Evaluating clinical practice guidelines developed for the management of thyroid nodules and thyroid cancers and assessing the reliability and validity of the AGREE instrument
Bibliographic record
Abstract
OBJECTIVES: We assessed the quality of a sample of clinical guidelines for thyroid nodules and thyroid cancers, using the Appraisal of Guidelines Research and Evaluation (AGREE) instrument. We also evaluated the reliability and validity of the AGREE instrument and summarized the key recommendations of the appraised guidelines. METHODS: Twenty-six clinical researchers and endocrinologists who had been trained in the principles of developing clinical guidelines and using the AGREE instrument participated in the study and appraised the guidelines. Clinical guidelines selected via a systematic search were assessed, each by eight participants. We compared the AGREE domain scores of the guidelines, and compared the participants' scores before and after group discussions. We used Cronbach's alpha, and intraclass correlation coefficients to assess the reliability, and the Spearman's rho to assess the correlation between the overall assessment and other variables. RESULTS: Seven guidelines were included in the study. 'Scope and purpose' and 'clarity and presentation' achieved the highest domain scores. 'Applicability' received the lowest domain scores and reliability coefficients. 'Rigor of development' and 'clarity and presentation' obtained the highest correlations with overall assessment scores. There was a significant relationship between the overall assessment score and the numbers of algorithms, tables and figures in the guidelines. CONCLUSIONS: We identified three clinical guidelines that obtained high overall assessment scores and were recommended for use in practice. Our findings have important implications for those developing clinical guidelines, especially as clarity and presentation significantly influenced the participants' assessment of the guidelines. The developers should ensure that the recommendations are presented clearly and unambiguously, and flowcharts, algorithms and other tools are developed to help the users in applying the recommendations into practice. The optimal number of appraisers for each guideline is four. Further work is needed to improve the 'applicability' domain of the AGREE.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.159 | 0.428 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; both teacher heads agree on what is shown here.
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".