Evaluation of the Level of Evidence Supporting the Recommendations Constituting the American Academy of Dermatology Clinical Practice Guidelines: Cross-Sectional Analysis
Bibliographic record
Abstract
Background Clinical practice guidelines are evidence-based recommendations used by physicians to improve patient care. These guidelines provide the physician with an assessment of the benefits and harms of a treatment and its alternatives. Therefore, it is essential that the clinical practice guidelines be based on the strongest available evidence. Numerous studies in a variety of different fields of medicine have demonstrated that recommendations supported by weak evidence are a common theme in clinical practice guidelines. A clinical guideline based solely on weak evidence has the capability to reduce the quality of care provided by physicians. Objective Our primary objective is to evaluate the levels of evidence supporting the recommendations constituting the American Academy of Dermatology clinical practice guidelines. Methods Using a cross-sectional study design, authors SM and RO located all current clinical practice guidelines on the American Academy of Dermatology website on June 10, 2017, and December 11, 2019. Each recommendation and its corresponding evidence rating were extracted in a duplicate and blinded fashion. A consensus meeting was planned a priori to resolve disagreements in extractions or stratifications. Results In total, 6 clinical guidelines and their subsections were screened and 899 recommendations were identified. Our final data set included 841 recommendations, as 58 recommendations contained no level of evidence and were excluded from calculations. Many recommendations were supported by a moderate level of evidence and therefore received a B rating (346/841, 41.1%). Roughly one-third of the recommendations were supported by a strong level of evidence and were given an A rating (n=307, 36.5%). The clinical practice guideline with the highest overall strength of evidence was regarding the treatment of acne, which had 17 of 35 (48.6%) recommendations supported by strong evidence and only 2 (5.7%) supported by weak evidence. The clinical practice guideline with the fewest recommendations supported by strong evidence was melanoma (13/63, 20.6%). Conclusions Clinical practice guidelines that lack strong supporting evidence could negatively affect patient care, and dermatologists should be mindful that not all recommendations are supported by the strongest level of evidence. An increased quantity of quality research needs to be performed in the field of dermatology to improve the evidence supporting the American Academy of Dermatology clinical practice guidelines.
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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 | 0.174 | 0.384 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.019 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".