Computed Tomography Screening for Lung Cancer: What Is a Positive Screen?
Bibliographic record
Abstract
Editorials19 February 2013Computed Tomography Screening for Lung Cancer: What Is a Positive Screen?Stephen Lam, MD, Annette McWilliams, MB, John Mayo, MD, and Martin Tammemagi, PhDStephen Lam, MDFrom British Columbia Cancer Agency, Vancouver, British Columbia, Canada; Vancouver General Hospital, Vancouver, British Columbia, Canada; and Brock University, St. Catharines, Ontario, Canada.Search for more papers by this author, Annette McWilliams, MBFrom British Columbia Cancer Agency, Vancouver, British Columbia, Canada; Vancouver General Hospital, Vancouver, British Columbia, Canada; and Brock University, St. Catharines, Ontario, Canada.Search for more papers by this author, John Mayo, MDFrom British Columbia Cancer Agency, Vancouver, British Columbia, Canada; Vancouver General Hospital, Vancouver, British Columbia, Canada; and Brock University, St. Catharines, Ontario, Canada.Search for more papers by this author, and Martin Tammemagi, PhDFrom British Columbia Cancer Agency, Vancouver, British Columbia, Canada; Vancouver General Hospital, Vancouver, British Columbia, Canada; and Brock University, St. Catharines, Ontario, Canada.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-158-4-201302190-00011 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail The NLST (National Lung Screening Trial) showed that screening with low-dose thoracic computed tomography (CT) reduces lung cancer mortality by 20% (1). Several organizations recommend (2) or suggest (3) that clinicians offer screening to persons who meet either the NLST criteria for lung cancer risk or modified versions of these criteria if comprehensive multidisciplinary coordinated care and follow-up similar to those provided to NLST participants are available. A major issue for practical and cost-effective implementation of low-dose CT screening for lung cancer is the definition of a positive scan.A positive low-dose CT scan, by definition, triggers diagnostic work-up. Most ...References1. Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, Fagerstrom RM, et al; National Lung Screening Trial Research Team. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011;365:395-409. [PMID: 21714641] CrossrefMedlineGoogle Scholar2. Wood DE, Eapen GA, Ettinger DS, Hou L, Jackman D, Kazerooni E, et al. Lung cancer screening. J Natl Compr Canc Netw. 2012;10:240-65. [PMID: 22308518] CrossrefMedlineGoogle Scholar3. Bach PB, Mirkin JN, Oliver TK, Azzoli CG, Berry DA, Brawley OW, et al. Benefits and harms of CT screening for lung cancer: a systematic review. JAMA. 2012;307:2418-29. [PMID: 22610500] CrossrefMedlineGoogle Scholar4. Henschke CI, Yip R, Yankelevitz DF, Smith JP; International Early Lung Cancer Action Program Investigators. Definition of a positive test result in computed tomography screening for lung cancer. A cohort study. Ann Intern Med. 2013;158:246-52. LinkGoogle Scholar5. Zurawska JH, Jen R, Lam S, Coxson HO, Leipsic J, Sin DD. What to do when a smoker's CT scan is “normal”?: Implications for lung cancer screening. Chest. 2012;141:1147-52. [PMID: 22553261] CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAuthors: Stephen Lam, MD; Annette McWilliams, MB; John Mayo, MD; Martin Tammemagi, PhDAffiliations: From British Columbia Cancer Agency, Vancouver, British Columbia, Canada; Vancouver General Hospital, Vancouver, British Columbia, Canada; and Brock University, St. Catharines, Ontario, Canada.Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M13-0085.Corresponding Author: Stephen Lam, MD, British Columbia Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada; e-mail, slam2@bccancer.bc.ca.Current Author Addresses: Drs. Lam and McWilliams: Department of Integrative Oncology, British Columbia Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada.Dr. Mayo: Department of Radiology, Vancouver General Hospital, 899 West 12 Avenue, Vancouver, British Columbia V5Z 1M9, Canada.Dr. Tammemagi: Department of Community Health Sciences, Brock University, Walker Complex-Academic South, Room 306, 500 Glenridge Avenue, St. Catharines, Ontario L2S 3A1, Canada. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoDefinition of a Positive Test Result in Computed Tomography Screening for Lung Cancer Claudia I. Henschke , Rowena Yip , David F. Yankelevitz , and James P. Smith , for the International Early Lung Cancer Action Program Investigators* Metrics Cited byLung cancer screeningImproving the Management of High Cost Anticancer Drugs in a Health Care SystemCost-Effectiveness Analyses of Lung Cancer Screening Strategies Using Low-Dose Computed Tomography: a Systematic ReviewLong-term Oncologic and Financial Implications of Lung Cancer ScreeningScreening tests: a review with examplesRecent Clinical Advances in Lung Cancer ManagementCT screening for lung cancer: countdown to implementationResults of the Two Incidence Screenings in the National Lung Screening TrialComputed Tomography Screening for Lung CancerGuglielmo M. Trovato, MD, Marco Sperandeo, MD, and Daniela Catalano, MDComputed Tomography Screening for Lung CancerClaudia I. Henschke, PhD, MD, Rowena Yip, MPH, David F. Yankelevitz, MD, and James P. Smith, MD 19 February 2013Volume 158, Issue 4Page: 289-290KeywordsCancer screeningComputed axial tomographyEmphysemaLung and intrathoracic tumorsLung cancer screeningLungsMortalityPopulation statisticsPrevention, policy, and public healthSurgical resection ePublished: 19 February 2013 Issue Published: 19 February 2013 Copyright & PermissionsCopyright © 2013 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.022 | 0.017 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".