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Item does not contain fulltext, Women tend to make a decision about participation in breast cancer screening and adhere to this for future invitations. Therefore, our study aimed to provide high-quality information on cumulative risks of false-positive (FP) recall and screen-detected breast cancer over multiple screening examinations. Individual Dutch screening registry data (2005-2018) were gathered on subsequent screening examinations of 92 902 women age 49 to 51 years in 2005. Survival analyses were used to calculate cumulative risks of a FP and a true-positive (TP) result after seven examinations. Data from 66 472 women age 58 to 59 years were used to extrapolate to 11 examinations. Participation, detection and additional FP rates were calculated for women who previously received FP results compared to women with true negative (TN) results. After 7 examinations, the cumulative risk of a TP result was 3.7% and the cumulative risk of a FP result was 9.1%. After 11 examinations, this increased to 7.1% and 13.5%, respectively. Following a FP result, participation was lower (71%-81%) than following a TN result (>90%). In women with a FP result, more TP results (factor 1.59 [95% CI: 1.44-1.72]), more interval cancers (factor 1.66 [95% CI: 1.41-1.91]) and more FP results (factor 1.96 [95% CI: 1.87-2.05]) were found than in women with TN results. In conclusion, due to a low recall rate in the Netherlands, the cumulative risk of a FP recall is relatively low, while the cumulative risk of a TP result is comparable. Breast cancer diagnoses and FP results were more common in women with FP results than in women with TN results, while participation was lower.

Item does not contain fulltext, In the TRIDENT-2 study, all pregnant women in the Netherlands are offered genome-wide non-invasive prenatal testing (GW-NIPT) with a choice of receiving either full screening or screening solely for common trisomies. Previous data showed that GW-NIPT can reliably detect common trisomies in the general obstetric population and that this test can also detect other chromosomal abnormalities (additional findings). However, evidence regarding the clinical impact of screening for additional findings is lacking. Therefore, we present follow-up results of the TRIDENT-2 study to determine this clinical impact based on the laboratory and perinatal outcomes of cases with additional findings. Between April 2017 and April 2019, additional findings were detected in 402/110,739 pregnancies (0.36%). For 358 cases, the origin was proven to be either fetal (n = 79; 22.1%), (assumed) confined placental mosaicism (CPM) (n = 189; 52.8%), or maternal (n = 90; 25.1%). For the remaining 44 (10.9%), the origin of the aberration could not be determined. Most fetal chromosomal aberrations were pathogenic and associated with severe clinical phenotypes (61/79; 77.2%). For CPM cases, occurrence of pre-eclampsia (8.5% [16/189] vs 0.5% [754/159,924]; RR 18.5), and birth weight <2.3rd percentile (13.6% [24/177] vs 2.5% [3,892/155,491]; RR 5.5) were significantly increased compared to the general obstetric population. Of the 90 maternal findings, 12 (13.3%) were malignancies and 32 (35.6%) (mosaic) pathogenic copy number variants, mostly associated with mild or no clinical phenotypes. Data from this large cohort study provide crucial information for deciding if and how to implement GW-NIPT in screening programs. Additionally, these data can inform the challenging interpretation, counseling, and follow-up of additional findings.

Contains fulltext : 189810.pdf (publisher's version ) (Open Access)

Item does not contain fulltext, Background: Overdiagnosis is the main harm of cancer screening programs but is difficult to quantify. This review aims to evaluate existing approaches to estimate the magnitude of overdiagnosis in cancer screening in order to gain insight into the strengths and limitations of these approaches and to provide researchers with guidance to obtain reliable estimates of overdiagnosis in cancer screening. Methods: A systematic review was done of primary research studies in PubMed that were published before January 1, 2016, and quantified overdiagnosis in breast cancer screening. The studies meeting inclusion criteria were then categorized by their methods to adjust for lead time and to obtain an unscreened reference population. For each approach, we provide an overview of the data required, assumptions made, limitations, and strengths. Results: A total of 442 studies were identified in the initial search. Forty studies met the inclusion criteria for the qualitative review. We grouped the approaches to adjust for lead time in two main categories: the lead time approach and the excess incidence approach. The lead time approach was further subdivided into the mean lead time approach, lead time distribution approach, and natural history modeling. The excess incidence approach was subdivided into the cumulative incidence approach and early vs late-stage cancer approach. The approaches used to obtain an unscreened reference population were grouped into the following categories: control group of a randomized controlled trial, nonattenders, control region, extrapolation of a prescreening trend, uninvited groups, adjustment for the effect of screening, and natural history modeling. Conclusions: Each approach to adjust for lead time and obtain an unscreened reference population has its own strengths and limitations, which should be taken into consideration when estimating overdiagnosis.

Contains fulltext : 172530.pdf (publisher's version ) (Open Access), BACKGROUND: Overdiagnosis by mammographic screening is defined as the excess in breast cancer incidence in the presence of screening compared to the incidence in the absence of screening. The latter is often estimated by extrapolating the pre-screening incidence trend. The aim of this theoretical study is to investigate the impact of assumptions in extrapolating the pre-screening incidence trend of invasive breast cancer on the estimated percentage of overdiagnosis. METHODS: We extracted data on invasive breast cancer incidence and person-years by calendar year (1975-2009) and 5-year age groups (0-85 years) from Dutch databases. Different combinations of assumptions for extrapolating the pre-screening period were investigated, such as variations in the type of regression model, end of the pre-screening period, screened age range, post-screening age range and adjustment for a trend in women <45. This resulted in 69,120 estimates of the percentage of overdiagnosis, i.e. excess cancer incidence in the presence of screening as a proportion of the number of screen-detected and interval cancers. RESULTS: Most overdiagnosis percentages are overestimated because of inadequate adjustment for lead time. The overdiagnosis estimates range between -7.1% and 65.1%, with a median of 33.6%. The choice of pre-screening period has the largest influence on the estimated percentage of overdiagnosis: the median estimate is 17.1% for extrapolations using 1975-1986 as the pre-screening period and 44.7% for extrapolations using 1975-1988 as the pre-screening period. CONCLUSION: The results of this theoretical study most likely cover the true overdiagnosis estimate, which is unknown, and may not necessarily represent the median overdiagnosis estimate. This study shows that overdiagnosis estimates heavily depend on the assumptions made in extrapolating the incidence in the pre-screening period, especially on the choice of the pre-screening period. These limitations should be acknowledged whe