Population Study of Ovarian Cancer Risk Prediction for Targeted Screening and Prevention

• Published in: Cancers Vol. 12; no. 5; p. 1241
• Main Authors: Gaba, Faiza, Blyuss, Oleg, Liu, Xinting, Goyal, Shivam, Lahoti, Nishant, Chandrasekaran, Dhivya, Kurzer, Margarida, Kalsi, Jatinderpal, Sanderson, Saskia, Lanceley, Anne, 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
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 15.05.2020; MDPI
• Subjects: Anxiety; BRCA1 protein; BRCA2 protein; Decision making; Epidemiology; Feasibility studies; Genetic screening; Ovarian cancer; Perception; Perceptions; Peritoneum; Population; Population genetics; Population studies; Prevention; Quality of life; Questionnaires; Risk assessment; Risk factors; Single-nucleotide polymorphism; Womens health; United Kingdom > UK; BRIP1; RAD51D; RAD51C; risk stratification; SNP; risk modelling; population genetic testing; BRCA1; BRCA2; ovarian cancer risk
• ISSN: 2072-6694; 2072-6694
• DOI: 10.3390/cancers12051241

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. women ≥18 years. 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 ( , 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. 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 ( = 0.30), anxiety ( = 0.10), quality-of-life ( = 0.99), and distress ( = 0.25) levels did not jointly change, while OC worry ( = 0.021) and general cancer risk perception ( = 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.