Evidence map›Paper›PMID 18458247›Full record

ArticleRadiology2008

Estimating long-term effectiveness of lung cancer screening in the Mayo CT screening study.

Pamela M McMahon, Chung Yin Kong, Bruce E Johnson, Milton C Weinstein, Jane C Weeks, Karen M Kuntz, Jo-Anne O Shepard, Stephen J Swensen, G Scott Gazelle

Abstract read
In one paragraph

Article in Radiology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

43 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. International association for the study of lung cancer/american thoracic society/european respiratory society international multidisciplinary classification of lung adenocarcinoma.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2011
    Pooled it
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  4. Natural history models for lung Cancer: A scoping review.Lung cancer (Amsterdam, Netherlands) · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Pamela M McMahonInstitute for Technology Assessment, Massachusetts General Hospital, 101 Merrimac St, 10th Floor, Boston, MA 02114, USA. pamela@mgh-ita.org
Chung Yin Kong
Bruce E Johnson
Milton C Weinstein
Jane C Weeks
Karen M Kuntz
Jo-Anne O Shepard
Stephen J Swensen
G Scott Gazelle

Funding

A Lung Cancer Policy ModelR01CA097337 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI GAZELLE, G SCOTT · 2004 to 2006
$1.1M
Developing approaches for modeling genomic and proteomic profiles in lung cancerK99CA126147 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI MCMAHON, PAMELA MARKELL · 2007 to 2008
$283k
NCI NIH HHS K99 CA126147NCI NIH HHS R01 CA97337
6 · The paper itself

Abstract

purposeTo use individual-level data provided from the single-arm study of helical computed tomographic (CT) screening at the Mayo Clinic (Rochester, Minn) to estimate the long-term effectiveness of screening in Mayo study participants and to compare estimates from an existing lung cancer simulation model with estimates from a different modeling approach that used the same data. MATERIALS AND

methodsThe study was approved by institutional review boards and was HIPAA compliant. Deidentified individual-level data from participants (1520 current or former smokers aged 50-85 years) in the Mayo Clinic helical CT screening study were used to populate the Lung Cancer Policy Model, a comprehensive microsimulation model of lung cancer development, screening findings, treatment results, and long-term outcomes. The model predicted diagnosed cases of lung cancer and deaths per simulated study arm (five annual screening examinations vs no screening). Main outcome measures were predicted changes in lung cancer-specific and all-cause mortality as functions of follow-up time after simulated enrollment and randomization.

resultsAt 6-year follow-up, the screening arm had an estimated 37% relative increase in lung cancer detection, compared with the control arm. At 15-year follow-up, five annual screening examinations yielded a 9% relative increase in lung cancer detection. The relative reduction in cumulative lung cancer-specific mortality from five annual screening examinations was 28% at 6-year follow-up (15% at 15 years). The relative reduction in cumulative all-cause mortality from five annual screening examinations was 4% at 6-year follow-up (2% at 15 years).

conclusionScreening may reduce lung cancer-specific mortality but may offer a smaller reduction in overall mortality because of increased competing mortality risks associated with smoking.

Indexed as

Outcome Assessment, Health CareAgedAged, 80 and overCohort StudiesFemaleHumansLung NeoplasmsMaleMass ScreeningMiddle AgedMinnesotaPrevalencePrognosisProportional Hazards ModelsReproducibility of ResultsSensitivity and Specificity

Identifiers

PMID18458247
PMCPMC5410933

What OpenQuestion holds

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Read underepoch 390

Registered trials

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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.