Evidence map›Paper›PMID 34765952›Full record

ArticleEClinicalMedicine2021

A modeling analysis to compare eligibility strategies for lung cancer screening in Brazil.

Adalberto Miranda-Filho, Hadrien Charvat, Freddie Bray, Arn Migowski, Li C Cheung, Salvatore Vaccarella, Mattias Johansson, Andre L Carvalho, Hilary A Robbins

Open access · goldAbstract read
In one paragraph

Article in EClinicalMedicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 20% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
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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

9 authors at 2 institutions in 2 countries.

Adalberto Miranda-FilhoInternational Agency for Research on Cancer, 150 Cours Albert Thomas, Lyon 69372 CEDEX 08, France.
Hadrien CharvatInternational Agency for Research on Cancer, 150 Cours Albert Thomas, Lyon 69372 CEDEX 08, France.
Freddie BrayInternational Agency for Research on Cancer, 150 Cours Albert Thomas, Lyon 69372 CEDEX 08, France.
Arn MigowskiCancer Early Detection Division, Brazilian National Cancer Institute (INCA), Brazil.
Li C CheungDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, DHHS, Bethesda, MD, USA.
Salvatore VaccarellaInternational Agency for Research on Cancer, 150 Cours Albert Thomas, Lyon 69372 CEDEX 08, France.
Mattias JohanssonInternational Agency for Research on Cancer, 150 Cours Albert Thomas, Lyon 69372 CEDEX 08, France.
Andre L CarvalhoInternational Agency for Research on Cancer, 150 Cours Albert Thomas, Lyon 69372 CEDEX 08, France.
Hilary A RobbinsInternational Agency for Research on Cancer, 150 Cours Albert Thomas, Lyon 69372 CEDEX 08, France.
Centre International de Recherche sur le Cancer · FRNational Cancer Institute · US

Funding

Translating Molecular and Clinical Data to Population Lung Cancer Risk AssessmentU19CA203654 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI Christopher I. Amos, Rayjean J. Hung · 2017 to 2026
$23.7M
Evaluating risk prediction models for use in lung cancer screening in diverse populations around the worldR03CA245979 · NCI · INTERNATIONAL AGENCY FOR RES ON CANCER · PI ROBBINS, HILARY A. · 2020 to 2020
$112k
NCI NIH HHS R03 CA245979NCI NIH HHS U19 CA203654World Health Organization 001
6 · The paper itself

Abstract

backgroundCountry-specific evidence is needed to guide decisions regarding whether and how to implement lung cancer screening in different settings. For this study, we estimated the potential numbers of individuals screened and lung cancer deaths prevented in Brazil after applying different strategies to define screening eligibility.

methodsWe applied the Lung Cancer Death Risk Assessment Tool (LCDRAT) to survey data on current and former smokers (ever-smokers) in 15 Brazilian state capital cities that comprise 18% of the Brazilian population. We evaluated three strategies to define eligibility for screening: (1) pack-years and cessation time (≥30 pack-years and <15 years since cessation); (2) the LCDRAT risk model with a fixed risk threshold; and (3) LCDRAT with age-specific risk thresholds.

findingsAmong 2.3 million Brazilian ever-smokers aged 55-79 years, 21,459 (95%CI 20,532-22,387) lung cancer deaths were predicted over 5 years without screening. Applying the fixed risk-based eligibility definition would prevent more lung cancer deaths than the pack-years definition [2,939 (95%CI 2751-3127) vs. 2,500 (95%CI 2318-2681) lung cancer deaths], and with higher screening efficiency [NNS=177 (95%CI 170-183) vs. 205 (95%CI 194-216)], but would tend to screen older individuals [mean age 67.8 (95%CI 67.5-68.2) vs. 63.4 (95%CI 63.0-63.9) years]. Applying age-specific risk thresholds would allow younger ever-smokers to be screened, although these individuals would be at lower risk. The age-specific thresholds strategy would avert three-fifths (60.1%) of preventable lung cancer deaths [

interpretationThe definition of eligibility impacts the efficiency of lung cancer screening and the mean age of the eligible population. As implementation of lung screening proceeds in different countries, our analytical framework can be used to guide similar analyses in other contexts. Due to limitations of our models, more research would be needed.

Indexed as

BrazilEarly cancer detectionLung cancer screeningTobacco smoking

Identifiers

PMID34765952
PMCPMC8571533
OpenAlexW3208377428

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.