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Unselected Population Genetic Testing for Personalised Ovarian Cancer Risk Prediction: A Qualitative Study Using Semi-Structured Interviews

Unselected population-based personalised ovarian cancer (OC) risk assessments combining genetic, epidemiological and hormonal data have not previously been undertaken. We aimed to understand the attitudes, experiences and impact on the emotional well-being of women from the general population who un...

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Autores principales: Gaba, Faiza, Oxley, Samuel, Liu, Xinting, Yang, Xin, Chandrasekaran, Dhivya, Kalsi, Jatinderpal, Antoniou, Antonis, Side, Lucy, Sanderson, Saskia, Waller, Jo, Ahmed, Munaza, Wallace, Andrew, Wallis, Yvonne, Menon, Usha, Jacobs, Ian, Legood, Rosa, Marks, Dalya, Manchanda, Ranjit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9139231/
https://www.ncbi.nlm.nih.gov/pubmed/35626184
http://dx.doi.org/10.3390/diagnostics12051028
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author Gaba, Faiza
Oxley, Samuel
Liu, Xinting
Yang, Xin
Chandrasekaran, Dhivya
Kalsi, Jatinderpal
Antoniou, Antonis
Side, Lucy
Sanderson, Saskia
Waller, Jo
Ahmed, Munaza
Wallace, Andrew
Wallis, Yvonne
Menon, Usha
Jacobs, Ian
Legood, Rosa
Marks, Dalya
Manchanda, Ranjit
author_facet Gaba, Faiza
Oxley, Samuel
Liu, Xinting
Yang, Xin
Chandrasekaran, Dhivya
Kalsi, Jatinderpal
Antoniou, Antonis
Side, Lucy
Sanderson, Saskia
Waller, Jo
Ahmed, Munaza
Wallace, Andrew
Wallis, Yvonne
Menon, Usha
Jacobs, Ian
Legood, Rosa
Marks, Dalya
Manchanda, Ranjit
author_sort Gaba, Faiza
collection PubMed
description Unselected population-based personalised ovarian cancer (OC) risk assessments combining genetic, epidemiological and hormonal data have not previously been undertaken. We aimed to understand the attitudes, experiences and impact on the emotional well-being of women from the general population who underwent unselected population genetic testing (PGT) for personalised OC risk prediction and who received low-risk (<5% lifetime risk) results. This qualitative study was set within recruitment to a pilot PGT study using an OC risk tool and telephone helpline. OC-unaffected women ≥ 18 years and with no prior OC gene testing were ascertained through primary care in London. In-depth, semi-structured and 1:1 interviews were conducted until informational saturation was reached following nine interviews. Six interconnected themes emerged: health beliefs; decision making; factors influencing acceptability; effect on well-being; results communication; satisfaction. Satisfaction with testing was high and none expressed regret. All felt the telephone helpline was helpful and should remain optional. Delivery of low-risk results reduced anxiety. However, care must be taken to emphasise that low risk does not equal no risk. The main facilitators were ease of testing, learning about children’s risk and a desire to prevent disease. Barriers included change in family dynamics, insurance, stigmatisation and personality traits associated with stress/worry. PGT for personalised OC risk prediction in women in the general population had high acceptability/satisfaction and reduced anxiety in low-risk individuals. Facilitators/barriers observed were similar to those reported with genetic testing from high-risk cancer clinics and unselected PGT in the Jewish population.
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spelling pubmed-91392312022-05-28 Unselected Population Genetic Testing for Personalised Ovarian Cancer Risk Prediction: A Qualitative Study Using Semi-Structured Interviews Gaba, Faiza Oxley, Samuel Liu, Xinting Yang, Xin Chandrasekaran, Dhivya Kalsi, Jatinderpal Antoniou, Antonis Side, Lucy Sanderson, Saskia Waller, Jo Ahmed, Munaza Wallace, Andrew Wallis, Yvonne Menon, Usha Jacobs, Ian Legood, Rosa Marks, Dalya Manchanda, Ranjit Diagnostics (Basel) Article Unselected population-based personalised ovarian cancer (OC) risk assessments combining genetic, epidemiological and hormonal data have not previously been undertaken. We aimed to understand the attitudes, experiences and impact on the emotional well-being of women from the general population who underwent unselected population genetic testing (PGT) for personalised OC risk prediction and who received low-risk (<5% lifetime risk) results. This qualitative study was set within recruitment to a pilot PGT study using an OC risk tool and telephone helpline. OC-unaffected women ≥ 18 years and with no prior OC gene testing were ascertained through primary care in London. In-depth, semi-structured and 1:1 interviews were conducted until informational saturation was reached following nine interviews. Six interconnected themes emerged: health beliefs; decision making; factors influencing acceptability; effect on well-being; results communication; satisfaction. Satisfaction with testing was high and none expressed regret. All felt the telephone helpline was helpful and should remain optional. Delivery of low-risk results reduced anxiety. However, care must be taken to emphasise that low risk does not equal no risk. The main facilitators were ease of testing, learning about children’s risk and a desire to prevent disease. Barriers included change in family dynamics, insurance, stigmatisation and personality traits associated with stress/worry. PGT for personalised OC risk prediction in women in the general population had high acceptability/satisfaction and reduced anxiety in low-risk individuals. Facilitators/barriers observed were similar to those reported with genetic testing from high-risk cancer clinics and unselected PGT in the Jewish population. MDPI 2022-04-19 /pmc/articles/PMC9139231/ /pubmed/35626184 http://dx.doi.org/10.3390/diagnostics12051028 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gaba, Faiza
Oxley, Samuel
Liu, Xinting
Yang, Xin
Chandrasekaran, Dhivya
Kalsi, Jatinderpal
Antoniou, Antonis
Side, Lucy
Sanderson, Saskia
Waller, Jo
Ahmed, Munaza
Wallace, Andrew
Wallis, Yvonne
Menon, Usha
Jacobs, Ian
Legood, Rosa
Marks, Dalya
Manchanda, Ranjit
Unselected Population Genetic Testing for Personalised Ovarian Cancer Risk Prediction: A Qualitative Study Using Semi-Structured Interviews
title Unselected Population Genetic Testing for Personalised Ovarian Cancer Risk Prediction: A Qualitative Study Using Semi-Structured Interviews
title_full Unselected Population Genetic Testing for Personalised Ovarian Cancer Risk Prediction: A Qualitative Study Using Semi-Structured Interviews
title_fullStr Unselected Population Genetic Testing for Personalised Ovarian Cancer Risk Prediction: A Qualitative Study Using Semi-Structured Interviews
title_full_unstemmed Unselected Population Genetic Testing for Personalised Ovarian Cancer Risk Prediction: A Qualitative Study Using Semi-Structured Interviews
title_short Unselected Population Genetic Testing for Personalised Ovarian Cancer Risk Prediction: A Qualitative Study Using Semi-Structured Interviews
title_sort unselected population genetic testing for personalised ovarian cancer risk prediction: a qualitative study using semi-structured interviews
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9139231/
https://www.ncbi.nlm.nih.gov/pubmed/35626184
http://dx.doi.org/10.3390/diagnostics12051028
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