Evaluation of the Guidelines for Penile Cancer Treatment: Overview and Assessment
Bibliographic record
Abstract
Introduction: Medical organizations have provided evidence-based guidelines for penile cancer treatment. This current review aims to compare and appraise guidelines on penile cancer treatment to provide a useful summary for clinicians. make an evidence-based approach in the clinical practice. Materials and Methods: We searched in PubMed and Medline for guidelines published between January 1, 2010, and February 1, 2020. The search query terms were “penile cancer,” “penile tumor,” “guidelines,” and “penile malignancy.” In the final analysis, we include the most recent versions of relevant guidelines published in English. The Appraisal of Guidelines for Research and Evaluation II (AGREE II) instrument was used to appraise the quality of each guideline. Results: In the final analysis, we included guidelines from the National Comprehensive Cancer Network (updated in 2020), The European Association of Urology (updated in 2018), and The European Society for Medical Oncology (published in 2013). The overall agreement among reviewers was excellent. The range of scores for each domain was as follows: scope and purpose (46% to 61%); stakeholder involvement (33% to 60%); rigor of development (34% to 69%); clarity and presentation (61% to 81%); applicability (33% to 59%) and editorial independence (52% to 78%). The European Association of Urology and National Comprehensive Cancer Network clinical practice guidelines received better scores according to the AGREE II evaluation. Conclusion: Despite the effort made by the guidelines groups to make a practical guideline regarding penile cancer treatment, the actual available evidence is weak. However, we believe our recommendations offer clear guidance.
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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 | 0.117 | 0.347 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.025 | 0.018 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| 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".