Sunday February 17, 2019

Regular Dose of Aspirin Reduces Risk of Ovarian Cancer

For this study, published in the journal JAMA Oncology, the team analysed data on more than 200,000 women among which 1,054 developed ovarian cancer

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Aspirin, Ovarian cancer
New ingestible, expanding pill to track ulcers, stomach cancer.

Taking a low-dose of aspirin daily may help women lower their risk of developing ovarian cancer by 23 per cent, suggests a new study.

Ovarian cancer is the most fatal gynaecological cancer, largely due to lack of early detection strategies and is believed that the inflammation that occurs during ovulation plays a role in the development of this cancer.

Aspirin is thought to lower cancer risk by reducing inflammation.

The findings, led by researchers from H. Lee Moffitt Cancer Centre and Research Institute in the US, showed that low-dose aspirin use was associated with a lower risk of ovarian cancer while standard-dose aspirin use increased the risk, their findings revealed.

Aspirin
Aspirin may lower risk of ovarian cancer. Pixabay

Conversely, women who took non-aspirin anti-inflammatory drugs (NSAIDs), such as ibuprofen (Advil) or naproxen (Aleve) — at least 10 tablets per week for many years, had an increased risk of developing the disease.

“We’re not quite at the stage where we could make the recommendation that daily aspirin use lowers ovarian cancer risk. We need to do more research. But it is definitely something women should discuss with their physician,” said Shelley Tworoger, Associate Centre Director from the varsity.

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For this study, published in the journal JAMA Oncology, the team analysed data on more than 200,000 women among which 1,054 developed ovarian cancer.

In addition, researchers looked at the participants’ use of aspirin (325 milligrams), low-dose aspirin (100 milligrams or less), non-aspirin NSAIDs and acetaminophen. (IANS)

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With Ovarian Cancer Deaths Set to Spike by 67%, AI to Rescue: Study

However, the scans cannot give clinicians detailed insight into patients’ likely overall outcomes or on the likely effect of a therapeutic intervention

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Cancer
Cancer Ribbon. Pixabay

With the incidence of ovarian cancer likely to increase by 55 per cent in another 15 years or so, researchers have created an artificial intelligence (AI) software to help best treat ovarian cancer that will pave the way for personalised medicine and expedite relief, a new study says.

The mathematical software tool — TEXLab — can also predict what treatment might be most effective for patients with the World Ovarian Cancer Coalition predicting that deaths will likely increase by 67 per cent by 2035 due to this particular cancer.

The technology can be used to identify patients who are unlikely to respond to standard treatments and offer alternatives as ovarian cancer is the sixth most common cancer in women in the UK that usually strikes after menopause or those with a family history of the disease.

Early detection of the disease could improve survival rates, the study noted.

“Long-term survival rate for patients with advanced ovarian cancer is poor despite advancements in treatments. There is an urgent need for new ways,” said lead author Eric Aboagye, Professor at Imperial College London.

For the study, researchers used the software to identify the aggressiveness of tumours in CT scans and tissue samples from 364 women with ovarian cancer.

The patients were then given a score known as Radiomic Prognostic Vector (RPV) which indicates how severe the disease is, ranging from mild to severe.

Cancer patient
Cancer patient.

The findings, published in Nature Communications, showed that the software was up to four times more accurate for predicting deaths from ovarian cancer than standard methods.

In addition, five per cent of patients with high RPV scores had a survival rate of less than two years, results showed.

High RPV was also associated with chemotherapy resistance and poor surgical outcomes, suggesting that RPV can be used as a potential bio-marker to predict how patients would respond to treatments.

“Our technology is able to give clinicians more detailed and accurate information on how the patients are likely to respond to different treatments, which could enable them to make better and more targeted treatment decisions,” said Aboagye.

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Doctors as of now diagnose ovarian cancer in a number of ways, including a blood test followed by a CT scan that uses X-rays and a computer to create detailed pictures of the ovarian tumour.

This helps clinicians know how far the disease has spread and determines the type of treatment patients receive, such as surgery and chemotherapy.

However, the scans cannot give clinicians detailed insight into patients’ likely overall outcomes or on the likely effect of a therapeutic intervention. (IANS)