Springer Nature
Browse

Modeling the natural history of ductal carcinoma in situ based on population data

Posted on 2020-05-28 - 03:39
Abstract Background The incidence of ductal carcinoma in situ (DCIS) has increased substantially since the introduction of mammography screening. Nevertheless, little is known about the natural history of preclinical DCIS in the absence of biopsy or complete excision. Methods Two well-established population models evaluated six possible DCIS natural history submodels. The submodels assumed 30%, 50%, or 80% of breast lesions progress from undetectable DCIS to preclinical screen-detectable DCIS; each model additionally allowed or prohibited DCIS regression. Preclinical screen-detectable DCIS could also progress to clinical DCIS or invasive breast cancer (IBC). Applying US population screening dissemination patterns, the models projected age-specific DCIS and IBC incidence that were compared to Surveillance, Epidemiology, and End Results data. Models estimated mean sojourn time (MST) in the preclinical screen-detectable DCIS state, overdiagnosis, and the risk of progression from preclinical screen-detectable DCIS. Results Without biopsy and surgical excision, the majority of DCIS (64–100%) in the preclinical screen-detectable state progressed to IBC in submodels assuming no DCIS regression (36–100% in submodels allowing for DCIS regression). DCIS overdiagnosis differed substantially between models and submodels, 3.1–65.8%. IBC overdiagnosis ranged 1.3–2.4%. Submodels assuming DCIS regression resulted in a higher DCIS overdiagnosis than submodels without DCIS regression. MST for progressive DCIS varied between 0.2 and 2.5 years. Conclusions Our findings suggest that the majority of screen-detectable but unbiopsied preclinical DCIS lesions progress to IBC and that the MST is relatively short. Nevertheless, due to the heterogeneity of DCIS, more research is needed to understand the progression of DCIS by grades and molecular subtypes.

CITE THIS COLLECTION

DataCite
3 Biotech
3D Printing in Medicine
3D Research
3D-Printed Materials and Systems
4OR
AAPG Bulletin
AAPS Open
AAPS PharmSciTech
Abhandlungen aus dem Mathematischen Seminar der Universität Hamburg
ABI Technik (German)
Academic Medicine
Academic Pediatrics
Academic Psychiatry
Academic Questions
Academy of Management Discoveries
Academy of Management Journal
Academy of Management Learning and Education
Academy of Management Perspectives
Academy of Management Proceedings
Academy of Management Review
or
Select your citation style and then place your mouse over the citation text to select it.

SHARE

email

Usage metrics

Breast Cancer Research

AUTHORS (11)

Sarocha Chootipongchaivat
Nicolien T. van Ravesteyn
Xiaoxue Li
Hui Huang
Harald Weedon-Fekjær
Marc D. Ryser
Donald L. Weaver
Elizabeth S. Burnside
Brandy M. Heckman-Stoddard
Harry J. de Koning
Sandra J. Lee
need help?