Complementary and alternative medicine mention and recommendations in pancreatic cancer clinical practice guidelines: A systematic review and quality assessment
Bibliographic record
Abstract
Background: Pancreatic cancer is the third leading cause of cancer death in the United States, which is attributed to limited treatment options. Complementary and alternative medicine (CAM) therapies have been proposed to provide benefits in treating pancreatic cancer. Despite its importance in treatment, clinicians are not generally well equipped to counsel their patients about CAM therapies. This review identified the quantity and assessed the quality of clinical practice guidelines (CPGs) providing CAM recommendations for the treatment and/or management of pancreatic cancer. Methods: A systematic review was conducted to identify pancreatic cancer CPGs. MEDLINE, EMBASE and CINAHL were searched from 2011 to 2022. The Guidelines International Network (GIN) and the National Center for Complementary and Integrative Health (NCCIH) websites were also searched. Eligible CPGs published by non-profit agencies on treatment and/or management of pancreatic cancer for adults were assessed using the Appraisal of Guidelines, Research and Evaluation II (AGREE II) instrument. Results: From 31 eligible search results, 7 CPGs mentioned CAM and 3 CPGs made CAM recommendations. The mean scaled domain percentages of the CPGs in this study (overall, CAM-specific) were as follows: scope and purpose (81.3%, 77.8%), stakeholder involvement (63.9%, 42.6%), rigor-of-development (51.0%, 40.3%), clarity-of-presentation (83.3%, 54.6%), applicability (42.3%, 30.5%), and editorial independence (58.3%, 58.3%). Conclusions: Evaluation of the CPGs demonstrated that quality varied both within and between CPGs. CPGs that scored well could be used by patients and clinicians as the basis for discussion for the use of CAM therapies. Future research should identify other appropriate CAM therapies for further development of CPGs for pancreatic cancer. Registration: The protocol was registered on PROSPERO (registration number: CRD42022334025).
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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 | 0.086 | 0.316 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.021 | 0.027 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".