Evidence map›Paper›PMID 40021589›Full record

ArticleBreast cancer research and treatment2025

The natural history of ductal carcinoma in situ: development, validation, and estimated outcomes of the SimDCIS model.

Keris Poelhekken, Monique D Dorrius, Amanda Dibden, Stephen W Duffy, Bert van der Vegt, Geertruida H de Bock, Marcel J W Greuter

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Breast cancer research and treatment, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Keris PoelhekkenDepartment of Epidemiology, University of Groningen, University Medical Center Groningen, P.O. Box 30 001, FA40, 9700 RB, Groningen, The Netherlands. k.poelhekken@umcg.nl.
Monique D DorriusDepartment of Radiology, University of Groningen, University Medical Center Groningen, PO Box 30.001, EB44, 9700 RB, Groningen, The Netherlands.
Amanda DibdenCentre for Cancer Screening, Prevention and Early Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.
Stephen W DuffyCentre for Cancer Screening, Prevention and Early Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.
Bert van der VegtDepartment of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, PO Box 30.001, 9700 RB, Groningen, The Netherlands.
Geertruida H de BockDepartment of Epidemiology, University of Groningen, University Medical Center Groningen, P.O. Box 30 001, FA40, 9700 RB, Groningen, The Netherlands.
Marcel J W GreuterDepartment of Radiology, University of Groningen, University Medical Center Groningen, PO Box 30.001, EB44, 9700 RB, Groningen, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo develop a novel simulation model for ductal carcinoma in situ (DCIS), fully validate it, and provide new estimates for DCIS in the setting of population-based biennial screening.

methodsA micro-simulation Markov model for DCIS (SimDCIS) was developed. Input parameters were independently derived from the literature and transition parameters were age- and grade-dependent. The model was applied to the Dutch biennial screening program. SimDCIS was internally, cross, and externally validated by comparison of the model output to data from the Netherlands Cancer Registry, a modelling study on the United Kingdom Frequency Trial, and the United Kingdom screening program, respectively. Univariate and probabilistic sensitivity analyses were performed to estimate uncertainty. DCIS regression, progression to invasive breast cancer (IBC), clinical detection, and screen-detection were estimated in Dutch screening setting.

resultsSimDCIS matched observed data in internal, external, and cross-validation. The model was most sensitive to DCIS onset probability, and the maximum variation in screen-detection rate was 11%. In Dutch screening setting, DCIS regression, progression to IBC, clinical detection, and screen-detection were estimated at 8% (0-14%), 19% (16-24%), 8% (0-13%), and 61% (56-65%), respectively. Grade distribution was 20% grade 1, 38% grade 2, and 42% grade 3.

conclusionSimDCIS provides strong accuracy across validation methods and is particularly sensitive to DCIS onset probability. Most DCIS will be found through screening, of which less than 50% of DCIS will be grade 3, less than 1 in 10 will regress, and 1 out of 5 DCIS will progress to IBC in biennial screening setting.

Indexed as

Breast NeoplasmsCarcinoma, Intraductal, NoninfiltratingAdultAgedComputer SimulationDisease ProgressionEarly Detection of CancerFemaleHumansMarkov ChainsMiddle AgedModels, StatisticalNetherlandsBreast ductal carcinoma in situBreast neoplasmsComputational modellingDisease progressionEarly detection of cancer

Identifiers

PMID40021589
PMCPMC11953075

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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.