001     182341
005     20240229145716.0
024 7 _ |a 10.1002/ijc.34340
|2 doi
024 7 _ |a pmid:36305647
|2 pmid
024 7 _ |a 0020-7136
|2 ISSN
024 7 _ |a 1097-0215
|2 ISSN
024 7 _ |a altmetric:137818439
|2 altmetric
037 _ _ |a DKFZ-2022-02584
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Wu, Wendy Yi-Ying
|0 0000-0002-6169-5155
|b 0
245 _ _ |a Assessment of the EarlyCDT-Lung test as an early biomarker of lung cancer in ever-smokers - A retrospective nested case-control study in two prospective cohorts.
260 _ _ |a Bognor Regis
|c 2023
|b Wiley-Liss
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1678877447_29495
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
500 _ _ |a 2023 May 1;152(9):2002-2010
520 _ _ |a The EarlyCDT-Lung test is a blood-based autoantibody assay intended to identify high-risk individuals for low-dose computed tomography lung cancer screening. However, there is a paucity of evidence on the performance of the EarlyCDT-Lung test in ever-smokers. We conducted a nested case-control study within two prospective cohorts to evaluate the risk-discriminatory performance of the EarlyCDT-Lung test using pre-diagnostic blood samples from 154 future lung cancer cases and 154 matched controls. Cases were selected from those who had ever smoked and had a pre-diagnostic blood samples less than 3 years prior to diagnosis. Conditional logistic regression was used to estimate the association between EarlyCDT-Lung test results and lung cancer risk. Sensitivity and specificity of the EarlyCDT-Lung test were calculated in all subjects and subgroups based on age, smoking history, lung cancer stage, sample collection time before diagnosis and year of sample collection. The overall lung cancer odds ratios were 0.89 (95% CI, 0.34-2.30) for a moderate risk EarlyCDT-Lung test result and 1.09 (95% CI, 0.48-2.47) for a high-risk test result compared to no significant test result. The overall sensitivity was 8.4% (95% CI, 4.6-14) and overall specificity was 92% (95% CI, 87-96) when considering a high-risk result as positive. Stratified analysis indicated higher sensitivity (17%, 95% CI, 7.2-32.1) in subjects with blood drawn up to 1 year prior to diagnosis. In conclusion, our study does not support a role of the EarlyCDT-Lung test in identifying the high-risk subjects in ever-smokers for lung cancer screening in the EPIC and NSHDS cohorts.
536 _ _ |a 313 - Krebsrisikofaktoren und Prävention (POF4-313)
|0 G:(DE-HGF)POF4-313
|c POF4-313
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
650 _ 7 |a EarlyCDT-Lung test
|2 Other
650 _ 7 |a biomarkers
|2 Other
650 _ 7 |a lung cancer
|2 Other
650 _ 7 |a prediagnostic samples
|2 Other
700 1 _ |a Haider, Zahra
|b 1
700 1 _ |a Feng, Xiaoshuang
|b 2
700 1 _ |a Heath, Alicia K
|0 0000-0001-6517-1300
|b 3
700 1 _ |a Tjønneland, Anne
|b 4
700 1 _ |a Agudo, Antonio
|b 5
700 1 _ |a Masala, Giovanna
|b 6
700 1 _ |a Robbins, Hilary A
|0 0000-0001-6041-6866
|b 7
700 1 _ |a Huerta, María-José
|b 8
700 1 _ |a Guevara, Marcela
|b 9
700 1 _ |a Schulze, Matthias B
|b 10
700 1 _ |a Rodriguez-Barranco, Miguel
|b 11
700 1 _ |a Vineis, Paolo
|b 12
700 1 _ |a Tumino, Rosario
|b 13
700 1 _ |a Kaaks, Rudolf
|0 P:(DE-He78)4b2dc91c9d1ac33a1c0e0777d0c1697a
|b 14
|u dkfz
700 1 _ |a Turzanski-Fortner, Renée
|0 P:(DE-He78)74a6af8347ec5cbd4b77e562e10ca1f2
|b 15
|u dkfz
700 1 _ |a Sieri, Sabina
|0 0000-0001-5201-172X
|b 16
700 1 _ |a Panico, Salvatore
|b 17
700 1 _ |a Nøst, Therese Haugdahl
|b 18
700 1 _ |a Sandanger, Torkjel M
|b 19
700 1 _ |a Braaten, Tonje
|b 20
700 1 _ |a Johansson, Mattias
|b 21
700 1 _ |a Melin, Beatrice
|b 22
700 1 _ |a Johansson, Mikael
|b 23
773 _ _ |a 10.1002/ijc.34340
|g p. ijc.34340
|0 PERI:(DE-600)1474822-8
|n 9
|p 2002-2010
|t International journal of cancer
|v 152
|y 2023
|x 0020-7136
909 C O |p VDB
|o oai:inrepo02.dkfz.de:182341
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 14
|6 P:(DE-He78)4b2dc91c9d1ac33a1c0e0777d0c1697a
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 15
|6 P:(DE-He78)74a6af8347ec5cbd4b77e562e10ca1f2
913 1 _ |a DE-HGF
|b Gesundheit
|l Krebsforschung
|1 G:(DE-HGF)POF4-310
|0 G:(DE-HGF)POF4-313
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-300
|4 G:(DE-HGF)POF
|v Krebsrisikofaktoren und Prävention
|x 0
914 1 _ |y 2022
915 _ _ |a DEAL Wiley
|0 StatID:(DE-HGF)3001
|2 StatID
|d 2021-02-04
|w ger
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2021-02-04
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1190
|2 StatID
|b Biological Abstracts
|d 2021-02-04
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2021-02-04
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
|d 2023-10-21
|w ger
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2023-10-21
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2023-10-21
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2023-10-21
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
|d 2023-10-21
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2023-10-21
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
|d 2023-10-21
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b INT J CANCER : 2022
|d 2023-10-21
915 _ _ |a IF >= 5
|0 StatID:(DE-HGF)9905
|2 StatID
|b INT J CANCER : 2022
|d 2023-10-21
920 1 _ |0 I:(DE-He78)C020-20160331
|k C020
|l C020 Epidemiologie von Krebs
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-He78)C020-20160331
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21