Evidence map›Paper›PMID 25906671›Full record

SynthesisBreast (Edinburgh, Scotland)2015

Simulation models in population breast cancer screening: A systematic review.

Rositsa G Koleva-Kolarova, Zhuozhao Zhan, Marcel J W Greuter, Talitha L Feenstra, Geertruida H De Bock

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Breast (Edinburgh, Scotland), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 9 pooled it
–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

19 citing papers in PubMed, 9 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Cost effectiveness of breast cancer screening and prevention: a systematic review with a focus on risk-adapted strategies.The European journal of health economics : HEPAC : health economics in prevention and care · 2021
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  5. Simulation modeling validity and utility in colorectal cancer screening delivery: A systematic review.Journal of the American Medical Informatics Association : JAMIA · 2020
    Pooled it
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  8. Simulation Models in Gastric Cancer Screening: A Systematic ReviewAsian Pacific journal of cancer prevention : APJCP · 2018
    Pooled it
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  10. Modeling in Colorectal Cancer Screening: Assessing External and Predictive Validity of MISCAN-Colon Microsimulation Model Using NORCCAP Trial Results.Medical decision making : an international journal of the Society for Medical Decision Making · 2018
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Rositsa G Koleva-KolarovaUniversity of Groningen, University Medical Center Groningen, Department of Epidemiology, PO Box 30.001, 9700RB Groningen, The Netherlands. Electronic address: r.koleva-kolarova@umcg.nl.
Zhuozhao ZhanUniversity of Groningen, University Medical Center Groningen, Department of Epidemiology, PO Box 30.001, 9700RB Groningen, The Netherlands. Electronic address: z.zhan01@umcg.nl.
Marcel J W GreuterUniversity of Groningen, University Medical Center Groningen, Department of Radiology, PO Box 30.001, 9700RB Groningen, The Netherlands. Electronic address: m.j.w.greuter@umcg.nl.
Talitha L FeenstraUniversity of Groningen, University Medical Center Groningen, Department of Epidemiology, PO Box 30.001, 9700RB Groningen, The Netherlands; RIVM, PO Box 1, 3720BA Bilthoven, The Netherlands. Electronic address: t.l.feenstra@umcg.nl.
Geertruida H De BockUniversity of Groningen, University Medical Center Groningen, Department of Epidemiology, PO Box 30.001, 9700RB Groningen, The Netherlands. Electronic address: g.h.de.bock@umcg.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this review was to critically evaluate published simulation models for breast cancer screening of the general population and provide a direction for future modeling. A systematic literature search was performed to identify simulation models with more than one application. A framework for qualitative assessment which incorporated model type; input parameters; modeling approach, transparency of input data sources/assumptions, sensitivity analyses and risk of bias; validation, and outcomes was developed. Predicted mortality reduction (MR) and cost-effectiveness (CE) were compared to estimates from meta-analyses of randomized control trials (RCTs) and acceptability thresholds. Seven original simulation models were distinguished, all sharing common input parameters. The modeling approach was based on tumor progression (except one model) with internal and cross validation of the resulting models, but without any external validation. Differences in lead times for invasive or non-invasive tumors, and the option for cancers not to progress were not explicitly modeled. The models tended to overestimate the MR (11-24%) due to screening as compared to optimal RCTs 10% (95% CI - 2-21%) MR. Only recently, potential harms due to regular breast cancer screening were reported. Most scenarios resulted in acceptable cost-effectiveness estimates given current thresholds. The selected models have been repeatedly applied in various settings to inform decision making and the critical analysis revealed high risk of bias in their outcomes. Given the importance of the models, there is a need for externally validated models which use systematical evidence for input data to allow for more critical evaluation of breast cancer screening.

Indexed as

Models, TheoreticalAlgorithmsBiasBreast NeoplasmsCost-Benefit AnalysisEarly Detection of CancerFemaleHumansMass ScreeningSensitivity and SpecificityBreast neoplasmsComputer simulationCost–benefit analysisMass screeningMortality

Identifiers

PMID25906671

What OpenQuestion holds

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Registered trials

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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.