BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

441 related articles for article (PubMed ID: 30821827)

  • 1. Development and Validation of a Multivariable Lung Cancer Risk Prediction Model That Includes Low-Dose Computed Tomography Screening Results: A Secondary Analysis of Data From the National Lung Screening Trial.
    Tammemägi MC; Ten Haaf K; Toumazis I; Kong CY; Han SS; Jeon J; Commins J; Riley T; Meza R
    JAMA Netw Open; 2019 Mar; 2(3):e190204. PubMed ID: 30821827
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deep Learning Using Chest Radiographs to Identify High-Risk Smokers for Lung Cancer Screening Computed Tomography: Development and Validation of a Prediction Model.
    Lu MT; Raghu VK; Mayrhofer T; Aerts HJWL; Hoffmann U
    Ann Intern Med; 2020 Nov; 173(9):704-713. PubMed ID: 32866413
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Participant selection for lung cancer screening by risk modelling (the Pan-Canadian Early Detection of Lung Cancer [PanCan] study): a single-arm, prospective study.
    Tammemagi MC; Schmidt H; Martel S; McWilliams A; Goffin JR; Johnston MR; Nicholas G; Tremblay A; Bhatia R; Liu G; Soghrati K; Yasufuku K; Hwang DM; Laberge F; Gingras M; Pasian S; Couture C; Mayo JR; Nasute Fauerbach PV; Atkar-Khattra S; Peacock SJ; Cressman S; Ionescu D; English JC; Finley RJ; Yee J; Puksa S; Stewart L; Tsai S; Haider E; Boylan C; Cutz JC; Manos D; Xu Z; Goss GD; Seely JM; Amjadi K; Sekhon HS; Burrowes P; MacEachern P; Urbanski S; Sin DD; Tan WC; Leighl NB; Shepherd FA; Evans WK; Tsao MS; Lam S;
    Lancet Oncol; 2017 Nov; 18(11):1523-1531. PubMed ID: 29055736
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Lung cancer incidence and mortality in National Lung Screening Trial participants who underwent low-dose CT prevalence screening: a retrospective cohort analysis of a randomised, multicentre, diagnostic screening trial.
    Patz EF; Greco E; Gatsonis C; Pinsky P; Kramer BS; Aberle DR
    Lancet Oncol; 2016 May; 17(5):590-9. PubMed ID: 27009070
    [TBL] [Abstract][Full Text] [Related]  

  • 5. USPSTF2013 versus PLCOm2012 lung cancer screening eligibility criteria (International Lung Screening Trial): interim analysis of a prospective cohort study.
    Tammemägi MC; Ruparel M; Tremblay A; Myers R; Mayo J; Yee J; Atkar-Khattra S; Yuan R; Cressman S; English J; Bedard E; MacEachern P; Burrowes P; Quaife SL; Marshall H; Yang I; Bowman R; Passmore L; McWilliams A; Brims F; Lim KP; Mo L; Melsom S; Saffar B; Teh M; Sheehan R; Kuok Y; Manser R; Irving L; Steinfort D; McCusker M; Pascoe D; Fogarty P; Stone E; Lam DCL; Ng MY; Vardhanabhuti V; Berg CD; Hung RJ; Janes SM; Fong K; Lam S
    Lancet Oncol; 2022 Jan; 23(1):138-148. PubMed ID: 34902336
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Comparison Between Radiological Semantic Features and Lung-RADS in Predicting Malignancy of Screen-Detected Lung Nodules in the National Lung Screening Trial.
    Li Q; Balagurunathan Y; Liu Y; Qi J; Schabath MB; Ye Z; Gillies RJ
    Clin Lung Cancer; 2018 Mar; 19(2):148-156.e3. PubMed ID: 29137847
    [TBL] [Abstract][Full Text] [Related]  

  • 7. OWL: an optimized and independently validated machine learning prediction model for lung cancer screening based on the UK Biobank, PLCO, and NLST populations.
    Pan Z; Zhang R; Shen S; Lin Y; Zhang L; Wang X; Ye Q; Wang X; Chen J; Zhao Y; Christiani DC; Li Y; Chen F; Wei Y
    EBioMedicine; 2023 Feb; 88():104443. PubMed ID: 36701900
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Identifying high risk individuals for targeted lung cancer screening: Independent validation of the PLCO
    Weber M; Yap S; Goldsbury D; Manners D; Tammemagi M; Marshall H; Brims F; McWilliams A; Fong K; Kang YJ; Caruana M; Banks E; Canfell K
    Int J Cancer; 2017 Jul; 141(2):242-253. PubMed ID: 28249359
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Analysis of lung cancer risk model (PLCO
    Lebrett MB; Balata H; Evison M; Colligan D; Duerden R; Elton P; Greaves M; Howells J; Irion K; Karunaratne D; Lyons J; Mellor S; Myerscough A; Newton T; Sharman A; Smith E; Taylor B; Taylor S; Walsham A; Whittaker J; Barber PV; Tonge J; Robbins HA; Booton R; Crosbie PAJ
    Thorax; 2020 Aug; 75(8):661-668. PubMed ID: 32631933
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Risk Model-Based Lung Cancer Screening and Racial and Ethnic Disparities in the US.
    Choi E; Ding VY; Luo SJ; Ten Haaf K; Wu JT; Aredo JV; Wilkens LR; Freedman ND; Backhus LM; Leung AN; Meza R; Lui NS; Haiman CA; Park SL; Le Marchand L; Neal JW; Cheng I; Wakelee HA; Tammemägi MC; Han SS
    JAMA Oncol; 2023 Dec; 9(12):1640-1648. PubMed ID: 37883107
    [TBL] [Abstract][Full Text] [Related]  

  • 11. LDCT lung cancer screening in populations at different risk for lung cancer.
    Teles GBDS; Macedo ACS; Chate RC; Valente VAT; Funari MBG; Szarf G
    BMJ Open Respir Res; 2020 Feb; 7(1):. PubMed ID: 33371010
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Protocol and Rationale for the International Lung Screening Trial.
    Lim KP; Marshall H; Tammemägi M; Brims F; McWilliams A; Stone E; Manser R; Canfell K; Weber M; Connelly L; Bowman RV; Yang IA; Fogarty P; Mayo J; Yee J; Myers R; Atkar-Khattra S; Lam DCL; Rosell A; Berg CD; Fong KM; Lam S;
    Ann Am Thorac Soc; 2020 Apr; 17(4):503-512. PubMed ID: 32011914
    [No Abstract]   [Full Text] [Related]  

  • 13. Recalibration of a Deep Learning Model for Low-Dose Computed Tomographic Images to Inform Lung Cancer Screening Intervals.
    Landy R; Wang VL; Baldwin DR; Pinsky PF; Cheung LC; Castle PE; Skarzynski M; Robbins HA; Katki HA
    JAMA Netw Open; 2023 Mar; 6(3):e233273. PubMed ID: 36929398
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Evaluation of Prediction Models for Identifying Malignancy in Pulmonary Nodules Detected via Low-Dose Computed Tomography.
    González Maldonado S; Delorme S; Hüsing A; Motsch E; Kauczor HU; Heussel CP; Kaaks R
    JAMA Netw Open; 2020 Feb; 3(2):e1921221. PubMed ID: 32058555
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study.
    Ten Haaf K; Jeon J; Tammemägi MC; Han SS; Kong CY; Plevritis SK; Feuer EJ; de Koning HJ; Steyerberg EW; Meza R
    PLoS Med; 2017 Apr; 14(4):e1002277. PubMed ID: 28376113
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Factors Associated with a Positive Baseline Screening Exam Result in the National Lung Screening Trial.
    Balekian AA; Tanner NT; Fisher JM; Silvestri GA; Gould MK
    Ann Am Thorac Soc; 2016 Sep; 13(9):1568-74. PubMed ID: 27387658
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Detection of lung cancer through low-dose CT screening (NELSON): a prespecified analysis of screening test performance and interval cancers.
    Horeweg N; Scholten ET; de Jong PA; van der Aalst CM; Weenink C; Lammers JW; Nackaerts K; Vliegenthart R; ten Haaf K; Yousaf-Khan UA; Heuvelmans MA; Thunnissen E; Oudkerk M; Mali W; de Koning HJ
    Lancet Oncol; 2014 Nov; 15(12):1342-50. PubMed ID: 25282284
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Methods for Using Race and Ethnicity in Prediction Models for Lung Cancer Screening Eligibility.
    Landy R; Gomez I; Caverly TJ; Kawamoto K; Rivera MP; Robbins HA; Young CD; Chaturvedi AK; Cheung LC; Katki HA
    JAMA Netw Open; 2023 Sep; 6(9):e2331155. PubMed ID: 37721755
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Factors Associated With Nonadherence to Lung Cancer Screening Across Multiple Screening Time Points.
    Lin Y; Liang LJ; Ding R; Prosper AE; Aberle DR; Hsu W
    JAMA Netw Open; 2023 May; 6(5):e2315250. PubMed ID: 37227725
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Sensitivity of US Preventive Services Task Force and PLCOm2012 lung cancer screening eligibility criteria in individuals with lung cancer in South Dakota self-reporting as Indigenous and non-Indigenous.
    Tammemägi MC; Cina K; Kitts AKB; Koop D; Petereit MA; Sargent M; Petereit DG
    Cancer; 2023 Dec; 129(24):3894-3904. PubMed ID: 37807694
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 23.