Impact of the Children's Oncology Group's supportive care clinical practice guideline endorsement program: An institutional survey
Bibliographic record
Abstract
BACKGROUND: Supportive care clinical practice guidelines (CPGs) facilitate the incorporation of the best available evidence into pediatric cancer care. We aimed to assess the impact of the work of the Children's Oncology Group (COG) Supportive Care Guideline Task Force on institutional supportive care practices. PROCEDURE: An online survey was distributed to representatives at 209 COG sites to assess the awareness, use, and helpfulness of COG-endorsed supportive care CPGs. Availability of institutional policies regarding 13 topics addressed by current COG-endorsed CPGs was also assessed. Respondents described their institutional processes for developing supportive care policies. RESULTS: Representatives from 92 COG sites responded to the survey, and 78% (72/92) were "very aware" of the COG-endorsed supportive care CPGs. On average, sites had policies that addressed seven COG-endorsed supportive care CPG topics (median = 7, range: 0-12). Only 45% (41/92) of sites reported having institutional processes for developing supportive care policies. Of these, most (76%, 31/41) reported that the COG-endorsed CPGs have a medium or large impact on policy development. Compared with sites without processes for supportive care policy development, sites with established processes had policies on a greater number of topics aligned with current COG-endorsed CPG topics (mean = 6.6, range: 0-12 vs mean = 7.9, range: 2-12; p = 0.027). CONCLUSIONS: Most site respondents were aware of the COG-endorsed supportive care CPGs. Less than half of the COG sites represented in the survey have processes in place to implement supportive care policies. Improvement in local implementation is required to ensure that patients at COG sites receive evidence-based supportive care.
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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 | 0.015 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".