ArticleMedical decision making : an international journal of the Society for Medical Decision Making2018
The Dana-Farber CISNET Model for Breast Cancer Screening Strategies: An Update.
Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.
- Benefits and harms of annual, biennial, or triennial breast cancer mammography screening for women at average risk of breast cancer: a systematic review for the European Commission Initiative on Breast Cancer (ECIBC).British journal of cancer · 2022Pooled it
- Estimating the carcinogenesis timelines in early-onset versus late-onset cancers and changes across birth cohorts.Science advances · 2026Article
- Modeling Early-Onset Cancer Kinetics Reveals Changes in Underlying Risk and the Impact of Population Screening.Cancer research · 2025Article
- Estimating the carcinogenesis timelines in early-onset versus late-onset cancers and changes across birth cohorts.medRxiv : the preprint server for health sciences · 2025Article
- Modeling early-onset cancer kinetics to study changes in underlying risk, detection, and impact of population screening.medRxiv : the preprint server for health sciences · 2025Article
- Mathematical Modeling to Address Questions in Breast Cancer Screening: An Overview of the Breast Cancer Models of the Cancer Intervention and Surveillance Modeling Network.Journal of breast imaging · 2025Review
- Evaluation of the Slovenian Breast Cancer Screening Programme: Years of Life Gained and Avoided Deaths.Cancers · 2025Article
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- Population simulation modeling of disparities in US breast cancer mortality.Journal of the National Cancer Institute. Monographs · 2023Article
- Patient Navigation Can Improve Breast Cancer Outcomes among African American Women in Chicago: Insights from a Modeling Study.Journal of urban health : bulletin of the New York Academy of Medicine · 2022Article
- Estimation of Breast Cancer Overdiagnosis in a U.S. Breast Screening Cohort.Annals of internal medicine · 2022Article
- Cancer screening simulation models: a state of the art review.BMC medical informatics and decision making · 2021Review
- Reflecting on 20 years of breast cancer modeling in CISNET: Recommendations for future cancer systems modeling efforts.PLoS computational biology · 2021Review
- Long-Term Outcomes and Cost-Effectiveness of Breast Cancer Screening With Digital Breast Tomosynthesis in the United States.Journal of the National Cancer Institute · 2020Article
- Modeling the natural history of ductal carcinoma in situ based on population data.Breast cancer research : BCR · 2020Article
- Common Model Inputs Used in CISNET Collaborative Breast Cancer Modeling.Medical decision making : an international journal of the Society for Medical Decision Making · 2018Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundWe present updated features to a model developed by Dana-Farber investigators within the Cancer Intervention and Surveillance Modeling Network (CISNET). The initial model was developed to evaluate the impact of mammography screening strategies.
methodsThis major update includes the incorporation of ductal carcinoma in situ (DCIS) as part of the natural history of breast cancer. The updated model allows DCIS in the pre-clinical state to regress to undetectable early-stage DCIS, or to transition to invasive breast cancer, or to clinical DCIS. We summarize model assumptions for DCIS natural history and model parameters. Another new development is the derivation of analytical expressions for overdiagnosis. Overdiagnosis refers to mammographic identification of breast cancer that would never have resulted in disease symptoms in the patient's remaining lifetime (i.e., lead time longer than residual survival time). This is an inevitable consequence of early detection. Our model uniquely assesses overdiagnosis using an analytical formulation. We derive the lead time distribution resulting from the early detection of invasive breast cancer and DCIS, and formulate the analytical expression for overdiagnosis.
resultsThis formulation was applied to assess overdiagnosis from mammography screening. Other model updates involve implementing common model input parameters with updated treatment dissemination and effectiveness, and improved mammography performance. Lastly, the model was expanded to incorporate subgroups by breast density and molecular subtypes.
conclusionsThe incorporation of DCIS and subgroups and the derivation of an overdiagnosis estimation procedure improve the model for evaluating mammography screening programs.
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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.