American Society of Clinical Oncology Clinical Practice Guidelines: Formal Systematic Review–Based Consensus Methodology
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.
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 | 0.556 | 0.655 |
| Meta-epidemiology (narrow) | 0.004 | 0.006 |
| Meta-epidemiology (broad) | 0.011 | 0.015 |
| Bibliometrics | 0.038 | 0.030 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.011 | 0.012 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".