Evidence map›Paper›PMID 28179230›Full record

ArticleBMJ (Clinical research ed.)2017

Exposure to low dose computed tomography for lung cancer screening and risk of cancer: secondary analysis of trial data and risk-benefit analysis.

Cristiano Rampinelli, Paolo De Marco, Daniela Origgi, Patrick Maisonneuve, Monica Casiraghi, Giulia Veronesi, Lorenzo Spaggiari, Massimo Bellomi

Open access · hybridAbstract read
In one paragraph

Article in BMJ (Clinical research ed.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 140 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
140citing papers in PubMed, 5 pooled it
18.8field-weighted citation impact, top 1% 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

140 citing papers in PubMed, 5 syntheses or guidelines pooled it, 266 citations in OpenAlex.

  1. Personalizing cancer risk: a systematic review of risk communication strategies.Journal of cancer research and clinical oncology · 2026
    Pooled it
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  5. Lung Cancer Screening, Version 3.2018, NCCN Clinical Practice Guidelines in Oncology.Journal of the National Comprehensive Cancer Network : JNCCN · 2018
    Guideline
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  7. Trial
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  20. Detection and localization of radiation-induced pneumonitis usingPhysics and imaging in radiation oncology · 2025
    Article

80 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Cristiano RampinelliDepartment of Medical Imaging and Radiation Sciences, European Institute of Oncology, Milan, Italy cristiano.rampinelli@ieo.it.
Paolo De MarcoMedical Physics School, University of Milan, Milan, Italy.
Daniela OriggiDivision of Medical Physics, European Institute of Oncology, Milan, Italy.
Patrick MaisonneuveDivision of Epidemiology and Biostatistics, European Institute of Oncology, Milan, Italy.
Monica CasiraghiDivision of Thoracic Surgery, European Institute of Oncology, Milan, Italy.
Giulia VeronesiDivision of Thoracic Surgery, European Institute of Oncology, Milan, Italy.
Lorenzo SpaggiariDivision of Thoracic Surgery, European Institute of Oncology, Milan, Italy.
Massimo BellomiDepartment of Medical Imaging and Radiation Sciences, European Institute of Oncology, Milan, Italy.
European Institute of Oncology · ITUniversity of Milan · ITIRCCS Humanitas Research Hospital · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Lung NeoplasmsNeoplasms, Radiation-InducedPositron-Emission TomographyTomography, X-Ray ComputedAdultEarly Detection of CancerFemaleHumansIncidenceItalyMaleMass ScreeningMiddle AgedRadiation DosageRisk AssessmentRisk Factors

Identifiers

PMID28179230
PMCPMC5421449
OpenAlexW2587613030

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.