioners. The retrospective data collected included patients' demographics, risk factors and relevant investigations. The data were used as input into a logistic regression to arrive at our model. Our approach included data analysis, machine learning techniques, statistical inference and model validation metrics to arrive at the best performing model. The model was then tested with more data from 235 prospective patients.

RESULTS: Using our results from the logistic regression, we created a web-based tool that GPs can use to calculate their patient's probability of cancer and use this result to assist in their decision regarding referral. Our prototype can be seen in Figure 2.

CONCLUSION: We have created a prototype scoring system that can be hosted online to assist GPs with their referrals with a sensitivity of 31% and specificity of 92%. While we acknowledge that there are several limitations to our model, we believe we have created a novel preliminary scoring system that has the potential to be improved dramatically with further data and be very helpful for GPs in a long run.