Online search data could be used to detect gynaecological cancer earlier

The study, published in BMC Public Health, identified differences in online search data between people with a benign gynaecological condition and those with a gynaecological cancer, and ovarian cancer in particular.

Ovarian cancer is the most lethal gynaecological cancer and the sixth most common in the UK, with around 7,400 diagnoses and more than 4,000 deaths each year from the disease. There is currently no screening programme in place for early disease detection.

In this study, the researchers analysed patients’ Google search engine data and found that there was a difference in search patterns as early as 360 days in advance of a GP referral for gynaecological cancer. This proved to be a likely indication of disease at around 60 days prior to a GP referral.

Different symptom patterns were also noted between the benign and cancer groups. For example, a spike in online searches for urinary symptoms was noted 140 days in advance of GP referral, whereas searches for bloating and pelvic pain symptoms appeared to present later at 70 days in advance, compared to the benign group.

It is hoped that larger studies will confirm whether search engine data can be used as an early disease detection tool to help speed up diagnoses for gynaecological cancer.

Dr Srdjan Saso, senior author of the study and a gynaecological cancer surgeon from Imperial’s Department of Metabolism, Digestion and Reproduction, said: “Ovarian cancer is one of the most lethal cancers for women, with advanced stage carrying a poor prognosis, despite potential extensive surgery. The focus, therefore, remains on facilitating early disease detection. However, we do not have a screening programme in place to enable this.

“Our research, in collaboration with computer scientists from UCL and Microsoft led by Professor Ingemar Cox and Dr Elad Yom-Tov respectively, has shown that online search data may be used to differentiate between women with malignant and benign gynaecological conditions. This suggests that it may be possible to build early detection tools using the internet which can identify women who may be at a higher risk of, in particular, ovarian cancers.

“We are hoping to raise funding in the near future to develop a multi-centre study which can confirm these findings in a much larger cohort.”

A previous study led by Imperial researchers showed that loyalty card data could be used to identify ovarian cancer cases earlier. However, this new study uses data from internet search engines which are used by a much larger proportion of the population, both in the UK and globally.

Dr Jennifer F Barcroft, lead author for the study, from Imperial’s Department of Metabolism, Digestion and Reproduction, said: “Our results show that it is possible to use search engine data to understand how conditions present, and that this may have use in early disease detection, given we have highlighted different symptom patterns between those with benign conditions and gynaecological cancers.

“As nearly 98 per cent of people in the UK have access to the internet, it is increasingly being used for health purposes. Online search data offers enormous potential within health and disease screening, given the widespread use of the internet worldwide. We hope that our research will drive interest in this novel area of research.”

Professor Ingemar Cox, senior author for the study from UCL Computer Science, said: “Our current paper significantly expands on earlier work by incorporating a clinical study that confirms that individual's risk of some diseases can be determined based on their web search behaviour. Web searches may therefore offer a simple, inexpensive method for disease screening. Of course, this does raise important ethical and privacy concerns, which need to be resolved.”

Informed written consent was obtained from participants in the study to use online search.

Links

• Professor Ingemar Cox’s academic profile
• UCL Computer Science
• UCL Engineering

Image

•  Credit: bigtunaonline on iStock.

Media contact 

Matt Midgley

E: m.midgley [at] ucl.ac.uk