Effect of Issuing an Invitation for Breast Cancer Screening to Women Aged 65 to 69

1996 ◽  
Vol 3 (2) ◽  
pp. 88-89 ◽  
Author(s):  
P J Hendry ◽  
C Entwistle
Keyword(s):  
Breast Cancer ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Cancer Detection ◽  
Screening Programme ◽  
Age Group ◽  
Breast Screening Programme ◽  
The United Kingdom ◽  
General Practices ◽  
National Health Service Breast

Objective –Breast cancer screening is available to all women over 50 in the United Kingdom on the National Health Service breast screening programme. Only women aged between 50 and 64 receive a written invitation, with women over 64 being expected to self refer. Unfortunately, despite the higher incidence of breast cancer in the older age group only a very small proportion of women over 64 attend for screening. The aim of the study was to test the hypothesis that women between the ages of 65 and 69 will attend for screening if invited. Method –Women aged 65 to 69 were invited for screening from general practices in the Inverness area and were treated in all respects as the usual screening age group. Results –An uptake of 76% was achieved with a cancer detection rate of 9.3 per thousand. Conclusion –These results lend weight to the suggestion that women in this age group should receive a specific invitation for breast cancer screening.

scholarly journals Repeated mammographic screening reduces breast cancer mortality along the continuum of age

2002 ◽  
Vol 9 (4) ◽  
pp. 163-167 ◽  
Author(s):  
M.J.M. Broeders ◽  
A.L.M. Verbeek ◽  
H. Straatman ◽  
P.G.M. Peer ◽  
P.C.M. Pasker-de Jong ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Cancer Mortality ◽  
Screening Programme ◽  
Breast Cancer Mortality ◽  
Mammographic Screening ◽  
Protective Effects ◽  
Age Group ◽  
The Continuum

OBJECTIVE: The optimal age boundaries for breast cancer screening are still under debate. A case-referent design was used to describe the effect of mammographic screening on breast cancer mortality along the continuum of age, based on a 20 year follow up period. SETTING: The population based breast cancer screening programme in Nijmegen, The Netherlands, which has biennially invited women over 35 years since 1975. METHODS: Cases, defined as women who died from primary breast cancer between 1987 and 1997, were selected from the group of women who received at least one invitation to the screening programme. For 157 cases, 785 women from the same group were selected as referents. Information on the index screening (the screening examination preceding diagnosis of the case) was collected for both cases and referents. The risk of dying from breast cancer was calculated per 10 year moving age group for women who had attended the index screening versus those who had not. RESULTS: The youngest 10 year age group showing an effect in our study were women aged 45–54 at their index screening. Breast cancer mortality for women in this group who attended the index screening was 32% lower, although not significant, than for women who did not (odds ratio (OR) 0.68, 95% confidence interval (95% CI) 0.33 to 1.41). This reduction in risk was not explained solely by an effect in women over 50 because the OR in women aged 45–49 was 0.56 (95% CI 0.20 to 1.61). Reductions in mortality became smaller with increasing age. Nevertheless, for women over 60 at index screening, participation in screening over a maximum 4 year period before diagnosis of the case yielded protective effects at least up to an age around 80. CONCLUSIONS: Although our results are based on a relatively small number of cases, they suggest that even in a programme with a 2 year screening interval there may be a benefit of starting screening around age 45. Also older women who participate at least once every 4 years still have much to gain from screening.

scholarly journals Artificial intelligence (AI) to enhance breast cancer screening: protocol for population-based cohort study of cancer detection

BMJ Open ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. e054005
Author(s):  
M Luke Marinovich ◽  
Elizabeth Wylie ◽  
William Lotter ◽  
Alison Pearce ◽  
Stacy M Carter ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Artificial Intelligence ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Cancer Detection ◽  
Screening Programme ◽  
Ethics Committee ◽  
Population Screening ◽  
Interval Cancers ◽  
Double Reading

IntroductionArtificial intelligence (AI) algorithms for interpreting mammograms have the potential to improve the effectiveness of population breast cancer screening programmes if they can detect cancers, including interval cancers, without contributing substantially to overdiagnosis. Studies suggesting that AI has comparable or greater accuracy than radiologists commonly employ ‘enriched’ datasets in which cancer prevalence is higher than in population screening. Routine screening outcome metrics (cancer detection and recall rates) cannot be estimated from these datasets, and accuracy estimates may be subject to spectrum bias which limits generalisabilty to real-world screening. We aim to address these limitations by comparing the accuracy of AI and radiologists in a cohort of consecutive of women attending a real-world population breast cancer screening programme.Methods and analysisA retrospective, consecutive cohort of digital mammography screens from 109 000 distinct women was assembled from BreastScreen WA (BSWA), Western Australia’s biennial population screening programme, from November 2016 to December 2017. The cohort includes 761 screen-detected and 235 interval cancers. Descriptive characteristics and results of radiologist double-reading will be extracted from BSWA outcomes data collection. Mammograms will be reinterpreted by a commercial AI algorithm (DeepHealth). AI accuracy will be compared with that of radiologist single-reading based on the difference in the area under the receiver operating characteristic curve. Cancer detection and recall rates for combined AI–radiologist reading will be estimated by pairing the first radiologist read per screen with the AI algorithm, and compared with estimates for radiologist double-reading.Ethics and disseminationThis study has ethical approval from the Women and Newborn Health Service Ethics Committee (EC00350) and the Curtin University Human Research Ethics Committee (HRE2020-0316). Findings will be published in peer-reviewed journals and presented at national and international conferences. Results will also be disseminated to stakeholders in Australian breast cancer screening programmes and policy makers in population screening.

Sign in / Sign up

Export Citation Format

Share Document