Dataset Information

Mammography screening reduces rates of advanced and fatal breast cancers: Results in 549,091 women.

ABSTRACT:

Background

It is of paramount importance to evaluate the impact of participation in organized mammography service screening independently from changes in breast cancer treatment. This can be done by measuring the incidence of fatal breast cancer, which is based on the date of diagnosis and not on the date of death.

Methods

Among 549,091 women, covering approximately 30% of the Swedish screening-eligible population, the authors calculated the incidence rates of 2473 breast cancers that were fatal within 10 years after diagnosis and the incidence rates of 9737 advanced breast cancers. Data regarding each breast cancer diagnosis and the cause and date of death of each breast cancer case were gathered from national Swedish registries. Tumor characteristics were collected from regional cancer centers. Aggregated data concerning invitation and participation were provided by Sectra Medical Systems AB. Incidence rates were analyzed using Poisson regression.

Results

Women who participated in mammography screening had a statistically significant 41% reduction in their risk of dying of breast cancer within 10 years (relative risk, 0.59; 95% CI, 0.51-0.68 [P < .001]) and a 25% reduction in the rate of advanced breast cancers (relative risk, 0.75; 95% CI, 0.66-0.84 [P < .001]).

Conclusions

Substantial reductions in the incidence rate of breast cancers that were fatal within 10 years after diagnosis and in the advanced breast cancer rate were found in this contemporaneous comparison of women participating versus those not participating in screening. These benefits appeared to be independent of recent changes in treatment regimens.

SUBMITTER: Duffy SW

PROVIDER: S-EPMC7318598 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Publications

Mammography screening reduces rates of advanced and fatal breast cancers: Results in 549,091 women.

Duffy Stephen W SW Tabár László L Yen Amy Ming-Fang AM Dean Peter B PB Smith Robert A RA Jonsson Håkan H Törnberg Sven S Chen Sam Li-Sheng SL Chiu Sherry Yueh-Hsia SY Fann Jean Ching-Yuan JC Ku May Mei-Sheng MM Wu Wendy Yi-Ying WY Hsu Chen-Yang CY Chen Yu-Ching YC Svane Gunilla G Azavedo Edward E Grundström Helene H Sundén Per P Leifland Karin K Frodis Ewa E Ramos Joakim J Epstein Birgitta B Åkerlund Anders A Sundbom Ann A Bordás Pál P Wallin Hans H Starck Leena L Björkgren Annika A Carlson Stina S Fredriksson Irma I Ahlgren Johan J Öhman Daniel D Holmberg Lars L Chen Tony Hsiu-Hsi TH

Cancer 20200511 13

<h4>Background</h4>It is of paramount importance to evaluate the impact of participation in organized mammography service screening independently from changes in breast cancer treatment. This can be done by measuring the incidence of fatal breast cancer, which is based on the date of diagnosis and not on the date of death.<h4>Methods</h4>Among 549,091 women, covering approximately 30% of the Swedish screening-eligible population, the authors calculated the incidence rates of 2473 breast cancers ...[more]

PMID: 32390151

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Project description:PurposeTimely mammography to screen for breast cancer in accordance with the United States Preventive Services Task Force (USPSTF) recommendations can reduce morbidity and mortality substantially. This study assessed whether the odds of undergoing screening mammography are similar for women with and without visual impairment (VI).DesignRetrospective, longitudinal cohort study.ParticipantsWomen aged 65 to 72 years enrolled in fee-for-service Medicare from January 1, 2008, through December 31, 2015.MethodsPatients with no vision loss (NVL), partial vision loss (PVL), and severe vision loss (SVL) were matched 1:1:1 based on age, race, time in Medicare, urbanicity of residence, and overall health. Women with pre-existing breast cancer were excluded. Multivariable conditional logistic regression modeling compared the odds of undergoing screening mammography within a 2-year follow-up period among the 3 groups.Main outcomes measuresProportion of participants undergoing mammography and adjusted odds ratios (ORs) of undergoing mammography within 2 years of follow-up.ResultsA total of 1044 patients were matched (348 in each group). The mean ± standard deviation age at the index date was 69.0 ± 1.5 years for all 3 groups. The proportion of women undergoing 1 mammography screening or more within the 2-year follow-up was 69.0% (n = 240), 56.9% (n = 198), and 56.0% (n = 195) for the NVL, PVL, and SVL groups, respectively (P = 0.0005). The mean ± standard deviation number of mammography screenings undergone per patient during the 5-year period (3-year look-back plus 2-year follow-up) was 3.1 ± 2.0, 2.5 ± 2.0, and 2.3 ± 2.1 for the NVL, PVL, and SVL groups, respectively (P < 0.0001). Women with SVL had 42% decreased odds (OR, 0.58; 95% CI, 0.37-0.90; P = 0.01), and those with PVL had 44% decreased odds (OR, 0.56; CI, 0.36-0.87; P = 0.009) of undergoing mammography during follow-up compared with those with NVL.ConclusionsWomen with VI were significantly less likely to undergo mammography screening for breast cancer than women without VI. Clinicians should look for ways to help ensure that patients with VI undergo mammography and other preventive screenings as recommended by the USPSTF.

Project description:Despite recent advances in artificial intelligence (AI) software with improved performance in mammography screening for breast cancer, insufficient data are available on its performance in detecting cancers that were initially missed on mammography. In this study, we aimed to determine whether AI software-aided mammography could provide additional value in identifying cancers detected through supplemental screening ultrasound. We searched our database from 2017 to 2018 and included 238 asymptomatic patients (median age, 50 years; interquartile range, 45-57 years) diagnosed with breast cancer using supplemental ultrasound. Two unblinded radiologists retrospectively reviewed the mammograms using commercially available AI software and identified the reasons for missed detection. Clinicopathological characteristics of AI-detected and AI-undetected cancers were compared using univariate and multivariate logistic regression analyses. A total of 253 cancers were detected in 238 patients using ultrasound. In an unblinded review, the AI software failed to detect 187 of the 253 (73.9%) mammography cases with negative findings in retrospective observations. The AI software detected 66 cancers (26.1%), of which 42 (63.6%) exhibited indiscernible findings obscured by overlapping dense breast tissues, even with the knowledge of magnetic resonance imaging and post-wire localization mammography. The remaining 24 cases (36.4%) were considered interpretive errors by the radiologists. Invasive tumor size was associated with AI detection after multivariable analysis (odds ratio, 2.2; 95% confidence intervals, 1.5-3.3; p < 0.001). In the control group of 160 women without cancer, the AI software identified 19 false positives (11.9%, 19/160). Although most ultrasound-detected cancers were not detected on mammography with the use of AI, the software proved valuable in identifying breast cancers with indiscernible abnormalities or those that clinicians may have overlooked.

Project description:ContextScreening ultrasound may depict small, node-negative breast cancers not seen on mammography.ObjectiveTo compare the diagnostic yield, defined as the proportion of women with positive screen test results and positive reference standard, and performance of screening with ultrasound plus mammography vs mammography alone in women at elevated risk of breast cancer.Design, setting, and participantsFrom April 2004 to February 2006, 2809 women, with at least heterogeneously dense breast tissue in at least 1 quadrant, were recruited from 21 sites to undergo mammographic and physician-performed ultrasonographic examinations in randomized order by a radiologist masked to the other examination results. Reference standard was defined as a combination of pathology and 12-month follow-up and was available for 2637 (96.8%) of the 2725 eligible participants.Main outcome measuresDiagnostic yield, sensitivity, specificity, and diagnostic accuracy (assessed by the area under the receiver operating characteristic curve) of combined mammography plus ultrasound vs mammography alone and the positive predictive value of biopsy recommendations for mammography plus ultrasound vs mammography alone.ResultsForty participants (41 breasts) were diagnosed with cancer: 8 suspicious on both ultrasound and mammography, 12 on ultrasound alone, 12 on mammography alone, and 8 participants (9 breasts) on neither. The diagnostic yield for mammography was 7.6 per 1000 women screened (20 of 2637) and increased to 11.8 per 1000 (31 of 2637) for combined mammography plus ultrasound; the supplemental yield was 4.2 per 1000 women screened (95% confidence interval [CI], 1.1-7.2 per 1000; P = .003 that supplemental yield is 0). The diagnostic accuracy for mammography was 0.78 (95% CI, 0.67-0.87) and increased to 0.91 (95% CI, 0.84-0.96) for mammography plus ultrasound (P = .003 that difference is 0). Of 12 supplemental cancers detected by ultrasound alone, 11 (92%) were invasive with a median size of 10 mm (range, 5-40 mm; mean [SE], 12.6 [3.0] mm) and 8 of the 9 lesions (89%) reported had negative nodes. The positive predictive value of biopsy recommendation after full diagnostic workup was 19 of 84 for mammography (22.6%; 95% CI, 14.2%-33%), 21 of 235 for ultrasound (8.9%, 95% CI, 5.6%-13.3%), and 31 of 276 for combined mammography plus ultrasound (11.2%; 95% CI. 7.8%-15.6%).ConclusionsAdding a single screening ultrasound to mammography will yield an additional 1.1 to 7.2 cancers per 1000 high-risk women, but it will also substantially increase the number of false positives.Trial registrationclinicaltrials.gov Identifier: NCT00072501.

Dataset Information

Mammography screening reduces rates of advanced and fatal breast cancers: Results in 549,091 women.

Background

Methods

Results

Conclusions

Publications

Mammography screening reduces rates of advanced and fatal breast cancers: Results in 549,091 women.

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