Evidence map›Paper›PMID 36698854›Full record

ArticleMDM policy & practice

Modeling the Natural History and Screening Effects of Colorectal Cancer Using Both Adenoma and Serrated Neoplasia Pathways: The Development, Calibration, and Validation of a Discrete Event Simulation Model.

Chih-Yuan Cheng, Silvia Calderazzo, Christoph Schramm, Michael Schlander

Open access · goldAbstract read
In one paragraph

Article in MDM policy & practice. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.6field-weighted citation impact, top 15% of its field
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

8 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. A Scoping Review on Calibration Methods for Cancer Simulation Models.Medical decision making : an international journal of the Society for Medical Decision Making · 2025
    Article
  4. Article
  5. Calculating epidemiological outcomes from simulated longitudinal data.medRxiv : the preprint server for health sciences · 2025
    Article
  6. Article
  7. Article
  8. 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

4 authors at 2 institutions in 1 country.

Chih-Yuan ChengDivision of Health Economics, German Cancer Research Center (DKFZ), Heidelberg, Germany.ORCID https://orcid.org/0000-0001-6220-0524
Silvia CalderazzoDivision of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Christoph SchrammClinics of Gastroenterology, Hepatology and Transplantation Medicine, Essen University Hospital, Essen, Germany.
Michael SchlanderDivision of Health Economics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
German Cancer Research Center · DEEssen University Hospital · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Highlights: This article presents a new discrete event simulation model, DECAS, which models both adenoma-carcinoma and serrated neoplasia pathways for colorectal cancer (CRC) development and CRC screening effects.DECAS is calibrated based on a Bayesian inference method using the data from German screening colonoscopy program, which consists of more than 5 million first-time average-risk participants aged 55 years and older in 2003 to 2014.DECAS is flexible for evaluating various CRC screening strategies and can differentiate screening effects in different parts of the colon.DECAS is validated with large screening sigmoidoscopy and colonoscopy clinical study data and can be further used to evaluate the (cost-)effectiveness of German colorectal cancer screening strategies.

Indexed as

bayesian calibrationcolorectal cancerdiscrete event simulationscreeningserrated polyps

Identifiers

PMID36698854
PMCPMC9869210
OpenAlexW4317628612

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.