American Society of Clinical Oncology Clinical Practice Guidelines: Formal Systematic Review–Based Consensus Methodology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The American Society of Clinical Oncology (ASCO) guidelines program employs a systematic review-based methodology to produce evidence-based guidelines. This is consistent with the stance of the Institute of Medicine on guideline development, which is that high-quality evidence syntheses form the basis for recommendation development. In the absence of high-quality evidence, recommendation development becomes more complex. One option is to provide no recommendations or withdraw a guideline topic. However, it is often the areas of greatest uncertainty in which the evidentiary base is incomplete, and thus, guidelines are needed most. To provide recommendations in such circumstances, an explicit methodology is needed to ensure that a credible process is undertaken, and rigorous, reliable advice is provided. In 2010, the ASCO Board of Directors approved development of guideline recommendations using consensus methodology. A modified Delphi approach to recommendation development, based on the best available data identified in a systematic review, was piloted with an ASCO guideline. Consensus was achieved through the rating of a series of recommendations by a large group of clinicians, including academic and community-based content and methodology experts. A prespecified threshold of agreement was determined to indicate when consensus was achieved. Consensus was defined as agreement by ≥ 75% of raters. The formal consensus methodology used by ASCO enabled development of guideline recommendations on a challenging clinical issue based on limited evidence using a rigorous, transparent, and explicit method. This methodology is proposed for development of future ASCO guidelines on topics for which limited evidence is available.
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.
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 | 0.366 | 0.782 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.057 | 0.021 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.014 |
| 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 it