It's a little pill with big responsibilities. But despite its primary role to prevent pregnancy, the contraceptive pill (or 'the Pill') could also help reduce the risk of ovarian cancer , according to new research from the University of South Australia .
Screening for risk factors of ovarian cancer using artificial intelligence, UniSA researchers found that the oral contraceptive pill reduced the risk of ovarian cancer by 26% among women who had ever used the Pill, and by 43% for women who had used the Pill after the age of 45.
The study also identified some biomarkers associated with ovarian cancer risk, including several characteristics of red blood cells and certain liver enzymes in the blood, with lower body weight and shorter stature associating with a lower risk of ovarian cancer.
Researchers also found that women who had given birth to two or more children had a 39% reduced risk of developing ovarian cancer compared to those who had not had children.
Ahead of World Cancer Day on 4 February, the findings have potential to support early diagnosis of ovarian cancer.
In Australia, ovarian cancer is the tenth most common cancer in women and the sixth most common cause of death from cancer in women .
UniSA researcher Dr Amanda Lumsden says understanding risks and preventative factors for ovarian cancer is key for improved treatment and outcomes.
"Ovarian cancer is notoriously diagnosed at a late stage, with about 70% of cases only identified when they are significantly advanced ," Dr Lumsden says.
"Late detection contributes to a survival rate of less than 30% over five years, in comparison to more than 90% for ovarian cancers that are caught early . That's why it's so important to identify risk factors.
"In this research, we found that women who had used the oral contraceptive pill had a lower risk of ovarian cancer. And those who had last used the Pill in their mid-40s, had an even lower level of risk.
"This poses the question as to whether interventions that reduce the number of ovulations could be used as a potential target for prevention strategies for ovarian cancer."
Supported by the MRFF , the study used artificial intelligence to assess the data of 221,732 females (aged 37-73 at baseline) in the UK Biobank .
Machine learning specialist, UniSA's Dr Iqbal Madakkatel , says the study shows how artificial intelligence can help to identify risk factors that may otherwise have gone undetected.
"We included information from almost 3000 diverse characteristics related to health, medication use, diet and lifestyle, physical measures, metabolic, and hormonal factors, each measured at the start of the study," Dr Madakkatel says.
"It was particularly interesting that some blood measures – which were measured on average 12.6 years before diagnoses – were predictive of ovarian cancer risk, because it suggests we may be able to develop tests to identify women at risk at a very early stage."
Project Lead, Professor Elina Hyppönen, says that identifying risk factors for ovarian cancer could help to improve survival rates through prevention and earlier detection.
"It is exciting that our data-driven analyses have uncovered key risk factors for ovarian cancer that can be acted upon," Prof Hyppönen says.
"It is possible that by using the contraceptive pill to reduce ovulations or by reducing harmful adiposity, we may be able to lower to risk of ovarian cancer. But more research is needed to establish the best approaches to prevention, as well as the ways in which we can identify women most at risk."
