ArticleBMC cancer2018
Detection and interval cancer rates during the transition from screen-film to digital mammography in population-based screening.
Article in BMC cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.
- Impact of Full-Field Digital Mammography Versus Film-Screen Mammography in Population Screening: A Meta-Analysis.Journal of the National Cancer Institute · 2021Pooled it
- Artificial Intelligence-Driven Personalization in Breast Cancer Screening: From Population Models to Individualized Protocols.Cancers · 2025Review
- Budget impact analysis of introducing digital breast tomosynthesis in breast cancer screening in Italy.La Radiologia medica · 2024Article
- European validation of an image-derived AI-based short-term risk model for individualized breast cancer screening-a nested case-control study.The Lancet regional health. Europe · 2024Article
- Future of Breast Radiology.European journal of breast health · 2023Review
- Severity and risk factors of interval breast cancer in Queensland, Australia: a population-based study.Breast cancer (Tokyo, Japan) · 2023Article
- Considerations for Evaluating the Introduction of New Cancer Screening Technology: Use of Interval Cancers to Assess Potential Benefits and Harms.International journal of environmental research and public health · 2022Review
- Diagnostics in Patients Suspect for Breast Cancer in The Netherlands.Current oncology (Toronto, Ont.) · 2021Article
- Can artificial intelligence reduce the interval cancer rate in mammography screening?European radiology · 2021Article
- Comprehensive trends in incidence, treatment, survival and mortality of first primary invasive breast cancer stratified by age, stage and receptor subtype in the Netherlands between 1989 and 2017.International journal of cancer · 2021Article
- Breast Cancer Screening in Asian Women with Dense Breast by Mammography: A Cross-Sectional Observational Study.Asian Pacific journal of cancer prevention : APJCP · 2021Observational
- [Digital Mammography as a Screening Tool in Korea].Taehan Yongsang Uihakhoe chi · 2021Review
- Frequency and diagnostic outcome of bilateral recall at screening mammography.International journal of cancer · 2021Observational
- Contralateral breast cancer risk in patients with ductal carcinoma in situ and invasive breast cancer.NPJ breast cancer · 2020Article
- Flemish breast cancer screening programme: 15 years of key performance indicators (2002-2016).BMC cancer · 2019Article
- Comparison of Digital and Screen-Film Mammography for Breast-Cancer Screening: A Systematic Review and Meta-Analysis.Journal of breast cancer · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundBetween 2003 and 2010 digital mammography (DM) gradually replaced screen-film mammography (SFM) in the Dutch breast cancer screening programme (BCSP). Previous studies showed increases in detection rate (DR) after the transition to DM. However, national interval cancer rates (ICR) have not yet been reported.
methodsWe assessed programme sensitivity and specificity during the transition period to DM, analysing nationwide data on screen-detected and interval cancers. Data of 7.3 million screens in women aged 49-74, between 2004 and 2011, were linked to the Netherlands Cancer Registry to obtain data on interval cancers. Age-adjusted DRs, ICRs and recall rates (RR) per 1000 screens and programme sensitivity and specificity were calculated by year, age and screening modality.
results41,662 screen-detected and 16,160 interval cancers were analysed. The DR significantly increased from 5.13 (95% confidence interval (CI):5.00-5.30) in 2004 to 6.34 (95% CI:6.15-6.47) in 2011, for both in situ (2004:0.73;2011:1.24) and invasive cancers (2004:4.42;2011:5.07), whereas the ICR remained stable (2004: 2.16 (95% CI2.06-2.25);2011: 2.13 (95% CI:2.04-2.22)). The RR changed significantly from 14.0 to 21.4. Programme sensitivity significantly increased, mainly between ages 49-59, from 70.0% (95% CI:68.9-71.2) to 74.4% (95% CI:73.5-75.4) whereas specificity slightly declined (2004:99.1% (95% CI:99.09-99.13);2011:98.5% (95% CI:98.45-98.50)). The overall DR was significantly higher for DM than for SFM (6.24;5.36) as was programme sensitivity (73.6%;70.1%), the ICR was similar (2.19;2.20) and specificity was significantly lower for DM (98.5%;98.9%).
conclusionsDuring the transition from SFM to DM, there was a significant rise in DR and a stable ICR, leading to increased programme sensitivity. Although the recall rate increased, programme specificity remained high compared to other countries. These findings indicate that the performance of DM in a nationwide screening programme is not inferior to, and may be even better, than that of SFM.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.