Models in the Development of Clinical Practice Guidelines
Bibliographic record
Abstract
Letters7 April 2015Models in the Development of Clinical Practice GuidelinesIoannis M. Zacharioudakis, MD, Fainareti N. Zervou, MD, and Eleftherios Mylonakis, MD, PhDIoannis M. Zacharioudakis, MDFrom Warren Alpert Medical School of Brown University, Providence, Rhode Island.Search for more papers by this author, Fainareti N. Zervou, MDFrom Warren Alpert Medical School of Brown University, Providence, Rhode Island.Search for more papers by this author, and Eleftherios Mylonakis, MD, PhDFrom Warren Alpert Medical School of Brown University, Providence, Rhode Island.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/L15-5075 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail TO THE EDITOR:Habbema and colleagues (1) have presented a particularly interesting article about the position of models in clinical practice guidelines. Indeed, models can bridge the gap between direct evidence provided from randomized, controlled trials (RCTs) or observational studies and questions raised in daily practice. To estimate the degree that models are used in the development of current guidelines, we evaluated the list of the 100 most cited guidelines of the National Guideline Clearinghouse (www.guideline.gov) that we had identified for a previous study. The number of citations was extracted from the Thomson Reuters Web of Science (formerly ISI Web ...References1. Habbema JD, Wilt TJ, Etzioni R, Nelson HD, Schechter CB, Lawrence WF, et al. Models in the development of clinical practice guidelines. Ann Intern Med. 2014;161:812-8. [PMID: 25437409] doi:10.7326/M14-0845 LinkGoogle Scholar2. Husereau D, Drummond M, Petrou S, Carswell C, Moher D, Greenberg D, et al; CHEERS Task Force. Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement. BMJ. 2013;346:f1049. [PMID: 23529982] doi:10.1136/bmj.f1049 CrossrefMedlineGoogle Scholar3. Higgins JP, Altman DG, Gøtzsche PC, Jüni P, Moher D, Oxman AD, et al; Cochrane Bias Methods Group. The Cochrane Collaboration's tool for assessing risk of bias in randomised trials. BMJ. 2011;343:d5928. [PMID: 22008217] doi:10.1136/bmj.d5928 CrossrefMedlineGoogle Scholar4. Wells GA, Shea B, O'Connell D, Peterson J, Welch V, Losos M, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. 2014. Accessed at www.ohri.ca/programs/clinical_epidemiology/oxford.asp on 10 December 2014. Google Scholar Author, Article, and Disclosure InformationAffiliations: From Warren Alpert Medical School of Brown University, Providence, Rhode Island.Disclosures: Authors have disclosed no conflicts of interest. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterest Forms.do?msNum=L15-0055. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoModels in the Development of Clinical Practice Guidelines J. Dik F. Habbema , Timothy J. Wilt , Ruth Etzioni , Heidi D. Nelson , Clyde B. Schechter , William F. Lawrence , Joy Melnikow , Karen M. Kuntz , Douglas K. Owens , and Eric J. Feuer Models in the Development of Clinical Practice Guidelines J. Dik F. Habbema , Timothy J. Wilt , Ruth Etzioni , Heidi D. Nelson , Clyde B. Schechter , William F. Lawrence , Joy Melnikow , Karen M. Kuntz , Douglas K. Owens , and Eric J. Feuer Models in the Development of Clinical Practice Guidelines J. Dik F. Habbema , Timothy J. Wilt , and Ruth Etzioni Models in the Development of Clinical Practice Guidelines J. Dik F. Habbema , Timothy J. Wilt , and Ruth Etzioni Metrics Cited ByCollaborative Modeling: Experience of the U.S. Preventive Services Task Force 7 April 2015Volume 162, Issue 7Page: 529-530KeywordsConflicts of interestDisclosureForecastingHealth economicsMathematical modelsObservational studiesReproducibilityTreatment guidelines ePublished: 7 April 2015 Issue Published: 7 April 2015 CopyrightCopyright © 2015 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 | 0.239 | 0.529 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.011 | 0.007 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.007 | 0.011 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.015 | 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".