TY - JOUR
T1 - Population Study of Ovarian Cancer Risk Prediction for Targeted Screening and Prevention
AU - Gaba, Faiza
AU - Blyuss, Oleg
AU - Liu, Xinting
AU - Goyal, Shivam
AU - Lahoti, Nishant
AU - Chandrasekaran, Dhivya
AU - Kurzer, Margarida
AU - Kalsi, Jatinderpal
AU - Sanderson, Saskia
AU - Lanceley, Anne
AU - Ahmed, Munaza
AU - Side, Lucy
AU - Gentry-Maharaj, Aleksandra
AU - Wallis, Yvonne
AU - Wallace, Andrew
AU - Waller, Jo
AU - Luccarini, Craig
AU - Yang, Xin
AU - Dennis, Joe
AU - Dunning, Alison
AU - Lee, Andrew
AU - Antoniou, Antonis C.
AU - Legood, Rosa
AU - Menon, Usha
AU - Jacobs, Ian
AU - Manchanda, Ranjit
N1 - Funding: This study was funded by Cancer Research UK and The Eve-Appeal Charity (C16420/A18066). U.M. received support from the National Institute for Health Research University College London Hospitals Biomedical Research Centre. A.A. is supported by Cancer Research UK (grant number C12292/A20861).
The funding bodies had no role in the study design, data collection, analysis, interpretation or writing of the report or decision to submit for publication. The research team was independent of funders. Acknowledgments: This study is supported by researchers at the Cancer Research UK Barts Centre, Queen Mary
University of London (C16420/A18066). We are particularly grateful to the women who participated in this study. We are grateful to the entire medical, nursing, and administrative staff who work on the PROMISE Feasibility Study.
PY - 2020/5/15
Y1 - 2020/5/15
N2 - 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. View Full-Text
AB - 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. View Full-Text
KW - population genetic testing
KW - ovarian cancer risk
KW - risk stratification
KW - BRCA1
KW - BRCA2
KW - RAD51C
KW - RAD51D
KW - BRIP1
KW - SNP
KW - risk modelling
UR - https://www.mdpi.com/2072-6694/12/5/1241
U2 - 10.3390/cancers12051241
DO - 10.3390/cancers12051241
M3 - Article
VL - 12
JO - Cancers
JF - Cancers
SN - 2072-6694
IS - 5
M1 - 1241
ER -
