Europe against Cancer breast cancer screening programme in France

Rénaud, R; Gairard, B.; Schaffer, Paul; Guldenfels, C; Haehnel, P; Dale, Gro Helen; Bellocq, J P

doi:10.1097/00008469-199401001-00003

Cited by 10 publications

(3 citation statements)

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“…e One or two views depending on breast density. source in all registers is the regional morphology registers (Renaud et al, 1994;McCann et al, 1997;Bray et al, 2002). Estimation of completeness for BC has in several of the registers been reported up to 98% (Mattsson and Wallgren, 1984;Ascunce et al, 1994;Barlow et al, 2009).…”

Section: Methodsmentioning

confidence: 99%

A pooled analysis of interval cancer rates in six European countries

Törnberg

Kemetli

Ascunce

et al. 2010

European Journal of Cancer Prevention

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The objective of this study was to assess detection rates and interval breast cancer (IC) rates from eight programmes in the European Breast Cancer Screening Network. A common data collection protocol was used to explore differences in IC rates among programmes and discuss their potential determinants. Pooled analysis was used to describe IC rates by age, compliance in screening, recall rate, screening detection (SD) rate and expected breast cancer incidence. Participation in screening averaged 77.9% (range 42.6-88.7%), recall rate 5.4% (range 3.3-17.7%) in the initial and 3.4% (range 1.8-8.9%) in the subsequent screening rounds, and SD rate was 60.4 (range 41.6-91) per 10 000 women in initial and 38.5 (range 31.3-62.6) in subsequent screens. IC rate during first 12 months after screening was 5.9 (range 2.1-7.3) per 10 000 women screened negative and 12.6 (range 6.3-15) in the second year of the interval. IC comprised 28% of the IC and SD cancers. The ratio between IC rate and expected incidence was 0.29 for the first 12 months and 0.63 for the 13-24 months period. Sensitivity was higher for the ages 60-69 years and for initial tests than subsequent tests. There were distinct differences in the IC rates between programmes. The results of this study reveal large variations in screening sensitivity and performance. Pooled evaluation of some process indicators within the European breast cancer screening programmes proved to be feasible and is likely to be useful for the future, particularly if it is performed regularly and extensively.

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Section: Methodsmentioning

confidence: 99%

A pooled analysis of interval cancer rates in six European countries

Törnberg

Kemetli

Ascunce

et al. 2010

European Journal of Cancer Prevention

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“…White et al [16] analyzed 2591 women aged 40 to 49 years, without hormone therapy, and classified 24% of breasts as type 4 during the first week of the cycle and 23% during the second week, while for weeks three and four the percentage was 28%, which is a significant variation (p = 0.04) regardless of body mass index (BMI). They used the BI-RADS (Breast Imaging-Reporting and Data System) classification to define breast typology: In addition, Renaud et al [17], in a European epidemiological study of a cohort of 40,293 women aged 50 to 67 years, highlighted the evolution of breast density with age, as shown in Table 2, with a higher propensity for dense breasts in younger women, and therefore a greater difficulty in detecting the presence of a tumor. A simple, non-operator-dependent method to quantify breast density could help to diagnose breast cancer as well as to qualify natural "noise" due to the variation in density during the menstrual cycle, which affects tumor detection.…”

Section: Classificationmentioning

confidence: 99%

Evaluation on Phantoms of the Feasibility of a Smart Bra to Detect Breast Cancer in Young Adults

Moreno¹,

Herrera²

2019

Sensors

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Breast cancer is the most common cancer observed in women. Although mammography is a recognized method, it remains ionizing and cannot be used routinely or in young adults, leaving up to two years between two diagnoses. Prior to validation on human subjects, this study aims to validate on phantoms the feasibility of quantifying breast density and detecting breast cancer tumors using a smart bra in young women. Six phantoms with various densities and seven phantoms with various volumes of modelized tumor were prepared and measured with a smart bra, including an electrophysiological module. There was a significant difference between the "healthy phantoms" and the "tumor phantoms" with P(Student) = 0.008 (Shapiro-Wilk p = 0.846, samples follow a normal distribution; Fisher variance test, p = 0.287). In addition, this study seems to indicate the possibility of discriminating various types of tumorous and healthy breast tissue using a smart bra, in high density breast. However, a new study on a large sample of human subjects will be required to generate new models, including resistive, capacitive, and other sensor parameters versus reference data collected from imaging. ) is not the solution because it would increase the rate of false positives as well as the irradiation of women. Between 54% and 60% of interval cancers are new tumors that could not be detected by mammography. The others, however, are the result of errors, which can be technical (about 20% of cases) or human (about 30% of cases).Many projects have been carried out over the past twenty years to overcome these problems. Ng et al. [3] reviewed the various technical studies and solutions that have been developed, particularly for the diagnosis of breast cancer, by exploring the electrical characteristics of tissues. More specifically, Du [4], Gupta [5], Stojadinovic [6], Jossinet [7], and other authors [8] focused on detecting breast cancer using bioelectrical impedance analysis (BIA), demonstrating up to 82.62% sensitivity and 95.79% specificity in the discrimination of benign and malignant breast tumors based on simple BIA models (injection of a low current and analysis of the induced voltage [9]) using characteristic tissue frequency (fc, kHz), which is the extrapolation of resistances using the Cole-Cole model (shown in Figure 1) at zero frequency and infinite frequency, known as Re (ohms) and Rinf (ohms), respectively [10].

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“…Centralized facilities could permit expert interpretation, including second readings, of either films or digitized data collected at several remote locations (Shtern and Winfield, 1999;Michalowski, 2003). In France, for example, the Association pour le Dépistage des Maladies du Sein (ADEMAS) program has provided free mammography screening to women between the ages of 50 and 65 in the Strasbourg administrative regions and in surrounding small towns and rural areas since 1989 (Gairard et al, 1992;Renaud et al, 1994). This "decentralized" program was designed to accommodate existing patterns of service delivery predominated by private-practice radiologists, the lack of reliable population registries, and an apparent reluctance on the part of general practitioners to encourage women to obtain mammograms.…”

Section: Centralized and "Decentralized" Interpretationmentioning

confidence: 99%

Improving Breast Imaging Quality Standards

Nass¹,

Ball²

2005

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Europe against Cancer breast cancer screening programme in France

Cited by 10 publications

References 0 publications

A pooled analysis of interval cancer rates in six European countries

A pooled analysis of interval cancer rates in six European countries

Evaluation on Phantoms of the Feasibility of a Smart Bra to Detect Breast Cancer in Young Adults

Improving Breast Imaging Quality Standards

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