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A 10-year history of lung cancer practice guideline development: Process, productivity and impact

2007· article· en· W2241511433 on OpenAlexaff
William K. Evans, Christopher A. Smith, Yee Ung

Bibliographic record

VenueJournal of Clinical Oncology · 2007
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsMcMaster UniversityJuravinski Cancer CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineGuidelineLung cancerFamily medicineOncologyInternal medicinePathology

Abstract

fetched live from OpenAlex

17044 Background: CCO's Program in Evidence-based Care at McMaster University, has developed and disseminated clinical guidance documents through provincial DSGs for 10 years. The 37 member Lung DSG includes medical oncologists (17), radiation oncologists (11), thoracic surgeons (4), nurses (2), and a research coordinator. Pathologists (3), community/patient representatives (2), a medical resident and medical sociologist have previously been members. Methods: The LDSG has used the practice guideline (PG) development cycle described by Browman GP et al (JCO 1998; 16(3):1226–31). Results: 31 reports have been published in peer-reviewed journals, including 25 guidelines; all PGs are posted on the CCO website. Topics were initially selected on the basis of known practice variability (chemotherapy for Stage IV NSCLC) or clinical controversy (combined modality therapy for Stage III NSCLC); PGs for single chemotherapy drugs (6) or chemotherapy usage in specific situations (7) have dominated DSG activity; 5 PGs on radiotherapy alone and 3 on RT as part of CMT have been completed; recent PGs have been written for rare tumours (mesothelioma, thymoma) and diagnostic imaging (PET). Initially, PGs were based solely on published RCT evidence. Evidence from publicly accessible abstracts/meeting presentations, and Phase II trials (in the absence of higher quality evidence) is now considered. For rare tumours (thymoma), the DSG has used a Delphi consensus methodology. Knowledge transfer occurs through the DSG meeting process (twice yearly face-to-face; 2–4 teleconferences), practitioner feedback (PF), publications, presentations and web posting. PF using a standardized feedback questionnaire is generally high (59.9%) but varies by PG and discipline; PF is incorporated into final guideline documents. Guideline recommendations for the use of vinorelbine, gemcitabine, taxanes and erlotinib in NSCLC have been successful in securing government funding. No significant financial relationships to disclose.

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)0.176
metaresearch head score (Gemma)0.329
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.824
Threshold uncertainty score0.928

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1760.329
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0100.015
Science and technology studies0.0030.004
Scholarly communication0.0130.009
Open science0.0040.010
Research integrity0.0080.012
Insufficient payload (model declined to judge)0.0100.004

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 head0.293
GPT teacher head0.622
Teacher spread0.329 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainEvaluation
GenreEmpirical

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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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