Evidence map›Paper›PMID 32594286›Full record

ArticleEuropean journal of epidemiology2020

Risk prediction models versus simplified selection criteria to determine eligibility for lung cancer screening: an analysis of German federal-wide survey and incidence data.

Anika Hüsing, Rudolf Kaaks

Open access · hybridAbstract read
In one paragraph

Article in European journal of epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 2 pooled it
2.8field-weighted citation impact, top 7% 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

23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 36 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Incidental Pulmonary Nodules: What Should We Do in 2026?Respiration; international review of thoracic diseases · 2026
    Review
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Lung cancer risk score for ever and never smokers in China.Cancer communications (London, England) · 2023
    Article
  13. Article
  14. Design and Rationale of the HANSE Study: A Holistic German Lung Cancer Screening Trial Using Low-Dose Computed Tomography.RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin · 2022
    Article
  15. Article
  16. Blood-Based Biomarker Panel for Personalized Lung Cancer Risk Assessment.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2022
    Article
  17. Article
  18. Contemporary issues in the implementation of lung cancer screening.European respiratory review : an official journal of the European Respiratory Society · 2021
    Review
  19. Review
  20. 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

2 authors at 2 institutions in 1 country.

Anika HüsingDepartment of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Rudolf KaaksDepartment of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany. r.kaaks@dkfz.de.
German Cancer Research Center · DEHeidelberg University · DE

Funding

Deutsche Zentrum für Lungenforschung PB13394
6 · The paper itself

Abstract

As randomized trials in the USA and Europe have convincingly demonstrated efficacy of lung cancer screening by computed tomography (CT), European countries are discussing the introduction of screening programs. To maintain acceptable cost-benefit and clinical benefit-to-harm ratios, screening should be offered to individuals at sufficiently elevated risk of having lung cancer. Using federal-wide survey and lung cancer incidence data (2008-2013), we examined the performance of four well-established risk models from the USA (PLCO

Indexed as

Eligibility DeterminationAdultEarly Detection of CancerFemaleGermanyHumansIncidenceLung NeoplasmsMaleMass ScreeningMiddle AgedPatient SelectionPredictive Value of TestsRisk AssessmentRisk FactorsSmokingEligibilityLung cancerRisk modelsScreening

Identifiers

PMID32594286
PMCPMC7524688
OpenAlexW3037017694

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.