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Computer tool 'improves cancer diagnosis'

Monday 31st October 2011

A new computer tool could be used to improve diagnosis and prognosis for cancer patients, according to University of Nottingham researchers.

Scientists from the university teamed up with ClinRisk Ltd to develop the algorithm and found it to be successful in identifying those suffering with gastro-oesophageal cancer and lung cancer at an earlier stage by flagging up potentially worrying combinations of symptoms and risk factors.

According to the study, published in the British Journal of General Practice, the ten per cent of patients the algorithm predicted as at the most risk of developing one of the two diseases made up 77 per cent of all the gastro-oesophageal and lung cancers diagnosed over the following two years.

"Earlier diagnosis of cancer is a major challenge and we hope this new research will help doctors identify patients for earlier referral and investigation," said Professor Julia Hippisley-Cox, research leader.

Authors believe the tool could contribute towards the achievement of the government policy and the National Awareness and Early Diagnosis Initiative.

Researchers created two web calculators available for use by doctors, but say that a simpler version could be made available on the internet to raise public awareness.

It was noted that lung cancer is a huge challenge when it comes to diagnosis as symptoms can be common and non-specific.

Red flag symptoms for the disease include a new onset of coughing, coughing up blood, weight loss, loss of appetite and anaemia. If doctors concentrate on just one of these symptoms, they are likely to miss around 80 per cent of lung cancer cases.

Meanwhile, earlier diagnosis of gastro-oesophageal cancer could vastly improve five-year survival among people with the condition.

Vomiting blood, difficulty swallowing, apetite loss, weight loss and abdominal pain are all alarm symptoms for the condition, but focusing on just one of these factors means doctors will miss up to 40 per cent of cases.

Written by James PuckleADNFCR-1780-ID-800782146-ADNFCR

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