Evidence map›Paper›PMID 33687468›Full record

SynthesisJAMA2021

Screening for Lung Cancer With Low-Dose Computed Tomography: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force.

Daniel E Jonas, Daniel S Reuland, Shivani M Reddy, Max Nagle, Stephen D Clark, Rachel Palmieri Weber, Chineme Enyioha, Teri L Malo, Alison T Brenner, Charli Armstrong and 4 more

Registry-linked trialOpen access · bronzeAbstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in JAMA, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07675889 (Intraoperative Longitude-Latitude-Depth Three-Dimensional Localization Versus Preoperative CT-Guided Percutaneous Lung Puncture Localization for the Treatment of 0.8-2 cm Peripheral Pulmonary Nodules), which is not on this map. Cited by 367 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
367citing papers in PubMed, 7 pooled it
59.6field-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.

NCT07675889 nanot yet recruitingnot on this mapstarted 2026, after this paper: background citation

Intraoperative Longitude-Latitude-Depth Three-Dimensional Localization Versus Preoperative CT-Guided Percutaneous Lung Puncture Localization for the Treatment of 0.8-2 cm Peripheral Pulmonary Nodules: A Multicenter, Randomized, Open-Label, Non-Inferiority Clinical Trial

TypeinterventionalSponsorQilu Hospital of Shandong UniversityRan2026 to 2028Enrolled274ConditionsPulmonary Nodule, Solitary, Peripheral Pulmonary Nodules, Pulmonary NodulesArmsLongitude-Latitude-Depth Localization, CT-Guided Percutaneous Lung Puncture Localization
3 · Its place in the literature

Who cites it

367 citing papers in PubMed, 7 syntheses or guidelines pooled it, 573 citations in OpenAlex.

  1. Pooled it
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  3. Large Language Models in Lung Cancer: Systematic Review.Journal of medical Internet research · 2025
    Pooled it
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  7. Lung Cancer Risk in US Adults with COPD: A Systematic Review and Meta-Analysis.International journal of chronic obstructive pulmonary disease · 2025
    Pooled it
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307 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 5 institutions in 1 country.

Daniel E JonasRTI International, University of North Carolina at Chapel Hill Evidence-based Practice Center.
Daniel S ReulandDepartment of Medicine, University of North Carolina at Chapel Hill.
Shivani M ReddyRTI International, University of North Carolina at Chapel Hill Evidence-based Practice Center.
Max NagleMichigan Medicine, University of Michigan, Ann Arbor.
Stephen D ClarkDepartment of Internal Medicine, Virginia Commonwealth University, Richmond.
Rachel Palmieri WeberRTI International, University of North Carolina at Chapel Hill Evidence-based Practice Center.
Chineme EnyiohaDepartment of Family Medicine, University of North Carolina at Chapel Hill.
Teri L MaloLineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill.
Alison T BrennerLineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill.
Charli ArmstrongRTI International, University of North Carolina at Chapel Hill Evidence-based Practice Center.
Manny Coker-SchwimmerRTI International, University of North Carolina at Chapel Hill Evidence-based Practice Center.
Jennifer Cook MiddletonRTI International, University of North Carolina at Chapel Hill Evidence-based Practice Center.
Christiane VoisinRTI International, University of North Carolina at Chapel Hill Evidence-based Practice Center.
Russell P HarrisDepartment of Medicine, University of North Carolina at Chapel Hill.
University of North Carolina at Chapel Hill · USRTI International · USMichigan Medicine · USThe Ohio State University · USVirginia Commonwealth University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Lung cancer is the leading cause of cancer-related death in the US. Objective: To review the evidence on screening for lung cancer with low-dose computed tomography (LDCT) to inform the US Preventive Services Task Force (USPSTF). Data Sources: MEDLINE, Cochrane Library, and trial registries through May 2019; references; experts; and literature surveillance through November 20, 2020. Study Selection: English-language studies of screening with LDCT, accuracy of LDCT, risk prediction models, or treatment for early-stage lung cancer. Data Extraction and Synthesis: Dual review of abstracts, full-text articles, and study quality; qualitative synthesis of findings. Data were not pooled because of heterogeneity of populations and screening protocols. Main Outcomes and Measures: Lung cancer incidence, lung cancer mortality, all-cause mortality, test accuracy, and harms. Results: This review included 223 publications. Seven randomized clinical trials (RCTs) (N = 86 486) evaluated lung cancer screening with LDCT; the National Lung Screening Trial (NLST, N = 53 454) and Nederlands-Leuvens Longkanker Screenings Onderzoek (NELSON, N = 15 792) were the largest RCTs. Participants were more likely to benefit than the US screening-eligible population (eg, based on life expectancy). The NLST found a reduction in lung cancer mortality (incidence rate ratio [IRR], 0.85 [95% CI, 0.75-0.96]; number needed to screen [NNS] to prevent 1 lung cancer death, 323 over 6.5 years of follow-up) with 3 rounds of annual LDCT screening compared with chest radiograph for high-risk current and former smokers aged 55 to 74 years. NELSON found a reduction in lung cancer mortality (IRR, 0.75 [95% CI, 0.61-0.90]; NNS to prevent 1 lung cancer death of 130 over 10 years of follow-up) with 4 rounds of LDCT screening with increasing intervals compared with no screening for high-risk current and former smokers aged 50 to 74 years. Harms of screening included radiation-induced cancer, false-positive results leading to unnecessary tests and invasive procedures, overdiagnosis, incidental findings, and increases in distress. For every 1000 persons screened in the NLST, false-positive results led to 17 invasive procedures (number needed to harm, 59) and fewer than 1 person having a major complication. Overdiagnosis estimates varied greatly (0%-67% chance that a lung cancer was overdiagnosed). Incidental findings were common, and estimates varied widely (4.4%-40.7% of persons screened). Conclusions and Relevance: Screening high-risk persons with LDCT can reduce lung cancer mortality but also causes false-positive results leading to unnecessary tests and invasive procedures, overdiagnosis, incidental findings, increases in distress, and, rarely, radiation-induced cancers. Most studies reviewed did not use current nodule evaluation protocols, which might reduce false-positive results and invasive procedures for false-positive results.

Indexed as

Early Detection of CancerTomography, X-Ray ComputedAgedAged, 80 and overCause of DeathFalse Positive ReactionsHumansLungLung NeoplasmsMedical OveruseMiddle AgedPractice Guidelines as TopicRisk FactorsSensitivity and SpecificitySmokingUnnecessary Procedures

Identifiers

PMID33687468
OpenAlexW3134447409

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.