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NCRI 2017: Big data analysis predicts risk of radiotherapy effects 30 de Noviembre del 2017

Researchers at The Institute of Cancer Research, London, have, for the first time, applied big data analytics to information from more than 700 men given radiotherapy to treat their prostate cancer. This included medical history, genetics, radiotherapy dose, and reported side effects.
Advances in technology allow huge amounts of different information to be combined and analysed at once. This technique is already used in many different settings, including to improve the accuracy of weather forecasts, make investments and trading decisions, and even monitor premature babies.
State-of-the-art artificial intelligence
Researchers in this study used state-of-the-art artificial intelligence to highlight which information might predict sensitivity to the side effects of prostate radiotherapy. In particular, specific genetic characteristics SNPs (single nucleotide polymorphisms) were predictive of a patient suffering rectal bleeding.
At the moment there is no way to adjust doses of radiotherapy according to how sensitive a patient might be to the side effects. This means that while some men are receiving too much and suffering side effects, some are given too little and this compromises the chances of successful treatment.
Side effects include bowel, urinary and sexual dysfunction and can be difficult for patients to tolerate and can persist after treatment.
The researchers suggest that with further validation, this information could be used to create personalised treatment plans for prostate cancer patients. The technique could also be applied to many other types of cancer that are treated with radiotherapy.



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