Combining risk factors with faecal immunochemical test outcome for selecting CRC screenees for colonoscopy
Objective Faecal immunochemical testing (FIT) is increasingly used in colorectal cancer (CRC) screening but has a less than perfect sensitivity. Combining risk stratification, based on established risk factors for advanced neoplasia, with the FIT result for allocating screenees to colonoscopy could...
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| Veröffentlicht in: | Gut 2014-03, Vol.63 (3), p.466-471 |
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| creator | Stegeman, Inge de Wijkerslooth, Thomas R Stoop, Esther M van Leerdam, Monique E Dekker, Evelien van Ballegooijen, Marjolein Kuipers, Ernst J Fockens, Paul Kraaijenhagen, Roderik A Bossuyt, Patrick M |
| description | Objective Faecal immunochemical testing (FIT) is increasingly used in colorectal cancer (CRC) screening but has a less than perfect sensitivity. Combining risk stratification, based on established risk factors for advanced neoplasia, with the FIT result for allocating screenees to colonoscopy could increase the sensitivity and diagnostic yield of FIT-based screening. We explored the use of a risk prediction model in CRC screening. Design We collected data in the colonoscopy arm of the Colonoscopy or Colonography for Screening study, a multicentre screening trial. For this study 6600 randomly selected, asymptomatic men and women between 50 years and 75 years of age were invited to undergo colonoscopy. Screening participants were asked for one sample FIT (OC-sensor) and to complete a risk questionnaire prior to colonoscopy. Based on the questionnaire data and the FIT results, we developed a multivariable risk model with the following factors: total calcium intake, family history, age and FIT result. We evaluated goodness-of-fit, calibration and discrimination, and compared it with a model based on primary screening with FIT only. Results Of the 1426 screening participants, 1112 (78%) completed the questionnaire and FIT. Of these, 101 (9.1%) had advanced neoplasia. The risk based model significantly increased the goodness-of-fit compared with a model based on FIT only (p50 ng/mL, 5 more cases of advanced neoplasia would be detected (net reclassification improvement 0.054, p=0.073). Conclusions Adding risk based stratification increases the accuracy FIT-based CRC screening and could be used in preselection for colonoscopy in CRC screening programmes. |
| doi_str_mv | 10.1136/gutjnl-2013-305013 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1499121071</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>4014687851</sourcerecordid><originalsourceid>FETCH-LOGICAL-b369t-612f4524d993226f047529016266dca7c4b9e2a52c05454d2a6c2449bf7a90ce3</originalsourceid><addsrcrecordid>eNqNkUtLxDAUhYMozvj4Ay6k4MZNNUnzaJZSfMGAILoOaXqrrU0zJi3iv7djRxeuXB0u97uHwz0InRB8QUgmLl_Goe27lGKSpRnmk-ygJWEiTzOa57toiTGRKZdMLdBBjC3GOM8V2UcLminBsMqXqC28K5u-6V-S0MS3pDZ28CEmH83wOg1gTZc0zo29t6_gms04QBwSPw7WO0hqH5IIHdhhY1E8Fkm0AaAHiN876zvf-2j9-vMI7dWmi3C81UP0fHP9VNylq4fb--JqlZaZUEMqCK0Zp6xSKqNU1JhJThUmggpRWSMtKxVQw6nFnHFWUSMsZUyVtTQKW8gO0fnsuw7-fZzCatdEC11nevBj1IQpRSjBkkzo2R-09WPop3SaSKkYV1zJiaIzZYOPMUCt16FxJnxqgvWmCT03oTdN6LmJ6eh0az2WDqrfk5_XT0A6A6Vr_2P4BTYYk-4</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1779459597</pqid></control><display><type>article</type><title>Combining risk factors with faecal immunochemical test outcome for selecting CRC screenees for colonoscopy</title><source>MEDLINE</source><source>BMJ Journals - NESLi2</source><source>PubMed Central</source><creator>Stegeman, Inge ; de Wijkerslooth, Thomas R ; Stoop, Esther M ; van Leerdam, Monique E ; Dekker, Evelien ; van Ballegooijen, Marjolein ; Kuipers, Ernst J ; Fockens, Paul ; Kraaijenhagen, Roderik A ; Bossuyt, Patrick M</creator><creatorcontrib>Stegeman, Inge ; de Wijkerslooth, Thomas R ; Stoop, Esther M ; van Leerdam, Monique E ; Dekker, Evelien ; van Ballegooijen, Marjolein ; Kuipers, Ernst J ; Fockens, Paul ; Kraaijenhagen, Roderik A ; Bossuyt, Patrick M</creatorcontrib><description>Objective Faecal immunochemical testing (FIT) is increasingly used in colorectal cancer (CRC) screening but has a less than perfect sensitivity. Combining risk stratification, based on established risk factors for advanced neoplasia, with the FIT result for allocating screenees to colonoscopy could increase the sensitivity and diagnostic yield of FIT-based screening. We explored the use of a risk prediction model in CRC screening. Design We collected data in the colonoscopy arm of the Colonoscopy or Colonography for Screening study, a multicentre screening trial. For this study 6600 randomly selected, asymptomatic men and women between 50 years and 75 years of age were invited to undergo colonoscopy. Screening participants were asked for one sample FIT (OC-sensor) and to complete a risk questionnaire prior to colonoscopy. Based on the questionnaire data and the FIT results, we developed a multivariable risk model with the following factors: total calcium intake, family history, age and FIT result. We evaluated goodness-of-fit, calibration and discrimination, and compared it with a model based on primary screening with FIT only. Results Of the 1426 screening participants, 1112 (78%) completed the questionnaire and FIT. Of these, 101 (9.1%) had advanced neoplasia. The risk based model significantly increased the goodness-of-fit compared with a model based on FIT only (p<0.001). Discrimination improved significantly with the risk-based model (area under the receiver operating characteristic (ROC) curve: from 0.69 to 0.76, (p=0.02)). Calibration was good (Hosmer-Lemeshow test; p=0.94). By offering colonoscopy to the 102 patients at highest risk, rather than to the 102 cases with a FIT result >50 ng/mL, 5 more cases of advanced neoplasia would be detected (net reclassification improvement 0.054, p=0.073). Conclusions Adding risk based stratification increases the accuracy FIT-based CRC screening and could be used in preselection for colonoscopy in CRC screening programmes.</description><identifier>ISSN: 0017-5749</identifier><identifier>EISSN: 1468-3288</identifier><identifier>DOI: 10.1136/gutjnl-2013-305013</identifier><identifier>PMID: 23964098</identifier><identifier>CODEN: GUTTAK</identifier><language>eng</language><publisher>England: BMJ Publishing Group LTD</publisher><subject>Age ; Aged ; Algorithms ; Colonoscopy ; Colorectal cancer ; Colorectal Neoplasms - diagnosis ; Colorectal Neoplasms - etiology ; Decision Support Techniques ; Early Detection of Cancer - methods ; Family medical history ; Feces - chemistry ; Female ; Health risk assessment ; Humans ; Logistic Models ; Male ; Middle Aged ; Multivariate Analysis ; Participation ; Population ; Questionnaires ; Risk Assessment ; Risk Factors ; ROC Curve ; Studies ; Surveillance ; Surveys and Questionnaires ; Tumors ; Women</subject><ispartof>Gut, 2014-03, Vol.63 (3), p.466-471</ispartof><rights>Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions</rights><rights>Copyright: 2014 Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-b369t-612f4524d993226f047529016266dca7c4b9e2a52c05454d2a6c2449bf7a90ce3</citedby><cites>FETCH-LOGICAL-b369t-612f4524d993226f047529016266dca7c4b9e2a52c05454d2a6c2449bf7a90ce3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttp://gut.bmj.com/content/63/3/466.full.pdf$$EPDF$$P50$$Gbmj$$H</linktopdf><linktohtml>$$Uhttp://gut.bmj.com/content/63/3/466.full$$EHTML$$P50$$Gbmj$$H</linktohtml><link.rule.ids>114,115,315,781,785,3197,23576,27929,27930,77605,77636</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23964098$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Stegeman, Inge</creatorcontrib><creatorcontrib>de Wijkerslooth, Thomas R</creatorcontrib><creatorcontrib>Stoop, Esther M</creatorcontrib><creatorcontrib>van Leerdam, Monique E</creatorcontrib><creatorcontrib>Dekker, Evelien</creatorcontrib><creatorcontrib>van Ballegooijen, Marjolein</creatorcontrib><creatorcontrib>Kuipers, Ernst J</creatorcontrib><creatorcontrib>Fockens, Paul</creatorcontrib><creatorcontrib>Kraaijenhagen, Roderik A</creatorcontrib><creatorcontrib>Bossuyt, Patrick M</creatorcontrib><title>Combining risk factors with faecal immunochemical test outcome for selecting CRC screenees for colonoscopy</title><title>Gut</title><addtitle>Gut</addtitle><description>Objective Faecal immunochemical testing (FIT) is increasingly used in colorectal cancer (CRC) screening but has a less than perfect sensitivity. Combining risk stratification, based on established risk factors for advanced neoplasia, with the FIT result for allocating screenees to colonoscopy could increase the sensitivity and diagnostic yield of FIT-based screening. We explored the use of a risk prediction model in CRC screening. Design We collected data in the colonoscopy arm of the Colonoscopy or Colonography for Screening study, a multicentre screening trial. For this study 6600 randomly selected, asymptomatic men and women between 50 years and 75 years of age were invited to undergo colonoscopy. Screening participants were asked for one sample FIT (OC-sensor) and to complete a risk questionnaire prior to colonoscopy. Based on the questionnaire data and the FIT results, we developed a multivariable risk model with the following factors: total calcium intake, family history, age and FIT result. We evaluated goodness-of-fit, calibration and discrimination, and compared it with a model based on primary screening with FIT only. Results Of the 1426 screening participants, 1112 (78%) completed the questionnaire and FIT. Of these, 101 (9.1%) had advanced neoplasia. The risk based model significantly increased the goodness-of-fit compared with a model based on FIT only (p<0.001). Discrimination improved significantly with the risk-based model (area under the receiver operating characteristic (ROC) curve: from 0.69 to 0.76, (p=0.02)). Calibration was good (Hosmer-Lemeshow test; p=0.94). By offering colonoscopy to the 102 patients at highest risk, rather than to the 102 cases with a FIT result >50 ng/mL, 5 more cases of advanced neoplasia would be detected (net reclassification improvement 0.054, p=0.073). Conclusions Adding risk based stratification increases the accuracy FIT-based CRC screening and could be used in preselection for colonoscopy in CRC screening programmes.</description><subject>Age</subject><subject>Aged</subject><subject>Algorithms</subject><subject>Colonoscopy</subject><subject>Colorectal cancer</subject><subject>Colorectal Neoplasms - diagnosis</subject><subject>Colorectal Neoplasms - etiology</subject><subject>Decision Support Techniques</subject><subject>Early Detection of Cancer - methods</subject><subject>Family medical history</subject><subject>Feces - chemistry</subject><subject>Female</subject><subject>Health risk assessment</subject><subject>Humans</subject><subject>Logistic Models</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Multivariate Analysis</subject><subject>Participation</subject><subject>Population</subject><subject>Questionnaires</subject><subject>Risk Assessment</subject><subject>Risk Factors</subject><subject>ROC Curve</subject><subject>Studies</subject><subject>Surveillance</subject><subject>Surveys and Questionnaires</subject><subject>Tumors</subject><subject>Women</subject><issn>0017-5749</issn><issn>1468-3288</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqNkUtLxDAUhYMozvj4Ay6k4MZNNUnzaJZSfMGAILoOaXqrrU0zJi3iv7djRxeuXB0u97uHwz0InRB8QUgmLl_Goe27lGKSpRnmk-ygJWEiTzOa57toiTGRKZdMLdBBjC3GOM8V2UcLminBsMqXqC28K5u-6V-S0MS3pDZ28CEmH83wOg1gTZc0zo29t6_gms04QBwSPw7WO0hqH5IIHdhhY1E8Fkm0AaAHiN876zvf-2j9-vMI7dWmi3C81UP0fHP9VNylq4fb--JqlZaZUEMqCK0Zp6xSKqNU1JhJThUmggpRWSMtKxVQw6nFnHFWUSMsZUyVtTQKW8gO0fnsuw7-fZzCatdEC11nevBj1IQpRSjBkkzo2R-09WPop3SaSKkYV1zJiaIzZYOPMUCt16FxJnxqgvWmCT03oTdN6LmJ6eh0az2WDqrfk5_XT0A6A6Vr_2P4BTYYk-4</recordid><startdate>201403</startdate><enddate>201403</enddate><creator>Stegeman, Inge</creator><creator>de Wijkerslooth, Thomas R</creator><creator>Stoop, Esther M</creator><creator>van Leerdam, Monique E</creator><creator>Dekker, Evelien</creator><creator>van Ballegooijen, Marjolein</creator><creator>Kuipers, Ernst J</creator><creator>Fockens, Paul</creator><creator>Kraaijenhagen, Roderik A</creator><creator>Bossuyt, Patrick M</creator><general>BMJ Publishing Group LTD</general><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>88I</scope><scope>8AF</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BTHHO</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope></search><sort><creationdate>201403</creationdate><title>Combining risk factors with faecal immunochemical test outcome for selecting CRC screenees for colonoscopy</title><author>Stegeman, Inge ; de Wijkerslooth, Thomas R ; Stoop, Esther M ; van Leerdam, Monique E ; Dekker, Evelien ; van Ballegooijen, Marjolein ; Kuipers, Ernst J ; Fockens, Paul ; Kraaijenhagen, Roderik A ; Bossuyt, Patrick M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-b369t-612f4524d993226f047529016266dca7c4b9e2a52c05454d2a6c2449bf7a90ce3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Age</topic><topic>Aged</topic><topic>Algorithms</topic><topic>Colonoscopy</topic><topic>Colorectal cancer</topic><topic>Colorectal Neoplasms - diagnosis</topic><topic>Colorectal Neoplasms - etiology</topic><topic>Decision Support Techniques</topic><topic>Early Detection of Cancer - methods</topic><topic>Family medical history</topic><topic>Feces - chemistry</topic><topic>Female</topic><topic>Health risk assessment</topic><topic>Humans</topic><topic>Logistic Models</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Multivariate Analysis</topic><topic>Participation</topic><topic>Population</topic><topic>Questionnaires</topic><topic>Risk Assessment</topic><topic>Risk Factors</topic><topic>ROC Curve</topic><topic>Studies</topic><topic>Surveillance</topic><topic>Surveys and Questionnaires</topic><topic>Tumors</topic><topic>Women</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Stegeman, Inge</creatorcontrib><creatorcontrib>de Wijkerslooth, Thomas R</creatorcontrib><creatorcontrib>Stoop, Esther M</creatorcontrib><creatorcontrib>van Leerdam, Monique E</creatorcontrib><creatorcontrib>Dekker, Evelien</creatorcontrib><creatorcontrib>van Ballegooijen, Marjolein</creatorcontrib><creatorcontrib>Kuipers, Ernst J</creatorcontrib><creatorcontrib>Fockens, Paul</creatorcontrib><creatorcontrib>Kraaijenhagen, Roderik A</creatorcontrib><creatorcontrib>Bossuyt, Patrick M</creatorcontrib><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>Science Database (Alumni Edition)</collection><collection>STEM Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</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 Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection (ProQuest)</collection><collection>BMJ Journals</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database (ProQuest)</collection><collection>Biological Science 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 Basic</collection><collection>MEDLINE - Academic</collection><jtitle>Gut</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Stegeman, Inge</au><au>de Wijkerslooth, Thomas R</au><au>Stoop, Esther M</au><au>van Leerdam, Monique E</au><au>Dekker, Evelien</au><au>van Ballegooijen, Marjolein</au><au>Kuipers, Ernst J</au><au>Fockens, Paul</au><au>Kraaijenhagen, Roderik A</au><au>Bossuyt, Patrick M</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Combining risk factors with faecal immunochemical test outcome for selecting CRC screenees for colonoscopy</atitle><jtitle>Gut</jtitle><addtitle>Gut</addtitle><date>2014-03</date><risdate>2014</risdate><volume>63</volume><issue>3</issue><spage>466</spage><epage>471</epage><pages>466-471</pages><issn>0017-5749</issn><eissn>1468-3288</eissn><coden>GUTTAK</coden><abstract>Objective Faecal immunochemical testing (FIT) is increasingly used in colorectal cancer (CRC) screening but has a less than perfect sensitivity. Combining risk stratification, based on established risk factors for advanced neoplasia, with the FIT result for allocating screenees to colonoscopy could increase the sensitivity and diagnostic yield of FIT-based screening. We explored the use of a risk prediction model in CRC screening. Design We collected data in the colonoscopy arm of the Colonoscopy or Colonography for Screening study, a multicentre screening trial. For this study 6600 randomly selected, asymptomatic men and women between 50 years and 75 years of age were invited to undergo colonoscopy. Screening participants were asked for one sample FIT (OC-sensor) and to complete a risk questionnaire prior to colonoscopy. Based on the questionnaire data and the FIT results, we developed a multivariable risk model with the following factors: total calcium intake, family history, age and FIT result. We evaluated goodness-of-fit, calibration and discrimination, and compared it with a model based on primary screening with FIT only. Results Of the 1426 screening participants, 1112 (78%) completed the questionnaire and FIT. Of these, 101 (9.1%) had advanced neoplasia. The risk based model significantly increased the goodness-of-fit compared with a model based on FIT only (p<0.001). Discrimination improved significantly with the risk-based model (area under the receiver operating characteristic (ROC) curve: from 0.69 to 0.76, (p=0.02)). Calibration was good (Hosmer-Lemeshow test; p=0.94). By offering colonoscopy to the 102 patients at highest risk, rather than to the 102 cases with a FIT result >50 ng/mL, 5 more cases of advanced neoplasia would be detected (net reclassification improvement 0.054, p=0.073). Conclusions Adding risk based stratification increases the accuracy FIT-based CRC screening and could be used in preselection for colonoscopy in CRC screening programmes.</abstract><cop>England</cop><pub>BMJ Publishing Group LTD</pub><pmid>23964098</pmid><doi>10.1136/gutjnl-2013-305013</doi><tpages>6</tpages></addata></record> |
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| subjects | Age Aged Algorithms Colonoscopy Colorectal cancer Colorectal Neoplasms - diagnosis Colorectal Neoplasms - etiology Decision Support Techniques Early Detection of Cancer - methods Family medical history Feces - chemistry Female Health risk assessment Humans Logistic Models Male Middle Aged Multivariate Analysis Participation Population Questionnaires Risk Assessment Risk Factors ROC Curve Studies Surveillance Surveys and Questionnaires Tumors Women |
| title | Combining risk factors with faecal immunochemical test outcome for selecting CRC screenees for colonoscopy |
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