IANS | Toronto June 10, 2017 Last Updated at 15:42 IST

Using nanotechnology, scientists have developed a new diagnostic process that can identify aggressive prostate cancer from a single drop of blood with 40 per cent more accuracy than current screening methods.

The Extracellular Vesicle Fingerprint Predictive Score (EV-FPS) test uses machine learning to combine information from millions of cancer cell nano-particles in the blood to recognise the unique fingerprint of aggressive prostate cancer.

The diagnostic, evaluated in a group of men suspected of prostate cancer, correctly identified aggressive prostate cancer 40 per cent more accurately than the most common blood test -- Prostate-Specific Antigen (PSA) and helped them avoid unnecessary painful biopsies and over-treatment.

"Higher sensitivity means that our test will miss fewer aggressive cancers...for this kind of test you want the sensitivity to be as high as possible because you don't want to miss a single cancer that should be treated," said John Lewis from the University of Alberta in Canada.

Current tests such as the PSA and digital rectal exam (DRE) often lead to unneeded biopsies, the researchers said, while presenting the paper at the International Society for Extracellular Vesicles conference in Toronto recently.

More than 50 per cent of men who undergo biopsy do not have prostate cancer, yet suffer the pain and side effects of the procedure.

It is estimated that successful implementation of the EV-FPS test could eventually eliminate up to 600,000 unnecessary biopsies, 24,000 hospitalisations and up to 50 per cent of unnecessary treatments for prostate cancer each year in North America alone, Lewis said.

"Compared to elevated total PSA alone, the EV-FPS test can more accurately predict the result of prostate biopsy in previously unscreened men," added Adrian Fairey, Urologist from the University of Alberta.

--IANS

karthik/rt/nir/bg

(This story has not been edited by Business Standard staff and is auto-generated from a syndicated feed.)

Using nanotechnology, scientists have developed a new diagnostic process that can identify aggressive prostate cancer from a single drop of blood with 40 per cent more accuracy than current screening methods.

The Extracellular Vesicle Fingerprint Predictive Score (EV-FPS) test uses machine learning to combine information from millions of cancer cell nano-particles in the blood to recognise the unique fingerprint of aggressive prostate cancer.

The diagnostic, evaluated in a group of men suspected of prostate cancer, correctly identified aggressive prostate cancer 40 per cent more accurately than the most common blood test -- Prostate-Specific Antigen (PSA) and helped them avoid unnecessary painful biopsies and over-treatment.

"Higher sensitivity means that our test will miss fewer aggressive cancers...for this kind of test you want the sensitivity to be as high as possible because you don't want to miss a single cancer that should be treated," said John Lewis from the University of Alberta in Canada.

Current tests such as the PSA and digital rectal exam (DRE) often lead to unneeded biopsies, the researchers said, while presenting the paper at the International Society for Extracellular Vesicles conference in Toronto recently.

More than 50 per cent of men who undergo biopsy do not have prostate cancer, yet suffer the pain and side effects of the procedure.

It is estimated that successful implementation of the EV-FPS test could eventually eliminate up to 600,000 unnecessary biopsies, 24,000 hospitalisations and up to 50 per cent of unnecessary treatments for prostate cancer each year in North America alone, Lewis said.

"Compared to elevated total PSA alone, the EV-FPS test can more accurately predict the result of prostate biopsy in previously unscreened men," added Adrian Fairey, Urologist from the University of Alberta.

--IANS

karthik/rt/nir/bg

(This story has not been edited by Business Standard staff and is auto-generated from a syndicated feed.)

IANS

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Nanotech-based test can predict prostate cancer risk better ... - Business Standard