Conflict between Guideline Methodologic Quality and Recommendation Validity: A Potential Problem for Practitioners
Bibliographic record
Abstract
BACKGROUND: It is not clear if good methodologic quality in current practice guidelines necessarily leads to more valid recommendations, i.e., those that are supported with consistent research evidence or, when evidence is conflicting or lacking, with sufficient consensus among the guideline development team. To help clarify this issue, we assessed whether there is a link between methodologic quality and recommendation validity in practice guidelines for the use of laboratory tests in the management of patients with non-small cell lung cancer (NSCLC). METHODS: We conducted a systematic review of data on laboratory tests in NSCLC published in English or in French within the last 10 years and retrieved 11 practice guidelines for the use of these tests. The guidelines were critically appraised and scored for methodologic quality and recommendation validity based on the Appraisal of Guidelines Research and Evaluation (AGREE) criteria and on the systematic review. RESULTS: Overall, these 11 guidelines had considerable shortcomings in methodologic quality and, to a lesser extent, in recommendation validity. Practice guidelines with the best methodologic quality were not necessarily the most valid in their recommendations, and conversely. CONCLUSIONS: Poor methodologic quality and lack of recommendation validity in laboratory medicine call for methodologic standards of guideline development and for international collaboration of guideline development agencies. We advise readers of guidelines to critically evaluate the methods used as well as the content of the recommendations before adopting them for use in practice.
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 | 0.787 | 0.943 |
| Meta-epidemiology (narrow) | 0.002 | 0.004 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.018 | 0.018 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.016 | 0.014 |
| Open science | 0.010 | 0.009 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier 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".