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Wolfson Institute of Preventive Medicine - Barts and The London

Personalised Ovarian Cancer Risk Prediction Reduces Cancer Worries

A study offering personalised ovarian cancer risk prediction to women in the general population shows that 98% of participants felt less worried after finding out their ovarian cancer risk status.

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In the feasibility study, led by Professor Ranjit Manchanda of the Wolfson Institute of Preventive Medicine, volunteers accessed an online/web-based decision aid, with consenting participants then completing risk assessment and genetic testing to receive a personalised risk estimate using genetic/lifestyle/hormonal ovarian cancer risk factors. None of the participants would routinely have been offered genetic testing on the NHS, as they did not fulfil current clinical testing criteria.

The study assessed ovarian cancer risk stratification uptake/acceptability, satisfaction, decision aid/telephone helpline use, psychological health, and quality of life, through questionnaires over six months. Ovarian cancer worry and general cancer risk perception decreased over the six months. The results suggest that population-based personalised ovarian cancer risk stratification is feasible and acceptable, has high satisfaction, reduces cancer worry/risk perception, and does not have a negative impact on psychological health/quality of life.

Identifying women at high risk for ovarian cancer currently relies on clinical criteria and family history-based testing for susceptibility genes, a policy that misses >50% of the gene carriers and represents enormous missed opportunities for risk-stratified prevention. Around 70% of ovarian cancer cases are currently diagnosed at stage 3 or 4, meaning that treatment is more radical and the outlook is poorer than for a stage 1 or 2 ovarian cancer, when the patient will have a much higher chance of survival.

Professor Manchanda commented: “Our findings support broadening genetic testing for ovarian cancer genes across the entire population, beyond just the current criteria-based approach, to better identify women at risk. This could prevent thousands more cancers than any current strategy, saving many lives.”


Population Study of Ovarian Cancer Risk Prediction for Targeted Screening and Prevention.  Cancers 202012(5), 1241