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Record W2072770626 · doi:10.1002/jrsm.1089

Special issue on inclusion of non‐randomized studies in systematic reviews

2013· erratum· en· W2072770626 on OpenAlexfundaboutno aff
Barnaby C Reeves, George A. Wells

Bibliographic record

VenueResearch Synthesis Methods · 2013
Typeerratum
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsnot available
FundersNational Institute for Health and Care ResearchMedical Research CouncilUniversity of OttawaU.S. Department of Health and Human ServicesAgency for Healthcare Research and QualityScottish Government
KeywordsSystematic reviewMedicineHealth services researchLibrary scienceAgency (philosophy)Psychological interventionHealth careInclusion (mineral)Government (linguistics)Political scienceMEDLINEMedical educationFamily medicinePublic healthSociologyNursingSocial scienceLaw

Abstract

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Research Synthesis Methods 4(1) The institutional affiliation for Peter Tugwell and the Acknowledgement/Funding Section appears incomplete in some of the articles in this Special Issue. The complete and correct information are shown here. An introduction to methodological issues when including non-randomized studies in systematic reviews on the effects of interventions Barnaby C. Reeves,a*† Julian P. T. Higgins,b,c Craig Ramsay,d Beverley Shea,e Peter Tugwellf,g and George A. Wellsg,h Research Synthesis Methods 4(1): 1–11 Acknowledgements: The workshop was supported financially by the Agency for Healthcare Quality and Research (AHRQ; through the Ottawa Collaborating Agency of the ARHQ) and by a grant from the Cochrane Collaboration Discretionary Fund. BCR is supported in part by the UK National Institute for Health Research Bristol Cardiovascular Biomedical Research Unit. JPTH is supported by MRC Grant U105285807. The Health Services Research Unit is funded by the Scottish Government Executive Health Department. The views expressed in this article are those of the authors, who are responsible for their content and do not represent the views of AHRQ, the Cochrane Collaboration or its registered entities, committees or working groups, the Campbell Collaboration, or the National Institute for Health Research. No statement in this report should be construed as an official position of AHRQ or of the US Department of Health and Human Services. ——— aClinical Trials and Evaluation Unit, School of Clinical Sciences, University of Bristol, Bristol, UK bMRC Biostatistics Unit, Cambridge, UK cCentre for Reviews and Dissemination, University of York, York, UK dHealth Services Research Unit, University of Aberdeen, Aberdeen, UK eCommunity Information and Epidemiological Technologies, Institute of Population Health, Ottawa, ON, Canada fCentre for Global Health, Institute of Population Health, Ottawa, ON, Canada gDepartment of Medicine, University of Ottawa, Ottawa, Canada hDepartment of Epidemiology and Community Medicine, University of Ottawa, Ottawa, ON, Canada *Correspondence to: Barnaby C. Reeves, Clinical Trials and Evaluation Unit, University of Bristol, Level 7 Queen's Building, Bristol Royal Infirmary, Bristol BS2 8HW, UK. †E-mail: [email protected] ———— Issues relating to study design and risk of bias when including non-randomized studies in systematic reviews on the effects of interventions Julian P. T. Higgins,a,b*† Craig Ramsay,c Barnaby C. Reeves,d Jonathan J. Deeks,e Beverley Shea,f Jeffrey C. Valentine,g Peter Tugwellh,i and George Wellsh,j Research Synthesis Methods 4(1): 12–25 Acknowledgements: We are grateful to all the workshop participants (see the Appendix to Paper 1); all of whom contributed to the discussions that provided the foundation for this paper. The workshop was supported financially by the Agency for Healthcare Quality and Research (AHRQ; through the Ottawa Collaborating Agency of the ARHQ) and by a grant from the Cochrane Collaboration Discretionary Fund. JPTH is supported by the Medical Research Council (Unit Programme number U105285807). The Health Services Research Unit is funded by the Scottish Government Executive Health Department. BCR is supported in part by the UK National Institute for Health Research Bristol Cardiovascular Biomedical Research Unit. The views expressed in this article are those of the authors, who are responsible for their content and do not represent the views of AHRQ, the Cochrane Collaboration or its registered entities, committees or working groups, the Campbell Collaboration, or the National Institute for Health Research. No statement in this report should be construed as an official position of AHRQ or of the US Department of Health and Human Services. ——— aMRC Biostatistics Unit, Cambridge, UK bCentre for Reviews and Dissemination, University of York, York, UK cHealth Services Research Unit, University of Aberdeen, Aberdeen, UK dBristol Heart Institute, University of Bristol, Bristol Royal Infirmary, Bristol, UK ePublic Health, Epidemiology and Biostatistics, University of Birmingham, Birmingham, UK fCommunity Information and Epidemiological Technologies, Institute of Population Health, University of Ottawa, Ottawa, ON, Canada gCollege of Education and Human Development, University of Louisville, Louisville, KY, USA hDepartment of Medicine, University of Ottawa, Ottawa, ON, Canada iCentre for Global Health, Institute of Population Health, Ottawa, ON, Canada jDepartment of Epidemiology and Community Medicine, University of Ottawa, Ottawa, ON, Canada *Correspondence to: Julian Higgins, MRC Biostatistics Unit, Institute of Public Health, Robinson Way, Cambridge, CB2 0SR, UK. †E-mail: [email protected] ———— Issues relating to selective reporting when including non-randomized studies in systematic reviews on the effects of healthcare interventions Susan L. Norris,a*† David Moher,b Barnaby C. Reeves,c Beverley Shea,d Yoon Loke,e Sarah Garner,f Laurie Anderson,g Peter Tugwellh,i and George Wellsi,j Research Synthesis Methods 4(1): 36–47 Acknowledgements: The workshop was supported by the Agency for Healthcare Quality and Research (AHRQ; through the Ottawa Collaborating Agency of the ARHQ) and by a grant from the Cochrane Collaboration Discretionary Fund. BCR is supported in part by the UK National Institute for Health Research Bristol Biomedical Research Unit in Cardiovascular Medicine. DM is supported by the University of Ottawa Research Chair. The views expressed in this article are those of the authors, who are responsible for their content and do not represent the views of AHRQ, the Cochrane Collaboration or its registered entities, committees or working groups, the Campbell Collaboration, or the National Institute for Health Research. No statement in this report should be construed as an official position of AHRQ or of the US Department of Health and Human Services. Participants at the workshop contributed to discussions of this paper. ——— aDepartment of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA bOttawa Hospital Research Institute, Ottawa, ON, Canada cBristol Heart Institute, Bristol Royal Infirmary, University of Bristol, Bristol, UK dCommunity Information and Epidemiological Technologies, Institute of Population Health, Ottawa, ON, Canada eFaculty of Medicine and Health Sciences, University of East Anglia, Norwich, UK fNational Institute for Health and Clinical Excellence, London, UK gSchool of Public Health, University of Washington, Seattle, WA, USA hCentre for Global Health, Institute of Population Health, Ottawa, ON, Canada iDepartment of Medicine, University of Ottawa, Ottawa, ON, Canada jDepartment of Epidemiology and Community Medicine, University of Ottawa, ON, Canada *Correspondence to: Susan L. Norris, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, Mail Stop: BICC Portland, OR 97239, USA. †E-mail: [email protected] ———— Non-randomized studies as a source of complementary, sequential or replacement evidence for randomized controlled trials in systematic reviews on the effects of interventions Holger J. Schünemann,a,b,*,† Peter Tugwell,c,d,e Barnaby C. Reeves,f Elie A. Akl,a,g Nancy Santesso,a Frederick A. Spencer,b Beverley Shea,c George Wellsd,i and Mark Helfandh Research Synthesis Methods 4(1): 49–62 Acknowledgements: We are grateful to the workshop participants, all of whom contributed to the discussions that provided the foundation for this paper. The views expressed in this article are those of the authors, who are responsible for their content and do not represent the views of AHRQ, the Cochrane Collaboration or its registered entities, committees or working groups, the Campbell Collaboration, or the National Institute for Health Research. No statement in this report should be construed as an official position of AHRQ or of the US Department of Health and Human Services. ——— aDepartment of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada bDepartment of Medicine, McMaster University, Hamilton, ON, Canada cClinical Epidemiology Unit, Ottawa Hospital Research Institute, Ottawa Hospital, Ottawa, ON, Canada dDepartment of Medicine, University of Ottawa, Ottawa, ON, Canada eCentre for Global Health, Institute of Population Health, Ottawa, ON, Canada fBristol Heart Institute, University of Bristol, Bristol Royal Infirmary, Bristol, UK gDepartment of Internal Medicine, American University of Beirut, Beirut, Lebanon hPortland VA Medical Center and Department of Medicine, Oregon Health and Science University, Portland, OR, USA iDepartment of Epidemiology and Community Medicine, University of Ottawa, ON, Canada *Correspondence to: Holger J. Schünemann, Department of Clinical Epidemiology and Biostatistics, McMaster University Health Sciences Centre, Room 2C10B, 1280 Main Street West, Hamilton, ON L8S 4K1, Canada. †E-mail: [email protected] ———— Checklists of methodological issues for review authors to consider when including non-randomized studies in systematic reviews George A. Wells,a,b,*,† Beverley Shea,c Julian P. T. Higgins,d,e Jonathan Sterne,f Peter Tugwellb,g and Barnaby C. Reevesh Research Synthesis Methods 4(1): 63–77 Funding: The workshop was supported financially by the Agency for Healthcare Quality and Research (AHRQ; through the Ottawa Collaborating Agency of the ARHQ) and by a grant from the Cochrane Collaboration Discretionary Fund. BCR is supported in part by the UK National Institute for Health Research Bristol Cardiovascular Biomedical Research Unit. JPTH was supported by MRC Grant U105285807. The Health Services Research Unit is funded by the Scottish Government Executive Health Department. The views expressed in this article are those of the authors, who are responsible for their content and do not represent the views of AHRQ, the Cochrane Collaboration or its registered entities, committees or working groups, the Campbell Collaboration, or the National Institute for Health Research. No statement in this report should be construed as an official position of AHRQ or of the US Department of Health and Human Services. ——— aDepartment of Epidemiology and Community Medicine, University of Ottawa, Ottawa, ON, Canada bDepartment of Medicine, University of Ottawa, Ottawa, ON, Canada cCommunity Information and Epidemiological Technologies, Institute of Population Health, Ottawa, ON, Canada dMRC Biostatistics Unit, Cambridge, UK eCentre for Reviews and Dissemination, University of York, York, UK fSchool of Social and Community Medicine, University of Bristol, Bristol, UK gCentre for Global Health, Institute of Population Health, Ottawa, ON, Canada hClinical Trials and Evaluation Unit, School of Clinical Sciences, University of Bristol, Bristol, UK *Correspondence to: George Wells, Department of Epidemiology and Community Medicine, University of Ottawa, 451 Smyth Road, Ottawa, ON K1H 8M5, Canada. †E-mail: [email protected]

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 imitation

Not 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.

metaresearch head score (Codex)0.227
metaresearch head score (Gemma)0.491
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.773
Threshold uncertainty score0.953

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2270.491
Meta-epidemiology (narrow)0.0050.006
Meta-epidemiology (broad)0.0160.014
Bibliometrics0.0260.016
Science and technology studies0.0040.009
Scholarly communication0.0210.015
Open science0.0120.015
Research integrity0.0230.020
Insufficient payload (model declined to judge)0.1470.044

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.

Opus teacher head0.903
GPT teacher head0.708
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainMethods
GenreEditorial

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".

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Citations7
Published2013
Admission routes2
Has abstractyes

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