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1.
Public Health ; 210: 65-73, 2022 Sep.
Article in English | MEDLINE | ID: mdl-35870323

ABSTRACT

OBJECTIVES: This study aims to evaluate the cancer detection rate in French National Breast Cancer Screening Program, especially the cancer detection rate during second reading session (Reading 2) based on digital technologies used in radiology centres. STUDY DESIGN: This was an analytical and descriptive study. METHODS: Cancer detection rate was estimated by the ratio between the number of cancers detected and the number of women screened. The positive predictive value (PPV) was estimated as cancer detection rate among abnormal Reading 2. The relationship between Reading 2's PPV and the predictive factors was evaluated using multilevel mixed-effects logistic regression. RESULTS: A total of 1,380,006 digital mammograms were retained in the analysis between 2010 and 2019. Cancer detection rate represented 7.8‰ at first reading session (Reading 1) and 0.5‰ at Reading 2. Cancer detection rate is significantly associated with the use of tomosynthesis (P < 0.001) at Reading 1, and differences appear within different tomosynthesis brands (P = 0.007). Reading 2's PPV differs significantly according on technologies used by first Reader (P < 0.004). Nevertheless, Reading 2 has 1.9 (1.5-2.4) more likely to predict a cancer with the presence of previous mammogram compared with those without previous images. CONCLUSION: Using tomosynthesis technology improves cancer detection rate at Reading 1, even if differences are noticeable between brands. Using tomosynthesis technology at Reading 1 reduces Reading 2's PPV and cancer detection rate at Reading 2.


Subject(s)
Breast Neoplasms , Early Detection of Cancer , Breast Neoplasms/diagnostic imaging , Early Detection of Cancer/methods , Female , Humans , Mammography , Mass Screening/methods , Predictive Value of Tests
2.
Public Health ; 202: 121-130, 2022 Jan.
Article in English | MEDLINE | ID: mdl-34952431

ABSTRACT

OBJECTIVE: Statistical modeling was already predicted the occurrence/prognosis of breast cancer from previous radiological findings. This study predicts the breast cancer risk by the age at discovery of mammographic abnormality in the French breast cancer screening program. STUDY DESIGN: This was a cohort study. METHODS: The study included 261,083 women who meet the inclusion criteria: aged 50-74 years, living in French departments (Ain, Doubs, Haute-Saône, Jura, Territoire-de-Belfort, and Yonne), with at least two mammograms between January 1999 and December 2017, of which the first was 'normal/benign'. The incidence of each abnormality (microcalcifications, spiculated mass, obscured mass, architectural distortion, and asymmetric density) was first estimated, then the breast cancer risk was predicted secondly according to the age at discovery of each mammographic abnormality, using an actuarial life table and a Cox model. RESULTS: Overall breast cancer (6326 cases) incidence was 3.3 (3.0; 3.1)/1000 person-years. The breast cancer incidence increased proportionally with the discovery age of the speculated mass and microcalcifications. The incidence was twice as high when the spiculated mass age of discovery was ≥70 (12.2 [10.4; 14.4]) compared with age 50-54 years (5.8 [5.1; 6.7]). Depending on the spiculated mass discovery age, the breast cancer risk increased by at least 40% between the age groups 55-59 years (1.4 [1.0; 1.8]) and ≥70 years (2.4 [1.9; 3.3]). Whatever the abnormality, the incidence of breast cancer was higher when it was present in only one breast. CONCLUSION: The study highlights a stable incidence of breast cancer between successive mammograms, an increased risk of breast cancer with the finding age of spiculated mass and microcalcifications. The reduced delay between the abnormality discovery date and the breast cancer diagnosis date would justify a specific follow-up protocol after the finding of these two abnormalities.


Subject(s)
Breast Neoplasms , Cohort Studies , Early Detection of Cancer , Female , Humans , Incidence , Mammography , Mass Screening , Middle Aged
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