domingo, 7 de agosto de 2016

Genetic testing and personalized ovarian cancer screening: a survey of public attitudes. - PubMed - NCBI

Genetic testing and personalized ovarian cancer screening: a survey of public attitudes. - PubMed - NCBI



 2016 Jul 26;16(1):46. doi: 10.1186/s12905-016-0325-3.

Genetic testing and personalized ovarian cancer screening: a survey of public attitudes.

Abstract

BACKGROUND:

Advances in genetic technologies are expected to make population-wide genetic testing feasible. This could provide a basis for risk stratified cancer screening; but acceptability in the target populations has not been explored.

METHODS:

We assessed attitudes to risk-stratified ovarian cancer (OC) screening based on prior genetic risk assessment using a survey design. Home-based interviews were carried out by the UK Office of National Statistics in a population-based sample of 1095 women aged 18-74. Demographic and personal correlates of attitudes to risk-stratified OC screening based on prior genetic risk assessment were determined using univariate analyses and adjusted logistic regression models.

RESULTS:

Full data on the key analytic questions were available for 829 respondents (mean age 46 years; 27 % 'university educated'; 93 % 'White'). Relatively few respondents felt they were at 'higher' or 'much higher' risk of OC than other women of their age group (7.4 %, n = 61). Most women (85 %) said they would 'probably' or 'definitely' take up OC genetic testing; which increased to 88 % if the test also informed about breast cancer risk. Almost all women (92 %) thought they would 'probably' or 'definitely' participate in risk-stratified OC screening. In multivariate logistic regression models, university level education was associated with lower anticipated uptake of genetic testing (p = 0.009), but with more positive attitudes toward risk-stratified screening (p <0.001). Perceived risk was not significantly associated with any of the outcome variables.

CONCLUSIONS:

These findings give confidence in taking forward research on integration of novel genomic technologies into mainstream healthcare.

KEYWORDS:

Breast cancer; Implementation; Ovarian cancer; Predictive genetic testing; Risk; Stratification

PMID:
 
27460568
 
PMCID:
 
PMC4962369
 
DOI:
 
10.1186/s12905-016-0325-3

[PubMed - in process] 
Free PMC Article

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