Analysis of lung cancer risk model (PLCOM2012 and LLPv2) performance in a community-based lung cancer screening programme
IntroductionLow-dose CT (LDCT) screening of high-risk smokers reduces lung cancer (LC) specific mortality. Determining screening eligibility using individualised risk may improve screening effectiveness and reduce harm. Here, we compare the performance of two risk prediction models (PLCOM2012 and Li...
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| Veröffentlicht in: | Thorax 2020-08, Vol.75 (8), p.661-668 |
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| creator | Lebrett, Mikey B Balata, Haval Evison, Matthew Colligan, Denis Duerden, Rebecca Elton, Peter Greaves, Melanie Howells, John Irion, Klaus Karunaratne, Devinda Lyons, Judith Mellor, Stuart Myerscough, Amanda Newton, Tom Sharman, Anna Smith, Elaine Taylor, Ben Taylor, Sarah Walsham, Anna Whittaker, James Barber, Phil V Tonge, Janet Robbins, Hilary A Booton, Richard Crosbie, Philip A J |
| description | IntroductionLow-dose CT (LDCT) screening of high-risk smokers reduces lung cancer (LC) specific mortality. Determining screening eligibility using individualised risk may improve screening effectiveness and reduce harm. Here, we compare the performance of two risk prediction models (PLCOM2012 and Liverpool Lung Project model (LLPv2)) and National Lung Screening Trial (NLST) eligibility criteria in a community-based screening programme.MethodsEver-smokers aged 55–74, from deprived areas of Manchester, were invited to a Lung Health Check (LHC). Individuals at higher risk (PLCOM2012 score ≥1.51%) were offered annual LDCT screening over two rounds. LLPv2 score was calculated but not used for screening selection; ≥2.5% and ≥5% thresholds were used for analysis.ResultsPLCOM2012 ≥1.51% selected 56% (n=1429) of LHC attendees for screening. LLPv2 ≥2.5% also selected 56% (n=1430) whereas NLST (47%, n=1188) and LLPv2 ≥5% (33%, n=826) selected fewer. Over two screening rounds 62 individuals were diagnosed with LC; representing 87% (n=62/71) of 6-year incidence predicted by mean PLCOM2012 score (5.0%). 26% (n=16/62) of individuals with LC were not eligible for screening using LLPv2 ≥5%, 18% (n=11/62) with NLST criteria and 7% (n=5/62) with LLPv2 ≥2.5%. NLST eligible Manchester attendees had 2.5 times the LC detection rate than NLST participants after two annual screens (≈4.3% (n=51/1188) vs 1.7% (n=438/26 309); p |
| doi_str_mv | 10.1136/thoraxjnl-2020-214626 |
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| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7402560</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2421107458</sourcerecordid><originalsourceid>FETCH-LOGICAL-b4376-e254b88fc446a2fac7dc0fa7260a88b07c07a14d15fa2edb9acbb62cbc17d0f73</originalsourceid><addsrcrecordid>eNqNkUtvEzEUhS0EoqHwE0CW2JTFwPVj7MkGqYp4SUHtAtbWtceTThjbwc5U5N8zo5RAWSBWV7r3O0fHPoQ8Z_CaMaHe7G9Sxh_bOFQcOFScScXVA7KYZlMJvlQPyQJAQqWEVmfkSSlbAGgY04_JmeBKsKUQC3K4jDgcSl9o6ugwxg11GJ3PNPflGw2p9QO9uF6vrj5zYJxibOl6fX3LX9Gdz13KYaZpHylSl0IYY78_VBaLb--5FZe9j_202OW0yRiCf0oedTgU_-xunpOv7999WX2s1lcfPq0u15WVU_LK81rapumclAp5h063DjrUXAE2jQXtQCOTLas75L61S3TWKu6sY7qFTotz8vbouxtt8K3zcZ9xMLvcB8wHk7A39y-xvzGbdGu0BF4rmAwu7gxy-j76sjehL84PA0afxmK45IyBlnUzoS__QrdpzNMPz5QQXOpazYnqI-VyKiX77hSGgZnLNadyzVyuOZY76V78-ZKT6lebEwBHwIbtf3uy35JT2H9rfgL9isOP</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2433247567</pqid></control><display><type>article</type><title>Analysis of lung cancer risk model (PLCOM2012 and LLPv2) performance in a community-based lung cancer screening programme</title><source>MEDLINE</source><source>Alma/SFX Local Collection</source><creator>Lebrett, Mikey B ; Balata, Haval ; Evison, Matthew ; Colligan, Denis ; Duerden, Rebecca ; Elton, Peter ; Greaves, Melanie ; Howells, John ; Irion, Klaus ; Karunaratne, Devinda ; Lyons, Judith ; Mellor, Stuart ; Myerscough, Amanda ; Newton, Tom ; Sharman, Anna ; Smith, Elaine ; Taylor, Ben ; Taylor, Sarah ; Walsham, Anna ; Whittaker, James ; Barber, Phil V ; Tonge, Janet ; Robbins, Hilary A ; Booton, Richard ; Crosbie, Philip A J</creator><creatorcontrib>Lebrett, Mikey B ; Balata, Haval ; Evison, Matthew ; Colligan, Denis ; Duerden, Rebecca ; Elton, Peter ; Greaves, Melanie ; Howells, John ; Irion, Klaus ; Karunaratne, Devinda ; Lyons, Judith ; Mellor, Stuart ; Myerscough, Amanda ; Newton, Tom ; Sharman, Anna ; Smith, Elaine ; Taylor, Ben ; Taylor, Sarah ; Walsham, Anna ; Whittaker, James ; Barber, Phil V ; Tonge, Janet ; Robbins, Hilary A ; Booton, Richard ; Crosbie, Philip A J</creatorcontrib><description>IntroductionLow-dose CT (LDCT) screening of high-risk smokers reduces lung cancer (LC) specific mortality. Determining screening eligibility using individualised risk may improve screening effectiveness and reduce harm. Here, we compare the performance of two risk prediction models (PLCOM2012 and Liverpool Lung Project model (LLPv2)) and National Lung Screening Trial (NLST) eligibility criteria in a community-based screening programme.MethodsEver-smokers aged 55–74, from deprived areas of Manchester, were invited to a Lung Health Check (LHC). Individuals at higher risk (PLCOM2012 score ≥1.51%) were offered annual LDCT screening over two rounds. LLPv2 score was calculated but not used for screening selection; ≥2.5% and ≥5% thresholds were used for analysis.ResultsPLCOM2012 ≥1.51% selected 56% (n=1429) of LHC attendees for screening. LLPv2 ≥2.5% also selected 56% (n=1430) whereas NLST (47%, n=1188) and LLPv2 ≥5% (33%, n=826) selected fewer. Over two screening rounds 62 individuals were diagnosed with LC; representing 87% (n=62/71) of 6-year incidence predicted by mean PLCOM2012 score (5.0%). 26% (n=16/62) of individuals with LC were not eligible for screening using LLPv2 ≥5%, 18% (n=11/62) with NLST criteria and 7% (n=5/62) with LLPv2 ≥2.5%. NLST eligible Manchester attendees had 2.5 times the LC detection rate than NLST participants after two annual screens (≈4.3% (n=51/1188) vs 1.7% (n=438/26 309); p<0.0001). Adverse measures of health, including airflow obstruction, respiratory symptoms and cardiovascular disease, were positively correlated with LC risk. Coronary artery calcification was predictive of LC (adjOR 2.50, 95% CI 1.11 to 5.64; p=0.028).ConclusionProspective comparisons of risk prediction tools are required to optimise screening selection in different settings. The PLCOM2012 model may underestimate risk in deprived UK populations; further research focused on model calibration is required.</description><identifier>ISSN: 0040-6376</identifier><identifier>ISSN: 1468-3296</identifier><identifier>EISSN: 1468-3296</identifier><identifier>DOI: 10.1136/thoraxjnl-2020-214626</identifier><identifier>PMID: 32631933</identifier><language>eng</language><publisher>England: BMJ Publishing Group Ltd and British Thoracic Society</publisher><subject>Age ; Aged ; Chronic obstructive pulmonary disease ; Comorbidity ; Dyspnea ; Early Detection of Cancer ; Emphysema ; Female ; Health services ; Humans ; Lung Cancer ; Lung Neoplasms - diagnosis ; Lung Neoplasms - etiology ; Male ; Medical screening ; Middle Aged ; Mortality ; Patient Selection ; Population ; Predictive Value of Tests ; Risk Assessment ; Smoking ; Spirometry ; Tomography, X-Ray Computed ; United Kingdom ; Variables ; Variance analysis</subject><ispartof>Thorax, 2020-08, Vol.75 (8), p.661-668</ispartof><rights>Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.</rights><rights>2020 Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ . Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-b4376-e254b88fc446a2fac7dc0fa7260a88b07c07a14d15fa2edb9acbb62cbc17d0f73</citedby><cites>FETCH-LOGICAL-b4376-e254b88fc446a2fac7dc0fa7260a88b07c07a14d15fa2edb9acbb62cbc17d0f73</cites><orcidid>0000-0002-5386-9987 ; 0000-0001-9687-9184 ; 0000-0001-8941-4813</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,776,780,881,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32631933$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lebrett, Mikey B</creatorcontrib><creatorcontrib>Balata, Haval</creatorcontrib><creatorcontrib>Evison, Matthew</creatorcontrib><creatorcontrib>Colligan, Denis</creatorcontrib><creatorcontrib>Duerden, Rebecca</creatorcontrib><creatorcontrib>Elton, Peter</creatorcontrib><creatorcontrib>Greaves, Melanie</creatorcontrib><creatorcontrib>Howells, John</creatorcontrib><creatorcontrib>Irion, Klaus</creatorcontrib><creatorcontrib>Karunaratne, Devinda</creatorcontrib><creatorcontrib>Lyons, Judith</creatorcontrib><creatorcontrib>Mellor, Stuart</creatorcontrib><creatorcontrib>Myerscough, Amanda</creatorcontrib><creatorcontrib>Newton, Tom</creatorcontrib><creatorcontrib>Sharman, Anna</creatorcontrib><creatorcontrib>Smith, Elaine</creatorcontrib><creatorcontrib>Taylor, Ben</creatorcontrib><creatorcontrib>Taylor, Sarah</creatorcontrib><creatorcontrib>Walsham, Anna</creatorcontrib><creatorcontrib>Whittaker, James</creatorcontrib><creatorcontrib>Barber, Phil V</creatorcontrib><creatorcontrib>Tonge, Janet</creatorcontrib><creatorcontrib>Robbins, Hilary A</creatorcontrib><creatorcontrib>Booton, Richard</creatorcontrib><creatorcontrib>Crosbie, Philip A J</creatorcontrib><title>Analysis of lung cancer risk model (PLCOM2012 and LLPv2) performance in a community-based lung cancer screening programme</title><title>Thorax</title><addtitle>Thorax</addtitle><addtitle>Thorax</addtitle><description>IntroductionLow-dose CT (LDCT) screening of high-risk smokers reduces lung cancer (LC) specific mortality. Determining screening eligibility using individualised risk may improve screening effectiveness and reduce harm. Here, we compare the performance of two risk prediction models (PLCOM2012 and Liverpool Lung Project model (LLPv2)) and National Lung Screening Trial (NLST) eligibility criteria in a community-based screening programme.MethodsEver-smokers aged 55–74, from deprived areas of Manchester, were invited to a Lung Health Check (LHC). Individuals at higher risk (PLCOM2012 score ≥1.51%) were offered annual LDCT screening over two rounds. LLPv2 score was calculated but not used for screening selection; ≥2.5% and ≥5% thresholds were used for analysis.ResultsPLCOM2012 ≥1.51% selected 56% (n=1429) of LHC attendees for screening. LLPv2 ≥2.5% also selected 56% (n=1430) whereas NLST (47%, n=1188) and LLPv2 ≥5% (33%, n=826) selected fewer. Over two screening rounds 62 individuals were diagnosed with LC; representing 87% (n=62/71) of 6-year incidence predicted by mean PLCOM2012 score (5.0%). 26% (n=16/62) of individuals with LC were not eligible for screening using LLPv2 ≥5%, 18% (n=11/62) with NLST criteria and 7% (n=5/62) with LLPv2 ≥2.5%. NLST eligible Manchester attendees had 2.5 times the LC detection rate than NLST participants after two annual screens (≈4.3% (n=51/1188) vs 1.7% (n=438/26 309); p<0.0001). Adverse measures of health, including airflow obstruction, respiratory symptoms and cardiovascular disease, were positively correlated with LC risk. Coronary artery calcification was predictive of LC (adjOR 2.50, 95% CI 1.11 to 5.64; p=0.028).ConclusionProspective comparisons of risk prediction tools are required to optimise screening selection in different settings. The PLCOM2012 model may underestimate risk in deprived UK populations; further research focused on model calibration is required.</description><subject>Age</subject><subject>Aged</subject><subject>Chronic obstructive pulmonary disease</subject><subject>Comorbidity</subject><subject>Dyspnea</subject><subject>Early Detection of Cancer</subject><subject>Emphysema</subject><subject>Female</subject><subject>Health services</subject><subject>Humans</subject><subject>Lung Cancer</subject><subject>Lung Neoplasms - diagnosis</subject><subject>Lung Neoplasms - etiology</subject><subject>Male</subject><subject>Medical screening</subject><subject>Middle Aged</subject><subject>Mortality</subject><subject>Patient Selection</subject><subject>Population</subject><subject>Predictive Value of Tests</subject><subject>Risk Assessment</subject><subject>Smoking</subject><subject>Spirometry</subject><subject>Tomography, X-Ray Computed</subject><subject>United Kingdom</subject><subject>Variables</subject><subject>Variance analysis</subject><issn>0040-6376</issn><issn>1468-3296</issn><issn>1468-3296</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>9YT</sourceid><sourceid>ACMMV</sourceid><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNqNkUtvEzEUhS0EoqHwE0CW2JTFwPVj7MkGqYp4SUHtAtbWtceTThjbwc5U5N8zo5RAWSBWV7r3O0fHPoQ8Z_CaMaHe7G9Sxh_bOFQcOFScScXVA7KYZlMJvlQPyQJAQqWEVmfkSSlbAGgY04_JmeBKsKUQC3K4jDgcSl9o6ugwxg11GJ3PNPflGw2p9QO9uF6vrj5zYJxibOl6fX3LX9Gdz13KYaZpHylSl0IYY78_VBaLb--5FZe9j_202OW0yRiCf0oedTgU_-xunpOv7999WX2s1lcfPq0u15WVU_LK81rapumclAp5h063DjrUXAE2jQXtQCOTLas75L61S3TWKu6sY7qFTotz8vbouxtt8K3zcZ9xMLvcB8wHk7A39y-xvzGbdGu0BF4rmAwu7gxy-j76sjehL84PA0afxmK45IyBlnUzoS__QrdpzNMPz5QQXOpazYnqI-VyKiX77hSGgZnLNadyzVyuOZY76V78-ZKT6lebEwBHwIbtf3uy35JT2H9rfgL9isOP</recordid><startdate>20200801</startdate><enddate>20200801</enddate><creator>Lebrett, Mikey B</creator><creator>Balata, Haval</creator><creator>Evison, Matthew</creator><creator>Colligan, Denis</creator><creator>Duerden, Rebecca</creator><creator>Elton, Peter</creator><creator>Greaves, Melanie</creator><creator>Howells, John</creator><creator>Irion, Klaus</creator><creator>Karunaratne, Devinda</creator><creator>Lyons, Judith</creator><creator>Mellor, Stuart</creator><creator>Myerscough, Amanda</creator><creator>Newton, Tom</creator><creator>Sharman, Anna</creator><creator>Smith, Elaine</creator><creator>Taylor, Ben</creator><creator>Taylor, Sarah</creator><creator>Walsham, Anna</creator><creator>Whittaker, James</creator><creator>Barber, Phil V</creator><creator>Tonge, Janet</creator><creator>Robbins, Hilary A</creator><creator>Booton, Richard</creator><creator>Crosbie, Philip A J</creator><general>BMJ Publishing Group Ltd and British Thoracic Society</general><general>BMJ Publishing Group LTD</general><general>BMJ Publishing Group</general><scope>9YT</scope><scope>ACMMV</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BTHHO</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-5386-9987</orcidid><orcidid>https://orcid.org/0000-0001-9687-9184</orcidid><orcidid>https://orcid.org/0000-0001-8941-4813</orcidid></search><sort><creationdate>20200801</creationdate><title>Analysis of lung cancer risk model (PLCOM2012 and LLPv2) performance in a community-based lung cancer screening programme</title><author>Lebrett, Mikey B ; Balata, Haval ; Evison, Matthew ; Colligan, Denis ; Duerden, Rebecca ; Elton, Peter ; Greaves, Melanie ; Howells, John ; Irion, Klaus ; Karunaratne, Devinda ; Lyons, Judith ; Mellor, Stuart ; Myerscough, Amanda ; Newton, Tom ; Sharman, Anna ; Smith, Elaine ; Taylor, Ben ; Taylor, Sarah ; Walsham, Anna ; Whittaker, James ; Barber, Phil V ; Tonge, Janet ; Robbins, Hilary A ; Booton, Richard ; Crosbie, Philip A J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-b4376-e254b88fc446a2fac7dc0fa7260a88b07c07a14d15fa2edb9acbb62cbc17d0f73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Age</topic><topic>Aged</topic><topic>Chronic obstructive pulmonary disease</topic><topic>Comorbidity</topic><topic>Dyspnea</topic><topic>Early Detection of Cancer</topic><topic>Emphysema</topic><topic>Female</topic><topic>Health services</topic><topic>Humans</topic><topic>Lung Cancer</topic><topic>Lung Neoplasms - diagnosis</topic><topic>Lung Neoplasms - etiology</topic><topic>Male</topic><topic>Medical screening</topic><topic>Middle Aged</topic><topic>Mortality</topic><topic>Patient Selection</topic><topic>Population</topic><topic>Predictive Value of Tests</topic><topic>Risk Assessment</topic><topic>Smoking</topic><topic>Spirometry</topic><topic>Tomography, X-Ray Computed</topic><topic>United Kingdom</topic><topic>Variables</topic><topic>Variance analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lebrett, Mikey B</creatorcontrib><creatorcontrib>Balata, Haval</creatorcontrib><creatorcontrib>Evison, Matthew</creatorcontrib><creatorcontrib>Colligan, Denis</creatorcontrib><creatorcontrib>Duerden, Rebecca</creatorcontrib><creatorcontrib>Elton, Peter</creatorcontrib><creatorcontrib>Greaves, Melanie</creatorcontrib><creatorcontrib>Howells, John</creatorcontrib><creatorcontrib>Irion, Klaus</creatorcontrib><creatorcontrib>Karunaratne, Devinda</creatorcontrib><creatorcontrib>Lyons, Judith</creatorcontrib><creatorcontrib>Mellor, Stuart</creatorcontrib><creatorcontrib>Myerscough, Amanda</creatorcontrib><creatorcontrib>Newton, Tom</creatorcontrib><creatorcontrib>Sharman, Anna</creatorcontrib><creatorcontrib>Smith, Elaine</creatorcontrib><creatorcontrib>Taylor, Ben</creatorcontrib><creatorcontrib>Taylor, Sarah</creatorcontrib><creatorcontrib>Walsham, Anna</creatorcontrib><creatorcontrib>Whittaker, James</creatorcontrib><creatorcontrib>Barber, Phil V</creatorcontrib><creatorcontrib>Tonge, Janet</creatorcontrib><creatorcontrib>Robbins, Hilary A</creatorcontrib><creatorcontrib>Booton, Richard</creatorcontrib><creatorcontrib>Crosbie, Philip A J</creatorcontrib><collection>BMJ Open Access Journals</collection><collection>BMJ Journals:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>BMJ Journals</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Thorax</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lebrett, Mikey B</au><au>Balata, Haval</au><au>Evison, Matthew</au><au>Colligan, Denis</au><au>Duerden, Rebecca</au><au>Elton, Peter</au><au>Greaves, Melanie</au><au>Howells, John</au><au>Irion, Klaus</au><au>Karunaratne, Devinda</au><au>Lyons, Judith</au><au>Mellor, Stuart</au><au>Myerscough, Amanda</au><au>Newton, Tom</au><au>Sharman, Anna</au><au>Smith, Elaine</au><au>Taylor, Ben</au><au>Taylor, Sarah</au><au>Walsham, Anna</au><au>Whittaker, James</au><au>Barber, Phil V</au><au>Tonge, Janet</au><au>Robbins, Hilary A</au><au>Booton, Richard</au><au>Crosbie, Philip A J</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Analysis of lung cancer risk model (PLCOM2012 and LLPv2) performance in a community-based lung cancer screening programme</atitle><jtitle>Thorax</jtitle><stitle>Thorax</stitle><addtitle>Thorax</addtitle><date>2020-08-01</date><risdate>2020</risdate><volume>75</volume><issue>8</issue><spage>661</spage><epage>668</epage><pages>661-668</pages><issn>0040-6376</issn><issn>1468-3296</issn><eissn>1468-3296</eissn><abstract>IntroductionLow-dose CT (LDCT) screening of high-risk smokers reduces lung cancer (LC) specific mortality. Determining screening eligibility using individualised risk may improve screening effectiveness and reduce harm. Here, we compare the performance of two risk prediction models (PLCOM2012 and Liverpool Lung Project model (LLPv2)) and National Lung Screening Trial (NLST) eligibility criteria in a community-based screening programme.MethodsEver-smokers aged 55–74, from deprived areas of Manchester, were invited to a Lung Health Check (LHC). Individuals at higher risk (PLCOM2012 score ≥1.51%) were offered annual LDCT screening over two rounds. LLPv2 score was calculated but not used for screening selection; ≥2.5% and ≥5% thresholds were used for analysis.ResultsPLCOM2012 ≥1.51% selected 56% (n=1429) of LHC attendees for screening. LLPv2 ≥2.5% also selected 56% (n=1430) whereas NLST (47%, n=1188) and LLPv2 ≥5% (33%, n=826) selected fewer. Over two screening rounds 62 individuals were diagnosed with LC; representing 87% (n=62/71) of 6-year incidence predicted by mean PLCOM2012 score (5.0%). 26% (n=16/62) of individuals with LC were not eligible for screening using LLPv2 ≥5%, 18% (n=11/62) with NLST criteria and 7% (n=5/62) with LLPv2 ≥2.5%. NLST eligible Manchester attendees had 2.5 times the LC detection rate than NLST participants after two annual screens (≈4.3% (n=51/1188) vs 1.7% (n=438/26 309); p<0.0001). Adverse measures of health, including airflow obstruction, respiratory symptoms and cardiovascular disease, were positively correlated with LC risk. Coronary artery calcification was predictive of LC (adjOR 2.50, 95% CI 1.11 to 5.64; p=0.028).ConclusionProspective comparisons of risk prediction tools are required to optimise screening selection in different settings. The PLCOM2012 model may underestimate risk in deprived UK populations; further research focused on model calibration is required.</abstract><cop>England</cop><pub>BMJ Publishing Group Ltd and British Thoracic Society</pub><pmid>32631933</pmid><doi>10.1136/thoraxjnl-2020-214626</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-5386-9987</orcidid><orcidid>https://orcid.org/0000-0001-9687-9184</orcidid><orcidid>https://orcid.org/0000-0001-8941-4813</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Thorax, 2020-08, Vol.75 (8), p.661-668 |
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| subjects | Age Aged Chronic obstructive pulmonary disease Comorbidity Dyspnea Early Detection of Cancer Emphysema Female Health services Humans Lung Cancer Lung Neoplasms - diagnosis Lung Neoplasms - etiology Male Medical screening Middle Aged Mortality Patient Selection Population Predictive Value of Tests Risk Assessment Smoking Spirometry Tomography, X-Ray Computed United Kingdom Variables Variance analysis |
| title | Analysis of lung cancer risk model (PLCOM2012 and LLPv2) performance in a community-based lung cancer screening programme |
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