Evidence map›Paper›PMID 28273181›Full record

ArticlePloS one2017

Evaluating lung cancer screening in China: Implications for eligibility criteria design from a microsimulation modeling approach.

Deirdre F Sheehan, Steven D Criss, G Scott Gazelle, Pari V Pandharipande, Chung Yin Kong

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

10 citing papers in PubMed, 13 citations in OpenAlex.

  1. 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
  2. Article
  3. Review
  4. Natural history models for lung Cancer: A scoping review.Lung cancer (Amsterdam, Netherlands) · 2025
    Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. 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

5 authors at 2 institutions in 1 country.

Deirdre F SheehanInstitute for Technology Assessment, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Steven D CrissInstitute for Technology Assessment, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
G Scott GazelleInstitute for Technology Assessment, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Pari V PandharipandeInstitute for Technology Assessment, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Chung Yin KongInstitute for Technology Assessment, Massachusetts General Hospital, Boston, Massachusetts, United States of America.ORCID http://orcid.org/0000-0001-6431-7830
Harvard University · USMassachusetts General Hospital · US

Funding

Comparative Modeling of Lung Cancer Prevention and Control PoliciesU01CA199284 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DE KONING, HARRY J, HOLFORD, THEODORE R · 2015 to 2019
$8.4M
NCI NIH HHS U01 CA199284
6 · The paper itself

Abstract

More than half of males in China are current smokers and evidence from western countries tells us that an unprecedented number of smoking-attributable deaths will occur as the Chinese population ages. We used the China Lung Cancer Policy Model (LCPM) to simulate effects of computed tomography (CT)-based lung cancer screening in China, comparing the impact of a screening guideline published in 2015 by a Chinese expert group to a version developed for the United States by the U.S. Centers for Medicare & Medicaid Services (CMS). The China LCPM, built using an existing lung cancer microsimulation model, can project population outcomes associated with interventions for smoking-related diseases. After calibrating the model to published Chinese smoking prevalence and lung cancer mortality rates, we simulated screening from 2016 to 2050 based on eligibility criteria from the CMS and Chinese guidelines, which differ by age to begin and end screening, pack-years smoked, and years since quitting. Outcomes included number of screens, mortality reduction, and life-years saved for each strategy. We projected that in the absence of screening, 14.98 million lung cancer deaths would occur between 2016 and 2050. Screening with the CMS guideline would prevent 0.72 million deaths and 5.8 million life-years lost, resulting in 6.58% and 1.97% mortality reduction in males and females, respectively. Screening with the Chinese guideline would prevent 0.74 million deaths and 6.6 million life-years lost, resulting in 6.30% and 2.79% mortality reduction in males and females, respectively. Through 2050, 1.43 billion screens would be required using the Chinese screening strategy, compared to 988 million screens using the CMS guideline. In conclusion, CT-based lung cancer screening implemented in 2016 and based on the Chinese screening guideline would prevent about 20,000 (2.9%) more lung cancer deaths through 2050, but would require about 445 million (44.7%) more screens than the CMS guideline.

Indexed as

Population SurveillanceAdolescentAdultAgedAged, 80 and overChinaComputer SimulationEarly Detection of CancerFemaleHumansLung NeoplasmsMaleMass ScreeningMiddle AgedModels, TheoreticalPrevalence

Identifiers

PMID28273181
PMCPMC5342219
OpenAlexW2593457987

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.