Gaba, Faiza; Blyuss, Oleg; Liu, Xinting; Goyal, Shivam; Lahoti, Nishant; Chandrasekaran, Dhivya; Kurzer, Margarida; Kalsi, Jatinderpal; Sanderson, Saskia; Lanceley, Anne; +16 more... Ahmed, Munaza; Side, Lucy; Gentry-Maharaj, Aleksandra; Wallis, Yvonne; Wallace, Andrew; Waller, Jo; Luccarini, Craig; Yang, Xin; Dennis, Joe; Dunning, Alison; Lee, Andrew; Antoniou, Antonis C; Legood, Rosa; Menon, Usha; Jacobs, Ian; Manchanda, Ranjit; (2020) Population Study of Ovarian Cancer Risk Prediction for Targeted Screening and Prevention. Cancers, 12 (5). p. 1241. ISSN 2072-6694 DOI: https://doi.org/10.3390/cancers12051241
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Abstract
UNLABELLED: Unselected population-based personalised ovarian cancer (OC) risk assessment combining genetic/epidemiology/hormonal data has not previously been undertaken. We aimed to perform a feasibility study of OC risk stratification of general population women using a personalised OC risk tool followed by risk management. Volunteers were recruited through London primary care networks. INCLUSION CRITERIA: women ≥18 years. EXCLUSION CRITERIA: prior ovarian/tubal/peritoneal cancer, previous genetic testing for OC genes. Participants accessed an online/web-based decision aid along with optional telephone helpline use. Consenting individuals completed risk assessment and underwent genetic testing (BRCA1/BRCA2/RAD51C/RAD51D/BRIP1, OC susceptibility single-nucleotide polymorphisms). A validated OC risk prediction algorithm provided a personalised OC risk estimate using genetic/lifestyle/hormonal OC risk factors. Population genetic testing (PGT)/OC risk stratification uptake/acceptability, satisfaction, decision aid/telephone helpline use, psychological health and quality of life were assessed using validated/customised questionnaires over six months. Linear-mixed models/contrast tests analysed impact on study outcomes. MAIN OUTCOMES: feasibility/acceptability, uptake, decision aid/telephone helpline use, satisfaction/regret, and impact on psychological health/quality of life. In total, 123 volunteers (mean age = 48.5 (SD = 15.4) years) used the decision aid, 105 (85%) consented. None fulfilled NHS genetic testing clinical criteria. OC risk stratification revealed 1/103 at ≥10% (high), 0/103 at ≥5%-<10% (intermediate), and 100/103 at <5% (low) lifetime OC risk. Decision aid satisfaction was 92.2%. The telephone helpline use rate was 13% and the questionnaire response rate at six months was 75%. Contrast tests indicated that overall depression (p = 0.30), anxiety (p = 0.10), quality-of-life (p = 0.99), and distress (p = 0.25) levels did not jointly change, while OC worry (p = 0.021) and general cancer risk perception (p = 0.015) decreased over six months. In total, 85.5-98.7% were satisfied with their decision. Findings suggest population-based personalised OC risk stratification is feasible and acceptable, has high satisfaction, reduces cancer worry/risk perception, and does not negatively impact psychological health/quality of life.
Item Type | Article |
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Faculty and Department | Faculty of Public Health and Policy > Dept of Health Services Research and Policy |
Research Centre | Centre for the Mathematical Modelling of Infectious Diseases |
PubMed ID | 32429029 |
Elements ID | 147825 |
Official URL | http://dx.doi.org/10.3390/cancers12051241 |
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