Evidence map›Paper›PMID 33644856›Full record

ArticleInternational journal of cancer2021

Identifying key factors for the effectiveness of pancreatic cancer screening: A model-based analysis.

Brechtje D M Koopmann, Femme Harinck, Sonja Kroep, Ingrid C A W Konings, Steffie K Naber, Iris Lansdorp-Vogelaar, Paul Fockens, Jeanin E van Hooft, Djuna L Cahen, Marjolein van Ballegooijen and 2 more

Open access · hybridAbstract read
In one paragraph

Article in International journal of cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
0.7field-weighted citation impact, top 28% 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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Stage Shift as an Endpoint in Cancer Screening Trials: Implications for Evaluating Multicancer Early Detection Tests.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2022
    Article
  7. Prediction of Breast Cancer using Machine Learning Approaches.Journal of biomedical physics & engineering · 2022
    Article
  8. Article
  9. Review
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

12 authors at 2 institutions in 1 country.

Brechtje D M KoopmannDepartment of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.ORCID 0000-0001-5025-5050
Femme HarinckDepartment of Gastroenterology & Hepatology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Sonja KroepDepartment of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Ingrid C A W KoningsDepartment of Gastroenterology & Hepatology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Steffie K NaberDepartment of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Iris Lansdorp-VogelaarDepartment of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.ORCID 0000-0002-9438-2753
Paul FockensDepartment of Gastroenterology & Hepatology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands.
Jeanin E van HooftDepartment of Gastroenterology & Hepatology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands.
Djuna L CahenDepartment of Gastroenterology & Hepatology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Marjolein van BallegooijenDepartment of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Marco J BrunoDepartment of Gastroenterology & Hepatology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Inge M C M de KokDepartment of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.ORCID 0000-0002-9419-0452
Erasmus MC · NLAmsterdam University Medical Centers · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic cancer (PC) survival is poor, as detection usually occurs late, when treatment options are limited. Screening of high-risk individuals may enable early detection and a more favorable prognosis. Knowledge gaps prohibit establishing the effectiveness of screening. We developed a Microsimulation Screening Analysis model to analyze the impact of relevant uncertainties on the effect of PC screening in high-risk individuals. The model simulates two base cases: one in which lesions always progress to PC and one in which indolent and faster progressive lesions coexist. For each base case, the effect of annual and 5-yearly screening with endoscopic ultrasonography/magnetic resonance imaging was evaluated. The impact of variance in PC risk, screening test characteristics and surgery-related mortality was evaluated using sensitivity analyses. Screening resulted in a reduction of PC mortality by at least 16% in all simulated scenarios. This reduction depended strongly on the natural disease course (annual screening: -57% for "Progressive-only" vs -41% for "Indolent Included"). The number of screen and surveillance tests needed to prevent one cancer death was impacted most by PC risk. A 10% increase in test sensitivity reduced mortality by 1.9% at most. Test specificity is important for the number of surveillance tests. In conclusion, screening reduces PC mortality in all modeled scenarios. The natural disease course and PC risk strongly determines the effectiveness of screening. Test sensitivity seems of lesser influence than specificity. Future research should gain more insight in PC pathobiology to establish the true value of PC screening in high-risk individuals.

Indexed as

Computer SimulationEarly Detection of CancerEndosonographyHumansMagnetic Resonance ImagingMaleModels, MolecularMortalityPancreatic NeoplasmsPopulation SurveillanceRisk FactorsStochastic Processesmicrosimulation modelpancreatic cancerscreening

Identifiers

PMID33644856
PMCPMC8251934
OpenAlexW3134075616

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.