Aspirin and Nonsteroidal Anti-inflammatory Drugs for the Primary Prevention of Colorectal Cancer: Weighing the Evidence
Bibliographic record
Abstract
Letters6 November 2007Aspirin and Nonsteroidal Anti-inflammatory Drugs for the Primary Prevention of Colorectal Cancer: Weighing the EvidenceMary B. Barton, MD, MPP and Marion M. TorchiaMary B. Barton, MD, MPPFrom the Agency for Healthcare Research and Quality, Rockville, MD 20850.Search for more papers by this author and Marion M. TorchiaFrom the Agency for Healthcare Research and Quality, Rockville, MD 20850.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-147-9-200711060-00023 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail IN RESPONSE:We want to respond to Dr. Stürmer and colleagues, regarding the systematic review posting on the Agency for Healthcare Research and Quality Web site The appendices were inadvertently omitted from the Web posting. The mistake has been corrected, and the full systematic review is now available on the Web site at www.ahrq.gov/clinic/uspstf07/aspcolo/aspcoloes.pdf(1). We regret the frustration this error has caused.Reference1. Rostom A, Dubé C, Lewin G, Tsertsvadze A, Barrowman N, Code C, et al. Use of aspirin and NSAIDs to prevent colorectal cancer. Evidence Synthesis no. 45 (Prepared by the University of Ottawa Evidence-based Practice Center at The University of Ottawa under contract no. 290-02-0021). Bethesda, MD: Agency for Healthcare Research and Quality; March 2007. AHRQ publication no. 07-0596-EF-1. Accessed at www.ahrq.gov/clinic/uspstf07/aspcolo/aspcoloes.pdf on 28 August 2007. Google Scholar Author, Article, and Disclosure InformationAffiliations: From the Agency for Healthcare Research and Quality, Rockville, MD 20850.Disclosures: None disclosed. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoThe Use of Aspirin for Primary Prevention of Colorectal Cancer: A Systematic Review Prepared for the U.S. Preventive Services Task Force Catherine Dubé , Alaa Rostom , Gabriela Lewin , Alexander Tsertsvadze , Nicholas Barrowman , Catherine Code , Margaret Sampson , and David Moher Nonsteroidal Anti-inflammatory Drugs and Cyclooxygenase-2 Inhibitors for Primary Prevention of Colorectal Cancer: A Systematic Review Prepared for the U.S. Preventive Services Task Force Alaa Rostom , Catherine Dubé , Gabriela Lewin , Alexander Tsertsvadze , Nicholas Barrowman , Catherine Code , Margaret Sampson , and David Moher Aspirin and Nonsteroidal Anti-inflammatory Drugs for the Primary Prevention of Colorectal Cancer: Weighing the Evidence Til Stürmer , Julie E. Buring , and Robert J. Glynn Metrics 6 November 2007Volume 147, Issue 9Page: 674-675KeywordsCancer preventionColorectal cancerConflicts of interestDrugsEmotionsHealth care qualityHealth services researchResearch quality assessmentSystematic reviews ePublished: 6 November 2007 Issue Published: 6 November 2007 Copyright & PermissionsCopyright © 2007 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.070 | 0.332 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".