Web tool aims to better inform and refine need for treatment in early prostate cancer

ScienceDaily | 3/12/2019 | Staff
HelloimMe (Posted by) Level 3
The tool, PREDICT Prostate, launches today to coincide with publication in the journal PLOS Medicine of the research that underpins it. It brings together the latest evidence and mathematical models to give a personalised prognosis, which the researchers say will empower patients as they discuss treatment options with their consultant.

According to Cancer Research UK, there were 47,151 new cases of prostate cancer in 2015. Progession of the disease, which usually presents in later life, is very variable: in most cases, the disease progresses slowly and is not fatal. It is often said that more men die with prostate cancer than from it. However, it is still the case that in a significant number of men, the tumour will metastasise and spread to other organs, threatening their health.

Patient - Prostate - Cancer - Risk - Patient

When a patient is diagnosed with prostate cancer, they are currently classified as low, intermediate or high risk. Depending on the patient's risk group, clinicians will recommend either an 'active monitoring' approach or treatment. Treatment options include radiotherapy or surgery and can have potentially significant side-effects, including erectile dysfunction and urinary incontinence.

However, evidence suggests that these classifications, which are in the current guidelines provided by the National Institute for Health and Care Excellence (NICE), are only 60-70% accurate. This means that many men may elect for treatment when it is not necessary. In fact, a recent study carried out in the UK showed that for early prostate cancer (low and intermediate risk), treatment is no more beneficial in terms of ten year survival compared to no treatment.

Cambridge - Researchers - Accuracy - Model - %

Cambridge researchers have already shown that it is possible to improve the accuracy of the NICE-endorsed model to more than 80% by stratifying patients into five rather than three groups. Their next challenge was to use this information to give a more individual prediction of outcome to patients...
(Excerpt) Read more at: ScienceDaily
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