Loading…
A modeling analysis to compare eligibility strategies for lung cancer screening in Brazil
Country-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 defi...
Saved in:
Published in: | EClinicalMedicine 2021-12, Vol.42, p.101176-101176, Article 101176 |
---|---|
Main Authors: | , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c529t-51a70bbd2d1d9c935bfc3aa3d919b70faffbd17703e4e053ba4d12e6c3d253683 |
---|---|
cites | cdi_FETCH-LOGICAL-c529t-51a70bbd2d1d9c935bfc3aa3d919b70faffbd17703e4e053ba4d12e6c3d253683 |
container_end_page | 101176 |
container_issue | |
container_start_page | 101176 |
container_title | EClinicalMedicine |
container_volume | 42 |
creator | Miranda-Filho, Adalberto Charvat, Hadrien Bray, Freddie Migowski, Arn Cheung, Li C. Vaccarella, Salvatore Johansson, Mattias Carvalho, Andre L. Robbins, Hilary A. |
description | Country-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.
We 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 |
doi_str_mv | 10.1016/j.eclinm.2021.101176 |
format | article |
fullrecord | <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_49a9d67edaf7495d8fa501d26af61ed1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S2589537021004569</els_id><doaj_id>oai_doaj_org_article_49a9d67edaf7495d8fa501d26af61ed1</doaj_id><sourcerecordid>2597488117</sourcerecordid><originalsourceid>FETCH-LOGICAL-c529t-51a70bbd2d1d9c935bfc3aa3d919b70faffbd17703e4e053ba4d12e6c3d253683</originalsourceid><addsrcrecordid>eNp9kU1v1DAQQCMEolXpP0DIRy679UccxxekUgGtVIkLHDhZE3u8eOXEi52ttP31eEkp7YWTLc_MG8-8pnnL6JpR1l1s12hjmMY1p5wdn5jqXjSnXPZ6JYWiL5_cT5rzUraUUk7bXnf0dXMiWtVJLflp8-OSjMlhZW0ITBAPJRQyJ2LTuIOMpEY2YQgxzAdS5gwzbgIW4lMmcV9rLEwWMyk2I05HSJjIxwz3Ib5pXnmIBc8fzrPm--dP366uV7dfv9xcXd6urOR6XkkGig6D4445bbWQg7cCQDjN9KCoB-8Hx5SiAlukUgzQOsaxs8JxKbpenDU3C9cl2JpdDiPkg0kQzJ-HlDcG8hxsRNNq0K5T6MCrVkvXe5CUOd6B7xg6VlkfFtZuP4zoLE515PgM-jwyhZ9mk-5MLxWTQlTA-wdATr_2WGYzhmIxRpgw7YvhUqu276uumtouqTanUjL6xzaMmqNkszWLZHOUbBbJtezd0y8-Fv1V-m8GrEu_C5hNsQGrJRcy2rluJfy_w29JVrwz</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2597488117</pqid></control><display><type>article</type><title>A modeling analysis to compare eligibility strategies for lung cancer screening in Brazil</title><source>ScienceDirect</source><source>PubMed Central</source><creator>Miranda-Filho, Adalberto ; Charvat, Hadrien ; Bray, Freddie ; Migowski, Arn ; Cheung, Li C. ; Vaccarella, Salvatore ; Johansson, Mattias ; Carvalho, Andre L. ; Robbins, Hilary A.</creator><creatorcontrib>Miranda-Filho, Adalberto ; Charvat, Hadrien ; Bray, Freddie ; Migowski, Arn ; Cheung, Li C. ; Vaccarella, Salvatore ; Johansson, Mattias ; Carvalho, Andre L. ; Robbins, Hilary A.</creatorcontrib><description>Country-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.
We 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.
Among 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 [N = 2629 (95%CI 2448–2810)] by screening 21.9% of ever-smokers.
The 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.
H. Robbins and M. Johansson were supported by the INTEGRAL project (NCI U19 CA203654). H. Robbins was additionally supported by NCI R03 CA245979.</description><identifier>ISSN: 2589-5370</identifier><identifier>EISSN: 2589-5370</identifier><identifier>DOI: 10.1016/j.eclinm.2021.101176</identifier><identifier>PMID: 34765952</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Brazil ; Early cancer detection ; Lung cancer screening ; Research paper ; Tobacco smoking</subject><ispartof>EClinicalMedicine, 2021-12, Vol.42, p.101176-101176, Article 101176</ispartof><rights>2021</rights><rights>2021 Published by Elsevier Ltd.</rights><rights>2021 Published by Elsevier Ltd. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c529t-51a70bbd2d1d9c935bfc3aa3d919b70faffbd17703e4e053ba4d12e6c3d253683</citedby><cites>FETCH-LOGICAL-c529t-51a70bbd2d1d9c935bfc3aa3d919b70faffbd17703e4e053ba4d12e6c3d253683</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8571533/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S2589537021004569$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,3549,27924,27925,45780,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34765952$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Miranda-Filho, Adalberto</creatorcontrib><creatorcontrib>Charvat, Hadrien</creatorcontrib><creatorcontrib>Bray, Freddie</creatorcontrib><creatorcontrib>Migowski, Arn</creatorcontrib><creatorcontrib>Cheung, Li C.</creatorcontrib><creatorcontrib>Vaccarella, Salvatore</creatorcontrib><creatorcontrib>Johansson, Mattias</creatorcontrib><creatorcontrib>Carvalho, Andre L.</creatorcontrib><creatorcontrib>Robbins, Hilary A.</creatorcontrib><title>A modeling analysis to compare eligibility strategies for lung cancer screening in Brazil</title><title>EClinicalMedicine</title><addtitle>EClinicalMedicine</addtitle><description>Country-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.
We 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.
Among 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 [N = 2629 (95%CI 2448–2810)] by screening 21.9% of ever-smokers.
The 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.
H. Robbins and M. Johansson were supported by the INTEGRAL project (NCI U19 CA203654). H. Robbins was additionally supported by NCI R03 CA245979.</description><subject>Brazil</subject><subject>Early cancer detection</subject><subject>Lung cancer screening</subject><subject>Research paper</subject><subject>Tobacco smoking</subject><issn>2589-5370</issn><issn>2589-5370</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNp9kU1v1DAQQCMEolXpP0DIRy679UccxxekUgGtVIkLHDhZE3u8eOXEi52ttP31eEkp7YWTLc_MG8-8pnnL6JpR1l1s12hjmMY1p5wdn5jqXjSnXPZ6JYWiL5_cT5rzUraUUk7bXnf0dXMiWtVJLflp8-OSjMlhZW0ITBAPJRQyJ2LTuIOMpEY2YQgxzAdS5gwzbgIW4lMmcV9rLEwWMyk2I05HSJjIxwz3Ib5pXnmIBc8fzrPm--dP366uV7dfv9xcXd6urOR6XkkGig6D4445bbWQg7cCQDjN9KCoB-8Hx5SiAlukUgzQOsaxs8JxKbpenDU3C9cl2JpdDiPkg0kQzJ-HlDcG8hxsRNNq0K5T6MCrVkvXe5CUOd6B7xg6VlkfFtZuP4zoLE515PgM-jwyhZ9mk-5MLxWTQlTA-wdATr_2WGYzhmIxRpgw7YvhUqu276uumtouqTanUjL6xzaMmqNkszWLZHOUbBbJtezd0y8-Fv1V-m8GrEu_C5hNsQGrJRcy2rluJfy_w29JVrwz</recordid><startdate>20211201</startdate><enddate>20211201</enddate><creator>Miranda-Filho, Adalberto</creator><creator>Charvat, Hadrien</creator><creator>Bray, Freddie</creator><creator>Migowski, Arn</creator><creator>Cheung, Li C.</creator><creator>Vaccarella, Salvatore</creator><creator>Johansson, Mattias</creator><creator>Carvalho, Andre L.</creator><creator>Robbins, Hilary A.</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>6I.</scope><scope>AAFTH</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20211201</creationdate><title>A modeling analysis to compare eligibility strategies for lung cancer screening in Brazil</title><author>Miranda-Filho, Adalberto ; Charvat, Hadrien ; Bray, Freddie ; Migowski, Arn ; Cheung, Li C. ; Vaccarella, Salvatore ; Johansson, Mattias ; Carvalho, Andre L. ; Robbins, Hilary A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c529t-51a70bbd2d1d9c935bfc3aa3d919b70faffbd17703e4e053ba4d12e6c3d253683</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Brazil</topic><topic>Early cancer detection</topic><topic>Lung cancer screening</topic><topic>Research paper</topic><topic>Tobacco smoking</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Miranda-Filho, Adalberto</creatorcontrib><creatorcontrib>Charvat, Hadrien</creatorcontrib><creatorcontrib>Bray, Freddie</creatorcontrib><creatorcontrib>Migowski, Arn</creatorcontrib><creatorcontrib>Cheung, Li C.</creatorcontrib><creatorcontrib>Vaccarella, Salvatore</creatorcontrib><creatorcontrib>Johansson, Mattias</creatorcontrib><creatorcontrib>Carvalho, Andre L.</creatorcontrib><creatorcontrib>Robbins, Hilary A.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>EClinicalMedicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Miranda-Filho, Adalberto</au><au>Charvat, Hadrien</au><au>Bray, Freddie</au><au>Migowski, Arn</au><au>Cheung, Li C.</au><au>Vaccarella, Salvatore</au><au>Johansson, Mattias</au><au>Carvalho, Andre L.</au><au>Robbins, Hilary A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A modeling analysis to compare eligibility strategies for lung cancer screening in Brazil</atitle><jtitle>EClinicalMedicine</jtitle><addtitle>EClinicalMedicine</addtitle><date>2021-12-01</date><risdate>2021</risdate><volume>42</volume><spage>101176</spage><epage>101176</epage><pages>101176-101176</pages><artnum>101176</artnum><issn>2589-5370</issn><eissn>2589-5370</eissn><abstract>Country-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.
We 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.
Among 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 [N = 2629 (95%CI 2448–2810)] by screening 21.9% of ever-smokers.
The 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.
H. Robbins and M. Johansson were supported by the INTEGRAL project (NCI U19 CA203654). H. Robbins was additionally supported by NCI R03 CA245979.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>34765952</pmid><doi>10.1016/j.eclinm.2021.101176</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2589-5370 |
ispartof | EClinicalMedicine, 2021-12, Vol.42, p.101176-101176, Article 101176 |
issn | 2589-5370 2589-5370 |
language | eng |
recordid | cdi_doaj_primary_oai_doaj_org_article_49a9d67edaf7495d8fa501d26af61ed1 |
source | ScienceDirect; PubMed Central |
subjects | Brazil Early cancer detection Lung cancer screening Research paper Tobacco smoking |
title | A modeling analysis to compare eligibility strategies for lung cancer screening in Brazil |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-07T21%3A58%3A16IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20modeling%20analysis%20to%20compare%20eligibility%20strategies%20for%20lung%20cancer%20screening%20in%20Brazil&rft.jtitle=EClinicalMedicine&rft.au=Miranda-Filho,%20Adalberto&rft.date=2021-12-01&rft.volume=42&rft.spage=101176&rft.epage=101176&rft.pages=101176-101176&rft.artnum=101176&rft.issn=2589-5370&rft.eissn=2589-5370&rft_id=info:doi/10.1016/j.eclinm.2021.101176&rft_dat=%3Cproquest_doaj_%3E2597488117%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c529t-51a70bbd2d1d9c935bfc3aa3d919b70faffbd17703e4e053ba4d12e6c3d253683%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2597488117&rft_id=info:pmid/34765952&rfr_iscdi=true |