The lives of hundreds of women could be saved every year, thanks to a simple online calculator that could help GPs identify women most at risk of having ovarian cancer at a much earlier stage.
Academics from The University of Nottingham and ClinRisk Ltd have developed a new QCancer algorithm using the UK QResearch database. The new algorithm assesses a combination of patients' symptoms and risk factors to red flag those most likely to have ovarian cancer and enable them to be referred for further investigation or treatment at a much earlier stage.
A study into the effectiveness of the algorithm, published online this week at BMJ.com, has shown that it was successful in predicting almost two-thirds of ovarian cancers in the 10 per cent of women who were most at risk of having the disease over a two year period.
Leading the research, Professor Julia Hippisley-Cox, said: "Ovarian cancer is notoriously difficult to spot and we hope that this new tool will help GPs identify patients most at risk of having ovarian cancer for early referral and investigations."
Ovarian cancer is the seventh most common cancer in women worldwide and affects around 6,700 women in the UK every year, one of the highest rates in Europe. Most women are diagnosed when the disease is already at an advanced stage, meaning that in many cases their chances of surviving for five years after diagnosis can be as low as six per cent.
Less than one-third of women are diagnosed in the first stages of the disease but of those 90 per cent will survive to five years, showing that earlier diagnosis and treatment can have a dramatic impact on the patient's chances of survival.
However, GPs are faced with the tough challenge of making a correct diagnosis as early as possible for a disease which has few established risk factors and a range of non-specific symptoms such as loss of appetite, weight loss and abdominal pain which could also point to a number
|Contact: Emma Thorne|
University of Nottingham