Skip to main content
Research project

CANDID - Cancer Diagnosis Decision Rules

Project overview

Please visit the CANDID website:

In primary care the key areas of concern for both doctor and patients are delay in diagnosing cancer, getting high risk patients referred first, and keeping unnecessary investigation to a minimum. There have been few valid studies to assist decision making in primary care, either to get a patient referred quickly or to assist in making sure an anxious patient is effectively reassured.

This study seeks to work out which of the symptoms and examination findings are the most effective in predicting lung or colon cancer. To decide the best clinical information to collect in the study we will interview patients and also get consensus from a group of experts. Then we will recruit several thousand patients who consult their GP half with lung symptoms and the other half with low bowel symptoms. Clinical information will be collected using standardised internet based forms. Willing patients will complete lifestyle questionnaires and provide blood samples (including for genetic analysis).

The National Cancer Registry will then be monitored to see which patients develop cancer, and statistical analysis will determine the most important clinical variables that predict cancer. The clinical prediction 'rules' or decision aids developed from these studies will then be tested with further patients for each condition for validity.


Lead researcher

Professor Paul Little

Professor in Primary Care Research
Other researchers

Professor Geraldine Leydon

Prof of Medicine, Sociology & Healthcare

Research interests

  • Healthcare communication
  • Qualitative methods in health reesarch 
  • Optimising the patient experience

Collaborating research institutes, centres and groups

to top