The Endocrine Society Guidelines: When the Confidence Cart Goes Before the Evidence Horse
Bibliographic record
Abstract
CONTEXT: In 2005, the Endocrine Society (TES) adopted the GRADE system of developing clinical practice guidelines. Grading of Recommendations, Assessment, Development, and Evaluation working group guidance suggests that strong recommendations based on low or very low (L/VL) confidence may often be inappropriate, and has offered a taxonomy of paradigmatic situations in which strong recommendations based on L/VL confidence estimates may be appropriate. OBJECTIVE: We sought to characterize strong recommendations of TES based on L/VL confidence evidence. DATA SOURCES AND EXTRACTION: We identified all strong recommendations based on L/VL confidence evidence published in TES guidelines between 2005 and 2011. We identified those consistent with one of the paradigmatic situations in the taxonomy. DATA SYNTHESIS: Two hundred six of 357 (58%) of the recommendations of TES were strong; of these, 121 (59%) were based on L/VL confidence evidence. Of these 121, 35 (29%) were consistent with one of the paradigmatic situations. The most common situation (13, 11%) was of a strong recommendation against the intervention because of low confidence evidence for benefit and high confidence evidence for harm. The remaining 86 (71%) comprised 43 (36%) "best practice" statements for which sensible alternatives do not exist; 5 (4%) in which recommendations were for "additional research"; 5 (4%) in which greater confidence in the estimates was warranted; and 33 (27%) for which we could not find a compelling explanation for the incongruence. CONCLUSIONS: Guideline panels should beware of formulating strong recommendations when confidence in estimates is low. Our taxonomy when such recommendations are appropriate may be helpful.
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 | 0.343 | 0.753 |
| Meta-epidemiology (narrow) | 0.002 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.018 | 0.017 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.023 | 0.027 |
| Open science | 0.014 | 0.012 |
| Research integrity | 0.021 | 0.034 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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".